├── 2022 ├── About.md ├── README.md ├── carpentries-pedagogy-week-1 │ └── README.md ├── cc1-collaborative-development │ ├── About.md │ ├── Anelda-Van-Der-Walt-Talarify │ │ └── Slides-and-video.md │ ├── CC1 - Introduction and overview of the call.pdf │ ├── CC1 - Introduction and overview of the call.pptx │ ├── Malvika-Sharan-OLS │ │ └── Slides.md │ ├── Mishka-Nemes-The-Turing │ │ └── Slides.md │ └── Toby-Hodges-Carpentries │ │ └── slides.md ├── cc10-product-management-sustainability-and-entrepreneurship │ ├── ABOUT.md │ ├── Alden Connor.pptx │ └── CC10 - Product management, sustainability and entrepreneurship CHAT.txt ├── cc2-launching-hosting-maintaining-your-training │ ├── ABOUT.md │ ├── CC2 - Introduction and overview of the call.pdf │ ├── CC2 - Introduction and overview of the call.pptx │ ├── Esther-Plomp-TUDelft │ │ └── Slides.md │ └── Sarah-Gibson-Jupyter-Binder │ │ └── Slides.md ├── cc3-developing-training-for-live-delivery-vs-self-paced-learning │ ├── ABOUT.md │ ├── Rodrigo-Sanchez-Pizani-King's-College-London │ │ └── Slides.md │ ├── Sarah-Nietopski-The-Alan-Turing-Institute │ │ └── Slides.md │ └── Zoom-chat ├── cc4-ethics-in-the-context-of-training │ ├── ABOUT.md │ ├── Zoom-chat │ └── ai-educators.pdf ├── cc5-widening-participation │ ├── ABOUT.md │ └── Zoom-chat ├── cc6-challenges-with-teaching-DS-and-AI │ ├── ABOUT.md │ └── Zoom-chat ├── cc7-continuous-evaluation-and-implementation-of-learner-feedback │ └── ABOUT.md ├── cc8-making-learning-memorable │ ├── 2022-7-14 Making Learning Memorable Turing HClare v2.pdf │ ├── 2022-7-14 Making Learning Memorable Turing HClare v2.pptx │ ├── 20220714_ImmersiveLearning_DPerezSuarez.pdf │ ├── ABOUT.md │ └── CC8 - Making learning memorable CHAT.txt ├── cc9-collaboration-between-industry-and-academia │ ├── ABOUT.md │ └── CC9 - Collaboration between industry and academia CHAT.txt └── graduation-session-1 │ └── ABOUT.md ├── 2023 ├── README.md ├── carpentries-pedagogy-week-1 │ └── README.md ├── cc1-identifying-learner-needs │ ├── README.md │ └── learner-needs.md ├── cc10-making-teaching-relevant-to-real-world-problems │ └── ReadME.md ├── cc2-challenges-with-teaching-ds-and-ai │ └── ReadME.md ├── cc3-post-pandemic-teaching │ └── ReadME.md ├── cc4-making-learning-memorable │ └── ReadMe.md ├── cc5-embedding-ethics-the-background │ └── ReadME.md ├── cc6-embedding-ethics-the-practicals │ └── ReadME.md ├── cc8-collaborative-development-and-delivery-of-teaching-materials │ └── ReadME.md ├── cc9-working-together-to-embed-data-science-across-disciplines │ └── ReadME.md └── intro-and-housekeeping-slides │ └── ReadME.md ├── LICENSE ├── README.md └── code-of-conduct.md /2022/About.md: -------------------------------------------------------------------------------- 1 | A folder for the 2022 iteration of the DS and AI Educators' Programme. 2 | -------------------------------------------------------------------------------- /2022/README.md: -------------------------------------------------------------------------------- 1 | # The Data Science and AI Educators' Programme 2 | 3 | Welcome to the pilot run of the Data Science and AI Educators' Programme. 4 | Here, you will find all information, resources and relevant materials concerning the programme. They have been developed openly to be used, downloaded and amended as you need. 5 | 6 | | Week | Session(s) | Time | Date | Slides | Recordings | Collaborative document | 7 | | ----------- | ------------------------------- | ----------- | --------------| -------------- | -------------------- |-------------------- | 8 | | 1 | Pedagogy session 1 and 2 | 9am - 12:30pm (GMT+1) | Wednesday 18 May/Thursday 19 May | | [Wednesday 18 May](https://www.youtube.com/watch?v=qMMd-65gVdw&feature=youtu.be)

[Thursday 19 May](https://youtu.be/camSxoDVouY) | [Etherpad documents](https://github.com/alan-turing-institute/ds-ai-educators-programme/blob/main/2022/carpentries-pedagogy-week-1/README.md) | Complete | 9 | | 2 | CC1: Collaborative development and delivery of a new course | 10 - 11:30am (GMT+1) | Thursday 26 May | [Anelda Van Der Walt - Talarify](https://github.com/alan-turing-institute/ds-ai-educators-programme/blob/main/2022/cc1-collaborative-development/Anelda-Van-Der-Walt-Talarify/Slides-and-video.md)

[Mishka Nemes - The Alan Turing Institute](https://github.com/alan-turing-institute/ds-ai-educators-programme/blob/main/2022/cc1-collaborative-development/Mishka-Nemes-The-Turing/Slides.md)

[Toby Hodges - The Carpentries](https://github.com/alan-turing-institute/ds-ai-educators-programme/blob/main/2022/cc1-collaborative-development/Toby-Hodges-Carpentries/slides.md)

[Malvika Sharan - OLS](https://github.com/alan-turing-institute/ds-ai-educators-programme/blob/main/2022/cc1-collaborative-development/Malvika-Sharan-OLS/Slides.md) | [Anelda Van Der Walt recording](https://github.com/alan-turing-institute/ds-ai-educators-programme/blob/main/2022/cc1-collaborative-development/Anelda-Van-Der-Walt-Talarify/Slides-and-video.md)

[Cohort call recording](https://youtu.be/HYK0GiO_TRg) | [Etherpad document](https://github.com/alan-turing-institute/ds-ai-educators-programme/blob/main/2022/cc1-collaborative-development/About.md) | Complete | 10 | | 3 | CC2: Developing, launching and hosting your training project | 10 - 11:30am (GMT+1) | Tuesday 31 May | [Sarah Gibson - Jupyter](https://github.com/alan-turing-institute/ds-ai-educators-programme/blob/main/2022/cc2-launching-hosting-maintaining-your-training/Sarah-Gibson-Jupyter-Binder/Slides.md)

[Esther Plomp - FAIR principles](https://github.com/alan-turing-institute/ds-ai-educators-programme/blob/main/2022/cc2-launching-hosting-maintaining-your-training/Esther-Plomp-TUDelft/Slides.md) | [Cohort call recording](https://www.youtube.com/watch?v=AEqg9ygPk7w) | [HackMD](https://hackmd.io/F83C14OqTKmfgoAc9W9BhQ) | Complete | 11 | | 4 | CC3: Designing training for live delivery vs. self-aced delivery | 10 - 11:00am (GMT+1) | Thursday 9 June | [Sarah Nietopski - The Alan Turing Institute](https://github.com/alan-turing-institute/ds-ai-educators-programme/blob/main/2022/cc3-developing-training-for-live-delivery-vs-self-paced-learning/Sarah-Nietopski-The-Alan-Turing-Institute/Slides.md)

[Rodrigo Sanchez-Pizani - King's College London](https://github.com/alan-turing-institute/ds-ai-educators-programme/blob/main/2022/cc3-developing-training-for-live-delivery-vs-self-paced-learning/Rodrigo-Sanchez-Pizani-King's-College-London/Slides.md) | [Cohort call recording](https://www.youtube.com/watch?v=1rE78PfZW1w) | [HackMD](https://hackmd.io/7_MGYRWoR6mmf3Q9uMwK6A?both) | Complete | 12 | | 5 | CC4: Ethics in the context of training | 10 - 11am (GMT+1) | Thursday 16 June | [Chris Burr, Claudia Fischer - Turing and David Tarrant - ODI](https://github.com/alan-turing-institute/ds-ai-educators-programme/blob/main/2022/cc4-ethics-in-the-context-of-training/ai-educators.pdf) | [Cohort call recording](https://www.youtube.com/watch?v=k2eSE4RxXlk) | [HackMD](https://hackmd.io/IDtuYddoTIqo0Wm6kacJog?view) | Complete | 13 | | 6 | CC5: Widening participation in the context of training | 10 - 11am (GMT+1) | Thursday 23 June | n/a | [Cohort call recording](https://www.youtube.com/watch?v=k59kx2yaBN4) | [HackMD](https://hackmd.io/fQceWS7TSf6B-yQzrYatAw?both) | Complete | 14 | | 7 | CC6: Challenges with teaching DS and AI | 10 - 11am (GMT+1) | Thursday 30 June | n/a | [Cohort Call recording](https://youtu.be/nD8_oIErrPo) | [HackMD](https://hackmd.io/ohIMf55ZS_eeThplfd-ERg) | Complete | 15 | | 8 | CC7: Continuous evaluation and implementation of user/learner feedback | 10 - 11:00am (GMT+1) | Wednesday 6 July | n/a | n/a | [HackMD](https://hackmd.io/o0jc-jHkQNynCuaZp9vIDg) | Complete | 16 | | 9 | CC8: Making learning memorable | 10 - 11am (GMT+1) | Thursday 14 July | [Helen Clare - Jisc](https://github.com/alan-turing-institute/ds-ai-educators-programme/blob/main/2022/cc8-making-learning-memorable/2022-7-14%20Making%20Learning%20Memorable%20Turing%20HClare%20v2.pptx)

[Arron Lacey - The Alan Turing Institute](https://arronlacey.github.io/effective-learning-experience-talk/#/title-slide)

[David Perez-Suarez - UCL](https://docs.google.com/presentation/d/10XZpBCRtVrRubmrtYgCEQ-DS84ep0V7PTygErXnA1io/edit#slide=id.p) | [Cohort Call recording](https://youtu.be/3BvfWGwJ7Ao) | [HackMD](https://hackmd.io/P8F8b33rSpKUgAlwkGALmQ?view) | | 17 | | 10 | CC9: Collaboration between industry and academia in training | 10 - 11am (GMT+1) | Thursday 21 July | n/a | _In progress_ | [HackMD](https://hackmd.io/D3wjOJAXTDWq8jSM8d8seQ?view) | Complete | 18 | | 11 | CC10: Product management, sustainability, legacy and entrepreneurship | 10 - 11am (GMT+1) | Thursday 28 July | [Dr Alden Connor - The Alan Turing Institute](https://github.com/alan-turing-institute/ds-ai-educators-programme/blob/main/2022/cc10-product-management-sustainability-and-entrepreneurship/Alden%20Connor.pptx) | _In progress_ | [HackMD](https://hackmd.io/hvTOsKJaSOOAhAOFHPidBg) | Complete | 19 | | 12 | Graduation (session 1) | 10 - 11am (GMT+1) | Thursday 4 August | n/a | _In progress_ | [HackMD](https://hackmd.io/HeWzjj6-STeHSXk0LYAQmA) | Complete | 20 | | 13 | Graduation (session 2) | 3 - 4pm (GMT+1) | Thursday 11 August | n/a | _In progress_ | [HackMD](https://hackmd.io/M7Pt7Pz7RWG5grNUg90N4Q) | Complete | 21 | | 14 | Graduation (session 3) | 2 - 3pm (GMT+1) | Thursday 18 August | n/a | _In progress_ | [HackMD](https://hackmd.io/5PhLABwFTSySr-TBiJY3yA) | Complete | 22 | 23 | All training materials will be uploaded into the relevant folder as soon as possible after the sessions have taken place. 24 | -------------------------------------------------------------------------------- /2022/carpentries-pedagogy-week-1/README.md: -------------------------------------------------------------------------------- 1 | ## Slides 2 | [Live coding is a skill - The Carpentries.pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/8786976/Live.coding.is.a.skill.-.The.Carpentries.pdf) 3 | 4 | [Teaching is a Skill - The Carpentries.pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/8786980/Teaching.is.a.Skill.-.The.Carpentries.pdf) 5 | 6 | ## Recordings 7 | [The Carpentries Pedagogy Session 1 - 18 May](https://youtu.be/qMMd-65gVdw) 8 | 9 | [The Carpentries Pedagogy Session 2 - 19 May](https://youtu.be/camSxoDVouY) 10 | 11 | ## Collaborative documents 12 | [Wednesday 18 May Collaborative Document](https://pad.carpentries.org/2022-05-18-ATI) 13 | 14 | [Thursday 19 May Collaborative Document](https://pad.carpentries.org/2022-05-19-ATI) 15 | -------------------------------------------------------------------------------- /2022/cc1-collaborative-development/About.md: -------------------------------------------------------------------------------- 1 | # Collaborative development and delivery of a new course: Thursday 26 May 2022, 10 - 11:30am (GMT+1) 2 | 3 | ### This call will cover the following points: 4 | - Examples of good practice in collaborative lesson development 5 | - The importance of community in curriculum development 6 | - How and why community-led curriculum development is beneficial 7 | - Practical tips for lesson development 8 | - OLS, a case study: how to collaboratively develop a training programme 9 | - High-level training case studies from the Alan Turing Institute 10 | 11 | ### Today's speakers: 12 | - Toby Hodges _Director of Curriculum @ The Carpentries_ 13 | - Malvika Sharan _Senior Researcher @ The Alan Turing Institute_ 14 | - Mishka Nemes _Skills and Training Manager @ The Alan Turing Institute_ 15 | 16 | Apologies: 17 | - Anelda Van Der Walt _Founder and Director @ Talarify_ 18 | 19 | ### Collaborative document from the call: 20 | [Etherpad document](https://pad.carpentries.org/2022-05-26-turing-lessondev) 21 | 22 | ### Recording: 23 | [Collaborative development and delivery of a new course](https://www.youtube.com/watch?v=HYK0GiO_TRg) 24 | -------------------------------------------------------------------------------- /2022/cc1-collaborative-development/Anelda-Van-Der-Walt-Talarify/Slides-and-video.md: -------------------------------------------------------------------------------- 1 | Please find links to Anelda's talk, below. 2 | 3 | [Slides](https://docs.google.com/presentation/d/e/2PACX-1vTdzFNrh5v2--ITyjtdEHJEQ3z0Kl4FuWGVTq-kOTmiE6iGbTHQotlvWYLkd9bvVBH1A-CGfaJOvgo1/pub?start=false&loop=false&delayms=3000&slide=id.g12d394fd3dc_2_0) 4 | 5 | [Video recording](https://youtu.be/YwfY4UrjrhE) 6 | -------------------------------------------------------------------------------- /2022/cc1-collaborative-development/CC1 - Introduction and overview of the call.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/alan-turing-institute/ds-ai-educators-programme/df172e525d3e615170afa4011a2943df36fa64e0/2022/cc1-collaborative-development/CC1 - Introduction and overview of the call.pdf -------------------------------------------------------------------------------- /2022/cc1-collaborative-development/CC1 - Introduction and overview of the call.pptx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/alan-turing-institute/ds-ai-educators-programme/df172e525d3e615170afa4011a2943df36fa64e0/2022/cc1-collaborative-development/CC1 - Introduction and overview of the call.pptx -------------------------------------------------------------------------------- /2022/cc1-collaborative-development/Malvika-Sharan-OLS/Slides.md: -------------------------------------------------------------------------------- 1 | Please find Malvika's slides, below, as pdf. and ppt. documents. 2 | 3 | [Collaborative development and delivery of Open Life Science (OLS).pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/8778592/Collaborative.development.and.delivery.of.Open.Life.Science.OLS.pdf) 4 | 5 | [Collaborative development and delivery of Open Life Science (OLS).zip](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/8778593/Collaborative.development.and.delivery.of.Open.Life.Science.OLS.zip) 6 | -------------------------------------------------------------------------------- /2022/cc1-collaborative-development/Mishka-Nemes-The-Turing/Slides.md: -------------------------------------------------------------------------------- 1 | Please see Mishka's slides, below, as pdf. and ppt. documents. 2 | 3 | [Collaborative development and delivery - Case Studies from the Alan Turing Institute.pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/8778602/Collaborative.development.and.delivery.-.Case.Studies.from.the.Alan.Turing.Institute.pdf) 4 | 5 | [Collaborative development and delivery - Case Studies from the Alan Turing Institute.pptx](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/8778603/Collaborative.development.and.delivery.-.Case.Studies.from.the.Alan.Turing.Institute.pptx) 6 | 7 | 8 | -------------------------------------------------------------------------------- /2022/cc1-collaborative-development/Toby-Hodges-Carpentries/slides.md: -------------------------------------------------------------------------------- 1 | Please find Toby's slides, below, as pdf. and ppt. documents. 2 | 3 | [Collaborative development and delivery - Carpentries Incubator and Lesson Development.pptx](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/8778580/Collaborative.development.and.delivery.-.Carpentries.Incubator.and.Lesson.Development.pptx) 4 | 5 | [Collaborative development and delivery - Carpentries Incubator and Lesson Development.pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/8778582/Collaborative.development.and.delivery.-.Carpentries.Incubator.and.Lesson.Development.pdf) 6 | -------------------------------------------------------------------------------- /2022/cc10-product-management-sustainability-and-entrepreneurship/ABOUT.md: -------------------------------------------------------------------------------- 1 | # Product management, sustainability and entrepreneurship: Thursday 28 July 2022, 10 - 11:00am (GMT+1) 2 | 3 | ### This call will cover the following points: 4 | - 'You only fail when you don't try' inc Q&A 5 | - 'Product managers in academia: taking your research out of the lab' inc Q&A 6 | 7 | 8 | ### Today's speakers 9 | - [Esam Baboukhan](https://www.linkedin.com/in/esam-baboukhan/?originalSubdomain=uk) : [Transform Education](https://transformeducation.co.uk/) 10 | - [Dr Alden Conner](https://www.turing.ac.uk/people/business-team/alden-conner) : The Alan Turing Institute 11 | 12 | ### Collaborative document from the call 13 | [HackMD](https://hackmd.io/hvTOsKJaSOOAhAOFHPidBg) 14 | 15 | ### Recording 16 | 17 | -------------------------------------------------------------------------------- /2022/cc10-product-management-sustainability-and-entrepreneurship/Alden Connor.pptx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/alan-turing-institute/ds-ai-educators-programme/df172e525d3e615170afa4011a2943df36fa64e0/2022/cc10-product-management-sustainability-and-entrepreneurship/Alden Connor.pptx -------------------------------------------------------------------------------- /2022/cc10-product-management-sustainability-and-entrepreneurship/CC10 - Product management, sustainability and entrepreneurship CHAT.txt: -------------------------------------------------------------------------------- 1 | 00:21:47 Eric Atwell: I just found out 95% of promotion applications at Leeds Uni are successful: “you only fail if you don't try”! 2 | 00:22:20 Luisa Cutillo: Good to know Eric, because I did not try :-) 3 | 00:22:59 Luisa Cutillo: I am leaving at 1 pm! 4 | 00:23:29 Luisa Cutillo: After this meeting I will finish packing and go :-) 5 | 00:23:46 Salomey Afua Addo: lols 6 | 00:24:20 Esam: http://shor.by/whatisvoice 7 | 00:24:26 Eric Atwell: Here is the data: https://equality.leeds.ac.uk/equality-data/staff-data/staff-data-2022/ ... A total of 139 applications for promotion up to and including grade 9 were made by academic staff during 2020-21. Of these, 130 (95%) were successful." 8 | 00:27:06 Maarya Sharif: yes! 9 | 00:29:23 Ayesha Dunk (she/her): https://transformeducation.co.uk/ 10 | 00:32:19 Eric Atwell: Question: do I need insurance to cover legal liability in a "side hustle”? 11 | 00:33:16 Eric Atwell: So .. should I change my name to increase my ranking??? 12 | 00:33:50 Doschmund: @Eric, all business require insurance for liability.. Professional, Business, Employer etc., depending on how you operate 13 | 00:34:16 Eric Atwell: It's OK, I am already top hit for “Eric Atwell" as I have done Search Engine Optimisation myself 14 | 00:35:39 Doschmund: Some companies specifically request certain types of insurances before signing a contract 15 | 00:42:58 Andrew Moles: How do you dedicate enough time with the busy lives we lead? Is there a danger of burnout? I've been keen to start a blog on useful things I've learned, but just can't seem to find the time! 16 | 00:45:43 Andrew Moles: Great talk! 17 | 00:46:26 Luisa Cutillo: I like "Perfect is the enemy of good" end line! 18 | 00:46:31 Eric Atwell: This talk is a useful for teaching AI and DS MSc students 19 | 00:46:44 Malvika Sharan: Thanks Esam. 20 | 00:46:53 Malvika Sharan: That was a fantastic talk. 21 | 00:46:59 Maarya Sharif: Very motivating talk Esam! 22 | 00:47:21 Ogerta Elezaj: very useful and motivated talk 23 | 00:47:23 Ayesha Dunk (she/her): Great work, Esam - thank you so much! 24 | 00:48:17 Ayesha Dunk (she/her): If you'd like to join Esam's community, please follow: http://shor.by/edtechcommunity 25 | 00:57:31 Eric Atwell: How do we get funding to support all these roles? EPSRC funds Research Fellows to develop the core science (eg new AI software) but thn who funds the other roles?? 26 | 00:59:57 Eric Atwell: How can I guess hat users want?? 27 | 01:00:03 Doschmund: If the project is small and funding is limited, you could considering the skillset and the benefit that brings, rather than individual roles. In a larger complex project, these are add a lot of value 28 | 01:00:58 Doschmund: I wish there is an option to correct error, I noticed a few, sorry 🙂 29 | 01:15:22 Alden Conner (she/her): I have to drop off, thanks everyone! 30 | 01:15:24 Malvika Sharan: https://the-turing-way.netlify.app/project-design/persona.html 31 | 01:17:18 RYAN CROSBY: Thank you for today and the course as a whole 32 | 01:17:19 Luisa Cutillo: Thanks! 33 | 01:17:20 Noorhan: Thank you very much. 34 | 01:17:22 Adnane Ez-zizi: Bye 35 | 01:17:22 Ogerta Elezaj: Thank you! 36 | 01:17:23 Eric Atwell: Do we fill in a feedback form?? 37 | -------------------------------------------------------------------------------- /2022/cc2-launching-hosting-maintaining-your-training/ABOUT.md: -------------------------------------------------------------------------------- 1 | # Launching, hosting and maintaining your training project: Tuesday 31 May 2022, 10 - 11:30am (GMT+1) 2 | 3 | ### This call will cover the following points: 4 | - To reflect on challenges that learners might face in their computing environments 5 | - To reflect on challenges that the educator might face in providing computing environments for their learners 6 | - To understand what a computational environment is and why it is important 7 | - To understand how to teach with Binder and how to develop courses atop Binder 8 | - To learn about FAIR principles and how to apply this to training materials 9 | 10 | ### Today's speakers 11 | - [Matt Forshaw](https://twitter.com/MattForshaw) _Senior Advisor for Skills @ The Alan Turing Institute_ 12 | - [Sarah Gibson](https://sgibson91.github.io/) _Open Source Infrastructure Engineer @ 2i2c_ 13 | - [Esther Plomp](https://estherplomp.github.io/) _Data Steward @ TU Delft_ 14 | 15 | 16 | ### Collaborative document from the call 17 | [HackMD](https://hackmd.io/F83C14OqTKmfgoAc9W9BhQ?both) 18 | 19 | ### Recording 20 | [Launching, hosting and maintaining your training project](https://www.youtube.com/watch?v=AEqg9ygPk7w) 21 | -------------------------------------------------------------------------------- /2022/cc2-launching-hosting-maintaining-your-training/CC2 - Introduction and overview of the call.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/alan-turing-institute/ds-ai-educators-programme/df172e525d3e615170afa4011a2943df36fa64e0/2022/cc2-launching-hosting-maintaining-your-training/CC2 - Introduction and overview of the call.pdf -------------------------------------------------------------------------------- /2022/cc2-launching-hosting-maintaining-your-training/CC2 - Introduction and overview of the call.pptx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/alan-turing-institute/ds-ai-educators-programme/df172e525d3e615170afa4011a2943df36fa64e0/2022/cc2-launching-hosting-maintaining-your-training/CC2 - Introduction and overview of the call.pptx -------------------------------------------------------------------------------- /2022/cc2-launching-hosting-maintaining-your-training/Esther-Plomp-TUDelft/Slides.md: -------------------------------------------------------------------------------- 1 | Esther's Slides can be found below as ppt. and pdf. documents: 2 | 3 | [Launching, hosting and maintaining your training project - Esther Plomp.pptx](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/8805029/Launching.hosting.and.maintaining.your.training.project.-.Esther.Plomp.pptx) 4 | 5 | [Launching, hosting and maintaining your training project - Esther Plomp.pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/8805030/Launching.hosting.and.maintaining.your.training.project.-.Esther.Plomp.pdf) 6 | -------------------------------------------------------------------------------- /2022/cc2-launching-hosting-maintaining-your-training/Sarah-Gibson-Jupyter-Binder/Slides.md: -------------------------------------------------------------------------------- 1 | [Slides](https://docs.google.com/presentation/d/1Ar_qFkjdyEBpZwxt38zZjISfJZ7QsdsotbSWVRDexww/edit#slide=id.g1300411c638_0_295) 2 | -------------------------------------------------------------------------------- /2022/cc3-developing-training-for-live-delivery-vs-self-paced-learning/ABOUT.md: -------------------------------------------------------------------------------- 1 | # Developing training for live delivery vs. self-paced learning: Thursday 9 June 2022, 10 - 11:00am (GMT+1) 2 | 3 | ### This call will cover the following points: 4 | - To examine case studies of asynchronous learning programmes 5 | - To know some of the differences (and practical tips) for designing different types of learning 6 | - To examine the Hyflex model and how this may be applicable in your own setting 7 | - To reflect on pedagogical considerations for synchronous vs asynchronous vs hyrbid learning in relation to personal experiences 8 | 9 | ### Today's speakers 10 | - Sarah Nietopski, The Alan Turing Institute 11 | - Rodrigo Sanchez-Pizani, King's College London 12 | 13 | 14 | ### Collaborative document from the call 15 | [HackMD](https://hackmd.io/7_MGYRWoR6mmf3Q9uMwK6A?both) 16 | 17 | ### Recording 18 | [Developing training for live delivery vs. self-paced learning](https://www.youtube.com/watch?v=1rE78PfZW1w) 19 | -------------------------------------------------------------------------------- /2022/cc3-developing-training-for-live-delivery-vs-self-paced-learning/Rodrigo-Sanchez-Pizani-King's-College-London/Slides.md: -------------------------------------------------------------------------------- 1 | Rodrigo's slides on HyFlex can be found below as pptx. and pdf. files: 2 | 3 | [Designing training for live delivery vs. self-paced delivery - Rodrigo Sanchez-Pizani.pptx](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/8879019/Designing.training.for.live.delivery.vs.self-paced.delivery.-.Rodrigo.Sanchez-Pizani.pptx) 4 | 5 | 6 | [Designing training for live delivery vs. self-paced delivery - Rodrigo Sanchez-Pizani.pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/8879040/Designing.training.for.live.delivery.vs.self-paced.delivery.-.Rodrigo.Sanchez-Pizani.pdf) 7 | -------------------------------------------------------------------------------- /2022/cc3-developing-training-for-live-delivery-vs-self-paced-learning/Sarah-Nietopski-The-Alan-Turing-Institute/Slides.md: -------------------------------------------------------------------------------- 1 | Sarah's slides can be found, below, as pptx. and pdf. 2 | 3 | [Designing training for live delivery vs. self-paced learning - Sarah Nietopski.pptx](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/8879065/Designing.training.for.live.delivery.vs.self-paced.learning.-.Sarah.Nietopski.pptx) 4 | 5 | [Designing training for live delivery vs. self-paced learning - Sarah Nietopski.pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/8879084/Designing.training.for.live.delivery.vs.self-paced.learning.-.Sarah.Nietopski.pdf) 6 | -------------------------------------------------------------------------------- /2022/cc3-developing-training-for-live-delivery-vs-self-paced-learning/Zoom-chat: -------------------------------------------------------------------------------- 1 | 00:11:32 Nancy Ruzycki: Good Morning 2 | 00:11:57 Andrew Csizmadia: Morning all 3 | 00:12:03 Inigo Aldazabal: Hi there! 4 | 00:12:04 Ogerta Elezaj: Good Morning 5 | 00:12:12 Haya Elayan: Good Morning everyone 6 | 00:12:13 Luisa Cutillo: Hi all. 7 | 00:12:14 Rodrigo Sánchez: morning 8 | 00:12:15 Ryan Reavette: Morning all 9 | 00:12:17 Ruby Chang: good morning 10 | 00:12:18 Noorhan: Good morning everyone. 11 | 00:12:22 Matt Forshaw (he/him): Good morning everyone; i hope you're keeping well 🙂 12 | 00:12:35 Kwong-Cheong Wong: Good morning! 13 | 00:12:37 Martin Goodfellow: Morning everyone 14 | 00:12:50 Adnane Ez-zizi: Good morning 15 | 00:12:50 shamsuddeen: Morning from Nigeria ! 16 | 00:12:51 Riddhima Kedia: hello! 17 | 00:13:05 Eric Atwell: obvius answer: we taught lectures via Zoom instead of in lecture theaters 18 | 00:13:06 MARIA NAVAS LORO: Good morning! I started my teaching duties right after pandemics, but I would say it forced us to adapt all activities so they can be done online... in some cases it is difficult 19 | 00:13:13 Luisa Cutillo: I had to transition to online delivery of course, creating videos on top of my lecture as everyone I guess. The main challenge was to make it 'interactive' even if it was asynchronous. 20 | 00:13:30 Nancy Ruzycki: Had to adapt experiential learning to an online environment 21 | 00:13:46 Andrew Moles: Morning! My role became more flexible but also busier as with in-person and remote teaching there was just more to think about, like the pros and cons of each style. It certainly provides a new environment which suits shy students (online) 22 | 00:14:05 Anastasis Georgoulas: Had to rethink what the best ways of providing information were, and ensure contact opportunities with students 23 | 00:14:05 Eric Atwell: Zoom lectures are more interactive than in-LT teachiing, as students "chat" more readily 24 | 00:14:27 Inigo Aldazabal: Adapt carpentries practices to online teaching was very difficult 25 | 00:15:17 Matt Forshaw (he/him): HackMD link: https://hackmd.io/7_MGYRWoR6mmf3Q9uMwK6A 26 | 00:15:37 Martin Goodfellow: Stopped giving lectures. Instead broke up lectures into short videos for each concept (max 10 mins) and used Zoom sessions for Q and As and tutorials. 27 | 00:15:50 Eric Atwell: Actually giving lecures via Zoom was not much different from live lectures .. .diffierences were much less important than similarities, a bit like the difference between UK and US English: more or less the same overall, even tho we notice the differences 28 | 00:19:55 Eric Atwell: Do you know how many UK University partners of Turing also use Moodle? Leeds Uni uses Blackboard, the main commercial rival to Moodle 29 | 00:20:43 Adnane Ez-zizi: Are these Turing's online courses already available? 30 | 00:20:50 Andrew Moles: Most London based universities I've worked for/worked with use Moodle 31 | 00:21:03 Eric Atwell: How can I try this case study 1 course? Can I re-use it for teaching Leeds Uni AI students? 32 | 00:22:43 Eric Atwell: WHY is it better in smaller chinks? Surely if there is a long video, students can pause at any point? 33 | 00:23:43 Eric Atwell: What is “research engineering”?? 34 | 00:25:22 Ayesha Dunk (she/her): The research engineering group includes the research software engineers and research data scientists 35 | 00:25:37 Ayesha Dunk (she/her): @Eric I will direct some of these questions to Sarah! 36 | 00:26:10 Surangika Ranathunga Ranathunga: @sarah s it the flip class concept? 37 | 00:26:12 Anastasis Georgoulas: I also thought smaller chunks would be better, but when we recorded a class, some students asked for the whole recording so they can download it all at once. 38 | 00:26:16 Ogerta Elezaj: @Eric small videos allow the learners to start and finish each lecture in one sitting— instead of stopping in the middle and forgetting where they left off... 39 | 00:26:40 Ruby Chang: Are these courses aiming for people outside Turing without much data science and ai background? 40 | 00:27:15 Eric Atwell: A video also can also have a TRANSCRIPT, whcih students can use to recap meterial - this is missing in a live lecture 41 | 00:27:19 Ayesha Dunk (she/her): @Ruby - the courses vary and will always have information on the necessary prerequisites 42 | 00:27:57 Ayesha Dunk (she/her): @Ruby - the courses are for anyone to attend but the prerequisites vary! 43 | 00:28:01 MARIA NAVAS LORO: @Eric as far as I know, students right now lose interest really fast, their average attention time is of around 10 min... maybe it is one of the reasons why they do short videos? 44 | 00:29:04 Eric Atwell: @Maria, maybe Leeds Uni MSc and BSc students are different, they are used to paying attention for an hour, IF the lecturer is sufficiently inspiring and enthusiastic 45 | 00:31:01 Eric Atwell: I have heard that “young people cannot pay attention for more than 10 minutes” but I think this is just a social panic strategy by the news media 46 | 00:32:21 Adnane Ez-zizi: Are you collecting data from the learner's interactions with the platform? And if yes, for what purposes? 47 | 00:32:21 Eric Atwell: “A social panic is a state where a social or community group reacts negatively and in an extreme or irrational manner to unexpected or unforeseen changes in their expected social status quo.” https://en.wikipedia.org/wiki/Social_panic 48 | 00:32:34 Ruby Chang: @ Eric there are lots of distraction when learning at home; maybe we need to tell them to block time that they can concentrate. 49 | 00:34:05 Luisa Cutillo: In my experience a mix of asynchronous + sync. lecture a week balnces out very well 50 | 00:34:12 georgina: for students who have ADHD etc and struggle to concentrate, the chunking method is much more beneficial to them 51 | 00:34:24 Nancy Ruzycki: You have to think about the point of the video (the agency) if the purpose of the video is a short informational video as part of a learning progression that has a different purpose than a long recorded lecture 52 | 00:35:09 Eric Atwell: We are competing with TV shows of 30-45 minutes, eg training on coaching and teaching by “Ted Lasso" is 53 | 00:36:29 Eric Atwell: @Luisa, this year I did all teaching this way, and plan to continue for next year: “In my experience a mix of asynchronous + sync. lecture a week balnces out very well" 54 | 00:38:31 Sarah Nietopski: @Adnane - we will be collecting some data from users about how they interact. The main purpose is to get insight into things like which courses/modules are most used, where people drop out, and things like that. (things to help us improve and develop courses in the future) 55 | 00:38:42 Ayesha Dunk (she/her): https://www.youtube.com/watch?v=k3EMsf9kusA 56 | 00:39:22 Eric Atwell: How much does this cost? Maybe the cost of employing a lecturer? 57 | 00:39:49 Ayesha Dunk (she/her): https://doi.org/10.1016/B978-0-12-388435-0.50002-0 58 | 00:40:20 Ayesha Dunk (she/her): A good question @Eric - I will ask at the end! 59 | 00:40:54 Sarah Nietopski: @Surangika - most of our focus is on fully asynchronous courses, but we've been considering the flipped model for future live courses. We think it could be really useful if learners do some of the lectures etc. on their own and then use the sessions with live instructors to do Q&A/discussions/etc. 60 | 00:41:22 Eric Atwell: I'm a sci fi fan so might enjoy trying “alien technology”! 61 | 00:41:45 georgina: Related to Eric's question, is this only used at universities? It seems expensive and looks like it might be out of a secondary school's (or even primary school’s) budget 62 | 00:43:38 Adnane Ez-zizi: If I understand this correctly, are you providing (all) students with hardware like mics and cameras if they are attending the lectures from online? 63 | 00:45:24 Eric Atwell: Sorry I dont understand what is being correlated … 64 | 00:46:53 Eric Atwell: All these problems with acoustics etc - does this imply we should stick to video recording of Zoom lectures? 65 | 00:47:08 Maarya Sharif: what does ASR mean? 66 | 00:47:26 Eric Atwell: ASR automatic speech recognition - to get auto transcript 67 | 00:47:37 Maarya Sharif: ah, thanks! 68 | 00:47:45 Eric Atwell: (I tihkn) 69 | 00:47:55 Eric Atwell: (I think) 70 | 00:49:01 Surangika Ranathunga Ranathunga: @Eric is correct 71 | 00:49:22 Eric Atwell: “bear in mind workload” - of students, or of teachers? Probalby BOTH have more workload if you use all this tech. 72 | 00:49:34 Surangika Ranathunga Ranathunga: +1 :) 73 | 00:49:49 Andy MacLachlan: Good point Eric, I was feeling a bit nervous hearing about all this setup 74 | 00:49:50 Surangika Ranathunga Ranathunga: But some are just one-off work 75 | 00:49:53 Adnane Ez-zizi: I can relate with the exhaustion that comes with the use of multiple screen and trying to cater for both students joining online and in-person 76 | 00:50:50 Eric Atwell: “monitored by TA” - some of us don't have a spare TA to help with teaching … 77 | 00:51:04 Ruby Chang: I am struggling to read the chats and pay attention to the presentation at the same time :D 78 | 00:51:37 Luisa Cutillo: need a double screen setting :-) 79 | 00:51:50 Eric Atwell: @Ruby you need a TA to monitor the chat! 80 | 00:52:32 Anastasis Georgoulas: I get the sense that King's College was very proactive and openminded about getting equipment! Which is good ot see :) 81 | 00:52:33 Ruby Chang: @Eric cat is sleeping on the desk... 82 | 00:52:53 Luisa Cutillo: In the school of math we have cameras following the speaker. I Find that it helps a lot 83 | 00:53:10 georgina: Thanks Rodrigo that was really interesting 🙂 84 | 00:54:34 Eric Atwell: At Leeds Uni we have a room like this ... but we have thousands of taught modules, and only about 3 can use the system 85 | 00:55:05 Maarya Sharif: I've heard posititve feedback on the OWL camera 86 | 00:55:06 Eric Atwell: The other 999+ teachers have to use Zoom for lecures 87 | 00:57:57 Eric Atwell: How many taught modules at Kings are taught via Hyflex? 88 | 00:58:08 Nancy Ruzycki: We have had trouble with the owl and the mics in the room picking up voices 89 | 00:59:45 Matt Forshaw (he/him): HackMD link for breakout: https://hackmd.io/7_MGYRWoR6mmf3Q9uMwK6A 90 | 01:08:33 Maja Buljan: didn't get a chance to say thanks to my breakout room, so thanks! 91 | 01:08:48 Maarya Sharif: what is the GitHub link? 92 | 01:08:54 Nancy Ruzycki: Thanks to the speakers 93 | 01:09:01 Matt Forshaw (he/him): Thank you so much everyone for joining; wishing you a very nice rest of your day! 94 | 01:09:10 Surangika Ranathunga Ranathunga: thanks 95 | 01:09:12 Ruby Chang: thank you. 96 | 01:09:19 Martin Goodfellow: Thanks all 97 | 01:09:19 Anastasis Georgoulas: Thanks everyone! 98 | 01:09:24 Maja Buljan: thanks everyone, see you next week! 99 | 01:09:25 Eric Atwell: thank you for food forvthoguht 100 | 01:09:25 Noorhan: Thank you very much 101 | 01:09:27 Haya Elayan: Thanks all 102 | -------------------------------------------------------------------------------- /2022/cc4-ethics-in-the-context-of-training/ABOUT.md: -------------------------------------------------------------------------------- 1 | # Ethics in the context of training: Thursday 16 June 2022, 10 - 11:00am (GMT+1) 2 | 3 | ### This call will cover the following points: 4 | - Programme case studies and lessons learned 5 | - Recommendations for AI educators 6 | 7 | ### Today's speakers 8 | - Dr Chris Burr: The Alan Turing Institute 9 | - Dr David Tarrant: The Open Data Institute 10 | 11 | ### Collaborative document from the call 12 | [HackMD](https://hackmd.io/IDtuYddoTIqo0Wm6kacJog) 13 | 14 | ### Recording 15 | [Ethics in the context of training](https://youtu.be/k2eSE4RxXlk) 16 | -------------------------------------------------------------------------------- /2022/cc4-ethics-in-the-context-of-training/Zoom-chat: -------------------------------------------------------------------------------- 1 | 00:15:46 Mishka Nemes (she/her) | Alan Turing Institute: Collaborative HackMD document - we will populate this with other links after the call https://hackmd.io/IDtuYddoTIqo0Wm6kacJog?view 2 | 00:20:55 David Tarrant: Auto AI animations :) 3 | 00:25:50 Eric Atwell: Did he say 30 participants? I assumed these online learning resources were aimed at MOOC-style delivery to hundreds or thousands of students 4 | 00:26:44 Luisa Cutillo: @eric I think this involves interaction 5 | 00:26:55 Mishka Nemes (she/her) | Alan Turing Institute: The live delivery has a limited number of participants, the self-paced courses are open to all and therefore unlimited number of participants 6 | 00:27:48 Luisa Cutillo: I guessed so, a bit like this course :-) 7 | 00:28:34 Eric Atwell: How are students assessed, to get a Grade at the end? For self-paced students and for live delivery - is assesment different for these 2 user groups? 8 | 00:29:11 Luisa Cutillo: Is there an assessment? 9 | 00:30:56 Clau Fischer (she/her): Link to the blogpost: https://turing-commons.netlify.app/blog/2022/10-06-2022-public-engagement/ 10 | 00:31:17 Christopher Burr (he/him) | Alan Turing Institute: Our first two courses were actually delivered online over the course of 5 days with the participants. We're now in the process of building this into a self-directed course (e.g. MOOC style). 11 | 00:32:00 Christopher Burr (he/him) | Alan Turing Institute: There was no formal assessment for these courses. However, there were capstone projects at the end of the week that required the participants to draw upon the lessons learned over the previous days. 12 | 00:33:16 jakemarshall: Very interested in looking into these since are we reviewing our ethics and governance course as we speak! These could be fabulous resources to point our students towards (I'm in capability at the civil service 🙂) 13 | 00:33:32 Christopher Burr (he/him) | Alan Turing Institute: Our goal was to promote reflection and deliberation, and to see where assessment could support that. We will try to integrate some assessment into the MOOC style version, but this will always be secondary for us, as we are not dealing with questions that have "right" answers. Instead, we will be trying to assess how well participants can apply the frameworks or models in their own projects. 14 | 00:34:10 Mishka Nemes (she/her) | Alan Turing Institute: Please keep the questions coming - we will try to answer them in the panel discussion 😀 15 | 00:34:34 Eric Atwell: I wish we did not have to set and mark formal assessments in our AI teaching! https://www.linkedin.com/feed/update/urn:li:activity:6942014516708696065/ 16 | 00:35:29 Valentina Andries: Are these courses available? 17 | 00:35:59 jakemarshall: Are these ODI and turing courses free? Or are they part of a subscription or? 18 | 00:36:26 Christopher Burr (he/him) | Alan Turing Institute: I agree, Eric. Developing effective assessments in the space of data/AI ethics is very challenging. We're going to work with a number of educational institutions over the coming months to think about how to do this responsibly. 19 | 00:36:41 Doschmund: I attend and recommend the Data Ethics Professional Course - Call me biased 🙂 20 | 00:37:19 Ogerta Elezaj: Can you share the links of the courses? 21 | 00:37:33 Eric Atwell: I wish we had a corpus or data-set of reusable AI assessments, preferrably with auto-grading so AI can help reduce teacher workload https://www.linkedin.com/posts/ericatwell_negotiated-offers-agreed-by-ucu-members-activity-6942014516708696065-NO3e?utm_source=linkedin_share&utm_medium=member_desktop_web 22 | 00:37:44 Christopher Burr (he/him) | Alan Turing Institute: Turing Commons link: https://turing-commons.netlify.app 23 | 00:37:51 Christopher Burr (he/him) | Alan Turing Institute: I will let David share the ODI links later. 24 | 00:38:47 Doschmund: https://theodi.org/events/courses/ 25 | 00:39:53 Luisa Cutillo: Can we have the links to all these resources in a shared document please? 26 | 00:40:11 Eric Atwell: Do you have a corpus or text-data-set of ethics+AI case studies, so we can apply text analytics to analyse and learn from the case studies? eg see http://catalogue.elra.info/en-us/ 27 | 00:40:51 Christopher Burr (he/him) | Alan Turing Institute: Interesting proposal, Eric. We're building a repository of case studies at the moment. WIll certainly think about how to make the information accessible for data mining and analysis/ 28 | 00:41:39 Christopher Burr (he/him) | Alan Turing Institute: Our existing case studies are structured, but have been shared as PDFs so far—not the best for data mining!! 29 | 00:42:13 Christopher Burr (he/him) | Alan Turing Institute: Our goal is to develop a more structured repository, and maybe enable an API for people to access. 30 | 00:42:37 Christopher Burr (he/him) | Alan Turing Institute: Will certainly think about how this could be used to support ongoing research. 31 | 00:43:16 jakemarshall: It would also be good to group them by industry too, that way people won't need to scan through case studies to find one on ‘retail' for example 😛 32 | 00:43:24 Mishka Nemes (she/her) | Alan Turing Institute: @Luisa I am adding here to the bottom of the hackMD doc https://hackmd.io/IDtuYddoTIqo0Wm6kacJog?both 33 | 00:43:33 Mishka Nemes (she/her) | Alan Turing Institute: Adding the links* 34 | 00:43:40 Luisa Cutillo: Grazie! 35 | 00:43:42 jakemarshall: Perhaps that's too difficult a task if they cross multiple industries, but just throwing thoughts out there 36 | 00:43:43 Eric Atwell: The Association for Computational Linguistics collects published academic research and teaching texts, for use in AI and text analytics research, eg the ACL Anthology https://aclanthology.org/ https://www.sketchengine.eu/acl-anthology-reference-corpus-arc/ 37 | 00:43:55 Christopher Burr (he/him) | Alan Turing Institute: Definitely, Jake. They will certyainly be domain-specific. We're working with a couple of UK CDTs at the moment to ensure this is effetcive. 38 | 00:44:33 Christopher Burr (he/him) | Alan Turing Institute: I think Mishka's team will advertise some upcoming workshops if anyone is here from a current CDT and would like to contribute. 39 | 00:45:49 Mishka Nemes (she/her) | Alan Turing Institute: Yes we will definitely advertise open upcoming opportunities with everyone here - keep an eye on Slack! 40 | 00:46:16 Christopher Burr (he/him) | Alan Turing Institute: And just to reiterate, these were 5-day long courses!!! 41 | 00:47:51 Christopher Burr (he/him) | Alan Turing Institute: I will share some links to our existing case studies once I have stopped screen sharing. 42 | 00:49:11 Eric Atwell: In collating the repository of case studies, please think about making them available in a range of formats - PDFs are ok for humans to read, but for text analytics, SketchEngine format is better 43 | 00:49:11 Anastasis Georgoulas: What kind of structured activities did you have, besides the case studies? 44 | 00:49:59 jakemarshall: Another thing to point out is that PDF is not accessible for screen readers for example, htmls that are correctly formatted tend to be the best solution for that, so to be as inclusive as possible, definitely include more than one version 😄 45 | 00:50:20 Clau Fischer (she/her): So in the Public engagement course, all of the activities where structured around a hypothetical public engagement project. 46 | 00:50:44 Christopher Burr (he/him) | Alan Turing Institute: Yep. It's a limitation we are working to improve. Just trying to develop the necessary infrastructure to support altenratives. 47 | 00:51:19 Eric Atwell: You have told us about your infrastructure; I was expecitng to learn about ethics issues in AI and how to teach about hem… 48 | 00:51:23 Christopher Burr (he/him) | Alan Turing Institute: Our website does follow semantic HTML best practices though, so should be screenm reader accessible. 49 | 00:51:48 Clau Fischer (she/her): We asked the groups to define a hypothetical project where public engagement was necessary, and then used this case throughout the course, asking them to apply the course materials to it 50 | 00:52:06 Anastasis Georgoulas: I see, thanks Clau! 51 | 00:52:07 Christopher Burr (he/him) | Alan Turing Institute: Happy to expand on tihs in the panel, Eric. 52 | 00:52:08 jakemarshall: Good stuff 😛! Wanted to point it out as the accessibility audit carried out on our materials pointed out problems with PDFs being separate links and requiring extensions etc 😛 53 | 00:53:09 Eric Atwell: By coincidence, SketchEngine format is good. for text analytics and also good for accessibility and screenreaders 54 | 00:53:21 Anastasis Georgoulas: +1 for Eric's question: if, as a teacher, I want to learn more about ethics, what would you suggest as a starting point? What are the most important considerations in your view? Or just go to one of the courses? :) 55 | 00:54:14 Christopher Burr (he/him) | Alan Turing Institute: Thanks, Anastasia. i will start the panel by addressing this. 56 | 00:55:04 jakemarshall: Iris lol 57 | 00:55:11 jakemarshall: I'm glad we ignored it on the graduate programme 58 | 00:55:24 jakemarshall: Much rather gapminder as at least you can pull out interesting population statistics 59 | 00:55:27 Eric Atwell: “bias in data” - we teach algorithms and methods for machine learning of bias in training data - is this part of “ethics in AI" courses? 60 | 00:57:15 Clau Fischer (she/her): https://turing-commons.netlify.app/rri/chapter3/ 61 | 00:57:21 Clau Fischer (she/her): https://turing-commons.netlify.app/rri/chapter4/#chapter-outline? 62 | 00:57:41 Clau Fischer (she/her): Sorry, Im having trouble going into the project lifecycle link 63 | 00:57:49 Clau Fischer (she/her): https://turing-commons.netlify.app/rri/chapter2/project_lifecycle/ 64 | 00:58:01 Clau Fischer (she/her): It is this last link 65 | 00:58:09 Clau Fischer (she/her): for the project lifecycle 66 | 00:58:42 Malvika Sharan (she/her): Anastasia and Eric, for overview on some of the core principles of ethics in data science, you can start here: https://the-turing-way.netlify.app/ethical-research/ethical-research.html. Turing commons is a natural progression from their for deep dive. 67 | 00:59:36 David Tarrant: https://theodi.org/event_series/operationalising-data-ethics-webinar/ 68 | 01:01:39 Anastasis Georgoulas: Thank you for the answers, everyone! 69 | 01:01:54 Eric Atwell: We have a 15-credit “Ethics in AI" module as part of our online MSc in AI at Leeds Uni 70 | 01:02:18 David Tarrant: Leeds is one of the organisations that we have had close collaborations with thankfully :) 71 | 01:02:32 jakemarshall: Very interesting David! I wonder if some of us in the Data Science Campus faculty would be interested in going on that programme! Watch this space lol, will discuss with my manager later 72 | 01:02:38 Luisa Cutillo: How would the collaboration happen? 73 | 01:02:41 jakemarshall: We can always afford to get better with ethics, particularly as the educators 74 | 01:02:43 Luisa Cutillo: Is there any call? 75 | 01:03:06 Doschmund: In the Turings common - the link to AI Ethics and Governance - doesnt open anything 76 | 01:03:11 Doschmund: Is the course still in development? 77 | 01:03:33 Christopher Burr (he/him) | Alan Turing Institute: Yes. It should go to a page that states this. I will take a look at the link after the call. 78 | 01:03:45 Mishka Nemes (she/her) | Alan Turing Institute: @Doschmund that course is still under development 79 | 01:03:59 Doschmund: thats great, thank you 80 | 01:04:27 Christopher Burr (he/him) | Alan Turing Institute: The code for the platform is openly available on GitHUB for anyone who is interested: https://github.com/alan-turing-institute/turing-commons 81 | 01:04:28 jakemarshall: Apologies everyone I have to go as I have another meeting right now 😄 Thanks so much for this session! It was incredibly insightful and super useful from my persepctive! 82 | 01:04:44 Mishka Nemes (she/her) | Alan Turing Institute: thank you Jake! 83 | 01:04:50 Eric Atwell: Do you have a 1-page syllabys summary of “ethics in AI" MSc-level course, like ours at Leeds Uni? https://webprod3.leeds.ac.uk/catalogue/dynmodules.asp?Y=202223&M=OCOM-5202M 84 | 01:05:14 Ruby Chang: thank you for the session and will check out the RRI links! 85 | 01:05:48 Nancy Ruzycki: thank you for the links 86 | 01:05:50 Eric Atwell: I have to go buy a birthday cake ... bye 87 | 01:05:54 Andrew Moles: Really interesting stuff! Thank you 88 | 01:06:10 David Tarrant: Not one page but the syllabus: https://docs.google.com/document/d/1-MaKcj6rmBMbrmvcFnbq3HPY5CHkm_yf3e1kb7gItz0/edit?usp=sharing 89 | 01:06:13 Malvika Sharan (she/her): I will also store chat for ref 90 | 01:06:14 Maja Buljan: thank you all! 91 | -------------------------------------------------------------------------------- /2022/cc4-ethics-in-the-context-of-training/ai-educators.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/alan-turing-institute/ds-ai-educators-programme/df172e525d3e615170afa4011a2943df36fa64e0/2022/cc4-ethics-in-the-context-of-training/ai-educators.pdf -------------------------------------------------------------------------------- /2022/cc5-widening-participation/ABOUT.md: -------------------------------------------------------------------------------- 1 | # Panel: Widening participation in the context of training, Thursday 23 June 2022, 10 - 11:00am (GMT+1) 2 | 3 | ### This call is a panel discussion, which addresses the following questions: 4 | - What efforts have you made in your role to encourage widening participation? 5 | - What challenges or barriers have you faced? 6 | - What key learnings have you taken from these challenges? 7 | - What is an inspiring effort to widen participation either at scale or for poorly-represented groups elsewhere? 8 | - How did you use these learnings to start to overcome/overcome these challenges? 9 | - Top tips for widening participation in the context of training: where to start? 10 | - What 'easy wins' can you recommend? 11 | 12 | ### Today's speakers 13 | - Amy Gallimore, The Alan Turing Institute 14 | - Nick Halper, Neuromatch 15 | - Kate Hazeldene, Office for Students 16 | - Malvika Sharan, Open Life Science 17 | 18 | 19 | ### Collaborative document from the call 20 | [HackMD](https://hackmd.io/fQceWS7TSf6B-yQzrYatAw?both) 21 | 22 | ### Recording 23 | [Widening participation in the context of training](https://youtu.be/k59kx2yaBN4) 24 | -------------------------------------------------------------------------------- /2022/cc5-widening-participation/Zoom-chat: -------------------------------------------------------------------------------- 1 | 00:15:15 Mishka Nemes (she/her) | Alan Turing Institute: Jealous on the sunny weather! 2 | 00:15:21 Eric Atwell: https://www.turing.ac.uk/events/turings-cabaret-dangerous-ideas-leeds 3 | 00:16:28 Ayesha Dunk (she/her): https://hackmd.io/fQceWS7TSf6B-yQzrYatAw?both 4 | 00:17:02 Ayesha Dunk (she/her): https://app.sli.do/event/7Uwv2zV7qAsyuEgmykBsAv/live/polls 5 | 00:25:12 Eric Atwell: Why are there no University AI lecturers in the panel? I thoguht we would learn about EDI in university teaching 6 | 00:25:40 Malvika Sharan (she/her): Matt Forshaw is the rep throughout 🙂 7 | 00:26:38 Malvika Sharan (she/her): But we are discussing EDI of diverse lens and what you can take back in your work 8 | 00:27:07 Eric Atwell: I think Office for Students only help UK students - but most of our AI students are International 9 | 00:28:11 Malvika Sharan (she/her): Eric, Nick and I are bring the international aspect 10 | 00:29:31 Malvika Sharan (she/her): bringing* 11 | 00:30:05 Andy MacLachlan: hi Kate, are theses the scholarships you were referring to? How do you apply for a programme to be on the list - https://www.britishcouncil.org/study-work-abroad/in-uk/scholarship-women-stem 12 | 00:30:26 Doschmund: I couldnt catch the name of Nick's Organisation. Could you please add to the chat? 13 | 00:30:31 Matt Forshaw (he/him): Hi Andy; here is the link: https://www.officeforstudents.org.uk/advice-and-guidance/skills-and-employment/postgraduate-conversion-courses-in-data-science-and-artificial-intelligence/ 14 | 00:30:37 Mishka Nemes (she/her) | Alan Turing Institute: Neuromatch 15 | 00:30:39 Ayesha Dunk (she/her): Nick is from Neuromatch 16 | 00:30:47 Eric Atwell: @Kate I meant your studentships are only for UK students, is that right? My AI students are mainly BAME female students from overseas 17 | 00:31:25 Kate Hazeldene, OfS: More inforrmation about the programme and the schoalarships are available on our webpages here- https://www.officeforstudents.org.uk/advice-and-guidance/skills-and-employment/postgraduate-conversion-courses-in-data-science-and-artificial-intelligence/ 18 | 00:31:34 RYAN CROSBY: I tried typing this in sli do but the question seems to long. 19 | 00:31:46 RYAN CROSBY: It may aslo be a question for the end of the session as Nick may cover it 20 | 00:32:09 RYAN CROSBY: I think this will be a question for Nick – but if anyone else can input that would be great (and sorry it’s a ramble). Do you have any general advice on making assessment more accessible? Do you assess your courses? If so, how do you make those assessments accessible? For example, traditional exams to me aren’t accessible. Even when concessions are made, they don’t seem to be truly accessible. Do you have alternative assessments – I would assume you aren’t constrained by exams / coursework as HE sometimes is? 21 | 22 | The rest of this message is ignorable, just an example – 23 | With exams if we consider Autism – exams could be difficult due to hypo/hyper sensory sensitivity, and I’m unsure how this can be changed to make this aspect of exams accessible. I’m still very new to researching making assessment accessible so sorry if this is a question that is already resolved? 24 | 00:32:57 Kate Hazeldene, OfS: The eligibility criteria and application process are set by the individual providers who are delivering the scholarships and some may allow international students to apply but the priority is for UK students 25 | 00:33:58 Ayesha Dunk (she/her): Ryan, I have added your question to the Slido but made sure it fitted the word count 🙂 26 | 00:34:03 Eric Atwell: @Ryan, do you think MCQs are accessible? eg in Blackboard, a Test cna have 20 questions each with 4 possible answers, studnt must select 1 (or more) correct answer. Is this accessible for autisitc and other students? 27 | 00:34:21 RYAN CROSBY: Thank you Ayesha 0 sorry for the ramble 28 | 00:34:37 Matt Forshaw (he/him): Hi Eric, building on Kate's comments, I can certainly say from a Newcastle project perspective that we've seen very strong uptake in international leaners who are benefitting from the new programmes (which we wouldn't have been able to bring to market without OfS project). At Newcastle (and many providers do similar things) we offer 'pre-sessional' training to learners coming from other backgrounds, and mentorship opportunities with data leaders from industry. We are able to offer those benefits out to learners irrespective of whether they are home or international. 29 | 00:34:41 Eric Atwell: MCQ also has the great advantage of scaling up to big classes, 200+ students 30 | 00:35:48 staalcu: @Matt how do you manage such workload? 31 | 00:37:33 Ayesha Dunk (she/her): Slido can also be anonymous if you don't want to share your name! 32 | 00:38:46 staalcu: I think the default is anonymous 33 | 00:38:51 RYAN CROSBY: @Eric I think it depends on how the questions are structured, and if exams are necessary - I’ve found exams rarely have any benefit to the student and is a better assessor of students memory recall, strategic learning and ability to work under pressure. I am a big believer that assessment should be for learning not 'of learning’. However I am aware that exams are very important to HE institutes and potential employers 34 | 00:39:19 Eric Atwell: Malvika mentioned she put a link. - where? In slido? in hackmd? in zoom chat? (I only have a laptop screen and find it hard to tach several interfaces at once) 35 | 00:39:25 Malvika Sharan (she/her): HackMD 36 | 00:39:36 Malvika Sharan (she/her): Last section has links from all of us. 37 | 00:39:54 Malvika Sharan (she/her): Do ask for any additional links that could be useful. 38 | 00:40:10 Mishka Nemes (she/her) | Alan Turing Institute: https://hackmd.io/fQceWS7TSf6B-yQzrYatAw 39 | 00:40:12 Doschmund: @Malvika - how do you elicit participation from the groups you mentioned? What appraoches do you take? 40 | 00:40:41 staalcu: I asked a similar question in the slido 41 | 00:41:19 Matt Forshaw (he/him): Hi @Staalcu, a very good question. Doing this well does have a not insignificant workload impact. We were lucky with the OfS funding which supported that staff time in the first year of the scheme, while we demonstrated the benefits of the activity. We've now been able to build this into our Business as Usual. We've found ways to ensure our pre-sessional training is complementary with the development of blended/online training which we use in other contexts. 42 | 00:43:07 staalcu: @Matt, this sounds ideal! Do you have a good attendance of students and do these classes come with any form of credit or assessment? 43 | 00:43:59 Matt Forshaw (he/him): @staalcu, around 30% of our total Data Science students participate (either to brush up on their skills, or to learn for the first time). We do formative assessment on learners' practice exercise, but it isn't formally credit-bearing. 44 | 00:44:23 Matt Forshaw (he/him): It also runs remotely because many of our learners are unable to obtain visas to come to Newcastle before the start of term for pre-sessionals. 45 | 00:44:38 Malvika Sharan (she/her): Doschmund, this is one of our first reports that highlights how inclusiveness is centered in Open Life Science: https://openlifesci.org/posts/2020/10/01/annual-report-part-1/ 46 | 00:46:07 staalcu: @Matt, thanks. Side note: staalcu is Luisa Cutillo by the way :-) It seems like I did not set up my name after all 47 | 00:46:42 Malvika Sharan (she/her): We have documented some practical tips for online calls designed for inclusiveness: Yehudi, Y., Stack Whitney, K., & Sharan, M. (2020, November 24). Enhancing the inclusivity and accessibility of your online calls. https://doi.org/10.31219/osf.io/k3bfn 48 | 00:48:31 Doschmund: @Nick, are there any specific consideration for Summer schools in terms of wider participations 49 | 00:49:58 Nick Halper: I think one thing that people forget, and this is a current failure point of Neuromatch, is that summer break is not at the same time everywhere in the world. 50 | 00:50:28 Nick Halper: You are inherently exclusionary by being a 'summer school' that only operates on summer break in Northern hemisphere. 51 | 00:50:47 Nancy Ruzycki: I think it is important to build alliances also with lower school teachers who have access to local diverse students. How are pathways made available and accessible to local students? Many times we are bring in international students and not looking to build pathways to local students. 52 | 00:51:10 Nick Halper: Similarly, summer schools are typically full time for several weeks. This is inherently exclusionary to people that can't take time off work or school to attend. 53 | 00:53:41 Doschmund: @Malvika - very inspiring - how do you ensure that those students achieved the learning objectives? 54 | 00:53:43 Nancy Ruzycki: That is an important point, that achieving the certificate is not always the goal for some students 55 | 00:55:14 Malvika Sharan (she/her): 1:1 mentoring allows us to check in with mentors (we conduct mid-cohort survey) and schedule a graduation as a final presentation to allow students to reflect on their learning and how that has been for them. 56 | 00:57:53 RYAN CROSBY: THe longer message was just a ramble from me :) 57 | 00:59:15 Nancy Ruzycki: Do you have an office of disability in the UK universities that has the policies for testing and assessment of students with different needs? In the US, they handle the assessment process for students for extra time, space and accommodation for university class assessments. 58 | 01:01:41 RYAN CROSBY: That sounds very interesting Malvika. My PhD was on Ipsative assessment which reminds me of that. It focused more on the students learning gain rather than the final summative assessment. One of the conclusions I came to was that it would be very difficult to do that in current HE, but I try to focus on that in practicals / formative work. 59 | 01:01:43 Malvika Sharan (she/her): Ryan your point is absolutely valid: “However I am aware that exams are very important to HE institutes and potential employers”. 60 | 01:02:05 Eric Atwell: If I have a class of 200 students, how can I talk to talk and listen to individual students?? 61 | 01:02:11 Malvika Sharan (she/her): I suppose that final exam's success depends on the formative development during the teaching. 62 | 01:03:10 Malvika Sharan (she/her): Eric: Written ways to 'listen' is how you can assess everyone's engagement and understanding. Group activities are very useful to manage larger classroom. 63 | 01:03:34 Eric Atwell: @Kate, do you mean “welfare officers” are needed as separate from “lecturers”? Should Uni hire more welfare officers and fewer lecturers? 64 | 01:03:42 RYAN CROSBY: @eric - I think thats a discussion around class sizes vs teaching staff. It's alot eaiser to do in modules with 15-30 students. I've taught both types of classes. I found student reflections / peer talks / talking to demonstrators help in the larger classes 65 | 01:03:48 Matt Forshaw (he/him): Thank you so much everyone for joining, and to all of the panelists. I've learned a lot, and it's been great seeing such a lively discussion in the chat. I'm afraid I must dash to my next call, but wish you all the very best for the rest of your weeks. :) 66 | 01:03:58 Nick Halper: If you haven't looked at 'Ungrading' in terms of assessment. It is a growing movement that accomodates many different backgrounds. 67 | 01:04:10 staalcu: I think this is part of the support in place for students around the lectures. We could direct them to the right reference people so that the mechanisms we have in place can start 68 | 01:04:23 Ayesha Dunk (she/her): @Nick - do you have any useful links on this? Sounds really interesting 69 | 01:04:25 Malvika Sharan (she/her): Very interesting Nick, I did not know about it. 70 | 01:04:50 Malvika Sharan (she/her): https://reflect.ucl.ac.uk/mcarena/2021/05/26/ungrading/ 71 | 01:05:03 staalcu: will; this chat be saved? 72 | 01:05:18 Nick Halper: Ungrading: https://docs.google.com/document/d/11O8xqsc_e1Txm-NC_1DAEvLdcFrH3dvzqZZXVORVDmQ/edit 73 | 01:05:22 Nancy Ruzycki: Yes I agree, that the DSO is limited in what they provide. It is a law in the US, but not sure elsewhere 74 | 01:05:24 Ayesha Dunk (she/her): Yes it will 🙂 75 | 01:05:38 staalcu: thanks! 76 | 01:06:37 Nancy Ruzycki: Thanks @nick for the link 77 | 01:07:59 Malvika Sharan (she/her): Thanks Ayesha. 78 | 01:08:05 Eric Atwell: https://en.wikipedia.org/wiki/Ungrading BUT ... University educators MUST deliver a grade for every student in a module 79 | 01:08:09 Malvika Sharan (she/her): Sorry to put you on spot. <3 80 | 01:08:35 Ayesha Dunk (she/her): ❤️ no thank you for including me! 81 | 01:08:50 Kate Hazeldene, OfS: @Eric- I think that academic lecturers and student support staff need to be working together to support students from widening participation backgrounds. At the OfS we encourage a whole provider approach to supporting access and participation so it is not a case as more or less of one or the other but how all services collanorate and work together to achieve widening and pariticpation aims 82 | 01:08:55 Nick Halper: You still get/give a grade, but the formation of that grade is different and customized to the students' participation. 83 | 01:08:56 Eric Atwell: A lot of dscussion - cna you please summarise the main leasons I can take away for today? eg a list of URLs posted to chat! 84 | 01:09:26 Mishka Nemes (she/her) | Alan Turing Institute: Yes Eric we will do that! 85 | 01:09:38 Ayesha Dunk (she/her): @Eric, I will update the HackMD with everything from today and share this on the GitHub repo 86 | 01:09:44 Amy Gallimore (she/her) The Alan Turing Institute: If you want to find out more about EDI at Turing check out https://www.turing.ac.uk/about-us/equality-diversity-and-inclusion 87 | 01:10:00 Amy Gallimore (she/her) The Alan Turing Institute: Or if you're on Turing Slack #edi-equality-diversity-inclusion 88 | 01:10:10 Amy Gallimore (she/her) The Alan Turing Institute: You can also contact me any my colleague Khanisa at edi@turing.ac.uk 89 | 01:10:15 Amy Gallimore (she/her) The Alan Turing Institute: *and 90 | 01:10:17 Eric Atwell: sorry I dont understand what is “github repo” 91 | 01:10:54 Ayesha Dunk (she/her): @Eric - I'm wary of time so I will send you an email to discuss this 🙂 92 | 01:11:28 Eric Atwell: I dont want to reinvent the wheel BUT how do I choose the best wheel for me? There is a LOT of info out there, I need an AI to advise what to choose 93 | 01:12:47 Malvika Sharan (she/her): Thank you all! 94 | 01:12:47 staalcu: Thanks a lot!!! 95 | 01:12:48 RYAN CROSBY: Thank you for a very insightful discussion 96 | 01:12:50 Ayesha Dunk (she/her): Thank you so much everyone - any unanswered questions will be on Slack 🙂 97 | 01:12:54 Nick Halper: Thank you all! 98 | 01:12:56 Noorhan: Thank you very much 99 | 01:12:57 Kwong-Cheong Wong: Thank you 100 | 01:12:58 Funmi Obembe: Thank you 101 | 01:12:59 Martin Goodfellow: Thanks all, very interesting discussion 102 | 01:13:00 MARIA NAVAS LORO: thank you! 103 | 01:13:01 Nancy Ruzycki: thanks 104 | 01:13:01 Eric Atwell: Dont forget https://www.turing.ac.uk/events/turings-cabaret-dangerous-ideas-leeds 105 | 01:13:02 Doschmund: Thank you all 106 | 01:13:02 Ogerta Elezaj: Thank you all! 107 | -------------------------------------------------------------------------------- /2022/cc6-challenges-with-teaching-DS-and-AI/ABOUT.md: -------------------------------------------------------------------------------- 1 | # Challenges with teaching Data Science and AI (panel session): Thursday 30 June 2022, 10 - 11:00am (GMT+1) 2 | 3 | ### This call will cover the following points: 4 | Introductions: 5 | 6 | - Please share a bit about yourself, and your involvement in training in industry and academia 7 | 8 | General (primer) questions: 9 | 10 | - Could you share some of your experience of developing training and researcher development opportunities at the crossroad between academia and industry? 11 | - What are some lessons you could share with us today about what makes an effective & sustainable collaboration between academia and industy? 12 | - From your current work, what do you see is missing to enable development of educational resources that are useful and relevant for both theoretical and applied researchers? 13 | - Beyond technical skills, what are some of the industry relevant skills needed to success in the DS & AI workforce? 14 | 15 | Wrap-up questions: 16 | 17 | - Could you share with us top tips / resources / repositories etc to guide DS & AI educators in learning more about this topic beyond this call? 18 | 19 | ### Today's speakers 20 | - Matt Forshaw (Chair) 21 | - Graham Cole, Lecturer in Enterprise, Newcastle University 22 | - Darren Seymour-Russell, Accenture - Growth and Strategy Lead for Responsible AI 23 | - Richard Plant, The Alan Turing Institute, DSG 24 | 25 | ### Collaborative document from the call 26 | [HackMD](https://hackmd.io/D3wjOJAXTDWq8jSM8d8seQ) 27 | 28 | ### Recording 29 | -------------------------------------------------------------------------------- /2022/cc6-challenges-with-teaching-DS-and-AI/Zoom-chat: -------------------------------------------------------------------------------- 1 | 2 | 00:14:14 Ogerta Elezaj: Good morning everyone 3 | 00:14:14 Kwong Cheong WONG: Good morning 4 | 00:14:24 Luisa Cutillo: I was just worried I had some technical problems :-) 5 | 00:14:53 Doschmund: Same here 🙂 I was about to send out an email. 6 | 00:15:35 Martin Goodfellow: Morning everyone 7 | 00:15:55 Ayesha Dunk (she/her): https://hackmd.io/ohIMf55ZS_eeThplfd-ERg?both 8 | 00:19:24 Luisa Cutillo: @graham are you planning to create brand new modules? 9 | 00:20:11 Ayesha Dunk (she/her): https://www.raspberrypi.org/ 10 | 00:22:30 Eric Atwell: @Eric where/how did you learn Software Engineering as you did not do a Software Engineering BSc or PhD? 11 | 00:24:05 Andrew Moles: Why was Python used and not R? I've found learner find it easier to learn and get to making insights much faster with R 12 | 00:26:39 Luisa Cutillo: @carrie, can this be introduced at university level? 13 | 00:27:02 Carrie Anne Philbin: teachcomputing.org/curriculum - you can download the data science unit from here for free 14 | 00:27:24 Luisa Cutillo: @carrie, fantastic! Can I reach out later please? 15 | 00:27:51 graham.cole@newcastle.ac.uk: @ Luisa - I am indeed, beginning the first blush thinking now with a target of delivery in the 23-24 academic year 16 | 00:29:43 Luisa Cutillo: @graham, lot of work and very exciting. 17 | 00:32:38 Doschmund: @Graham- when you are teaching non cognates, where do you start? What works well? 18 | 00:34:28 Valentina Andries: @Luisa: are you using programming activities as part of teaching AI to children? do you address ethics of AI? 19 | 00:37:55 Eric Atwell: @Carrie Anne, I could not find the Data Science unit, at teachcomputing.org/curriculum ... can you share exact URL for this specifc page? 20 | 00:38:23 Carrie Anne Philbin: https://teachcomputing.org/curriculum/key-stage-3/data-science 21 | 00:38:38 Doschmund: Thanks Graham. I never thought of it as learning a langugage. thats a great analogy 22 | 00:39:10 Mervat Abuelkheir: What about mapping some AI concepts such as logic and KB to levels prior to university? What could be possible challenges and what could be a good start? Would introducing robotics with some basic intelligence tasks help clarify logic, KB, and reasoning later? 23 | 00:40:54 Ruby Chang: Thanks Graham, a fresh view of the R/Python language. 24 | 00:41:40 Valentina Andries: @Carrie- regarding the data science unit: what are the teachers' level of confidence teaching such concepts? Do they need any training? How easily can such units be integrated as part of their regular teaching practices? 25 | 00:43:34 Eric Atwell: @Mervat, I think this course does not cover AI concepts such as logic, KB, knowledge representation and reasoning, robotics, natural language processing, computer vision, deep learning, social media analytics etc ... the course is only about teaching programming for data analysis to small classes (less than 100) 26 | 00:44:20 Mervat Abuelkheir: @Eric, got it, and thank you Eric :) 27 | 00:45:02 Eric Atwell: @Mervat, maybe Turing should LATER host another ocurse on AI Educaiton, coviering teaching of these other areas of AI 28 | 00:46:49 Mervat Abuelkheir: @Eric, would be good, as I've seen initiatives to teach prep and high school students elements of logic embedded in robotics programming in summer camps and I was not sure if these can be too advanced concepts 29 | 00:49:12 Doschmund: For teachers in the group, is there a difference in method of teaching and content in terms of teaching different generations, as there are differences technology adoptions between last decade and this one for example? 30 | 00:54:41 Eric Atwell: @Doschmund, I guess fundamental concepts stay, eg CRISP-DM methodology, statistical concepts eg accuracy precsion and recall etc…. changes in technology are peripheral ... https://www.datascience-pm.com/crisp-dm-2/ https://medium.com/@erika.dauria/accuracy-recall-precision-80a5b6cbd28d 31 | 00:57:21 Eric Atwell: Do your data science courses include a practical Project? If so, do you use a Project textbook? If so, which Project textbook do you recommend? I am considering this one - is it any good? https://www.datascience-pm.com/crisp-dm-2/ 32 | 00:59:15 Eric Atwell: Sorry wrong URL I menat to ask is this a good textbook for AI+DS Projects? Projects in Computing and Information Systems: a students guide https://www.pearson.com/uk/educators/higher-education-educators/program/Dawson-Projects-in-Computing-and-Information-Systems-3rd-edn-A-Student-s-Guide-3rd-Edition/PGM1069173.html 33 | 01:02:57 Doschmund: In teaching Project Management, there are 2 things very important. 1. Lifecycle of an AI Project 2. how do you deliver it (i.e a project management methodology) 34 | 01:04:05 Doschmund: https://www.datascience-pm.com/ - provides an overview of both 35 | 01:05:09 Doschmund: If you are interested in knowing bit more, happy to chat to you. Thats one of my expert area 🙂 36 | 01:05:52 Doschmund: Also worth considering how to incorporate ethical considerations as part of the lifecycle 37 | 01:06:21 Ayesha Dunk (she/her): https://hackmd.io/ohIMf55ZS_eeThplfd-ERg?both 38 | 01:06:50 Carrie Anne Philbin: Thank you for inviting me. 39 | 01:07:04 Eric Daub: It was a pleasure to speak to everyone today! 40 | 01:07:35 Luisa Cutillo: and the chat too? :-) 41 | 01:07:53 Ruby Chang: Learned a lot of new ideas and will pilot them soon! 42 | 01:07:57 Kwong Cheong WONG: Thank you 43 | 01:07:58 MARIA NAVAS LORO: thank you, bye! 44 | 01:08:01 Martin Goodfellow: Thanks all 45 | 01:08:01 Ruby Chang: many thanks 46 | -------------------------------------------------------------------------------- /2022/cc7-continuous-evaluation-and-implementation-of-learner-feedback/ABOUT.md: -------------------------------------------------------------------------------- 1 | # Continuous evaluation and implementation of learner feedback: Wednesday 6 July 2022, 10 - 11:00am (GMT+1) 2 | 3 | ### Due to speaker apologies, this call has been cancelled. 4 | 5 | Breakout room sessions have been adapted to a [self-guided study](https://hackmd.io/o0jc-jHkQNynCuaZp9vIDg). Please complete this in your own time, adding your reflections directly into the HackMD document. 6 | 7 | 8 | -------------------------------------------------------------------------------- /2022/cc8-making-learning-memorable/2022-7-14 Making Learning Memorable Turing HClare v2.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/alan-turing-institute/ds-ai-educators-programme/df172e525d3e615170afa4011a2943df36fa64e0/2022/cc8-making-learning-memorable/2022-7-14 Making Learning Memorable Turing HClare v2.pdf -------------------------------------------------------------------------------- /2022/cc8-making-learning-memorable/2022-7-14 Making Learning Memorable Turing HClare v2.pptx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/alan-turing-institute/ds-ai-educators-programme/df172e525d3e615170afa4011a2943df36fa64e0/2022/cc8-making-learning-memorable/2022-7-14 Making Learning Memorable Turing HClare v2.pptx -------------------------------------------------------------------------------- /2022/cc8-making-learning-memorable/20220714_ImmersiveLearning_DPerezSuarez.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/alan-turing-institute/ds-ai-educators-programme/df172e525d3e615170afa4011a2943df36fa64e0/2022/cc8-making-learning-memorable/20220714_ImmersiveLearning_DPerezSuarez.pdf -------------------------------------------------------------------------------- /2022/cc8-making-learning-memorable/ABOUT.md: -------------------------------------------------------------------------------- 1 | # Making learning memorable: Thursday 14 July 2022, 10 - 11:00am (GMT+1) 2 | 3 | ### This call will cover the following points: 4 | - 'Seven ways to make your learning memorable' and Q&A 5 | - 'Creating an effective and enjoyable learning experience' and Q&A 6 | - '*Once upon a time...* or Immersive learning' and Q&A 7 | 8 | ### Today's speakers 9 | - [Helen Clare](https://www.jisc.ac.uk/staff/helen-clare) : [Jisc](https://www.jisc.ac.uk/)/[EOSC Synergy](https://www.eosc-synergy.eu/) 10 | - [Arron Lacey](https://github.com/arronlacey) : The Alan Turing Institute / EDoN 11 | - [David Pérez-Suárez](https://dpshelio.github.io/) : [UCL/ARC](http://ucl.ac.uk/arc/) 12 | 13 | ### Collaborative document from the call 14 | [HackMD]([https://hackmd.io/ohIMf55ZS_eeThplfd-ERg?both](https://hackmd.io/P8F8b33rSpKUgAlwkGALmQ)) 15 | 16 | ### Recording 17 | [Youtube recording](https://www.youtube.com/watch?v=3BvfWGwJ7Ao) 18 | -------------------------------------------------------------------------------- /2022/cc8-making-learning-memorable/CC8 - Making learning memorable CHAT.txt: -------------------------------------------------------------------------------- 1 | 00:15:27 Arron Lacey: my talk title has been updated to :Creating and Effective and Enjoyable Learning Experience 2 | 00:15:54 Doschmund: What are you all discussing in the chat? No idea 3 | 00:16:47 Eric Atwell: sorry I was waiting in the lobby ... what have I missed so far? 4 | 00:16:56 Mishka Nemes (she/her) | Alan Turing Institute: Hi Doschmund, we had a roll call questions on 'What is your highlight from the programme so far?’ 5 | 00:17:03 MARIA NAVAS LORO: @Doschmund the highlights of the course for each of us 6 | 00:17:16 Mishka Nemes (she/her) | Alan Turing Institute: @Eric - nothing major, just the usual housekeeping 😄 7 | 00:17:23 Doschmund: Oh I see, I didn't hear that part 🙂 8 | 00:20:57 Eric Atwell: “learning through dialogue” - how does this scale to classes of 200+ students? 9 | 00:22:14 Luisa Cutillo: @eric often my students freeze when I ask questions unfortunately, unless they are about 40 it does not work much for me 10 | 00:25:31 David Perez-Suarez | UCL: There was a session I attended at a mozfest a few years ago where they taught programming through dancing! It was awesome!! 11 | 00:25:52 Adnane Ez-zizi: Storytelling seems like a powerful tool - can you please give some ideas about how to find the stories to use in the context of AI and data science? 12 | 00:26:05 Arron Lacey: did they use for loops instead of hula hoops? 13 | 00:26:22 Eric Atwell: @Helen I notice your ppt style is different from most AI presentations, you have pictures but very little information (text and tsbles and figures) - why did you choose this style? Do you prefer "podcasts”with audio only, so students do not need to stay glued to the screen? 14 | 00:27:09 David Perez-Suarez | UCL: In the choreography, repeatingt the steps, that were the for loops. Hula hoops could be used too! 15 | 00:27:21 Eric Atwell: Please put the link in the chat 16 | 00:27:24 Andrew Moles: This was great! We use a very question heavy form of training too 🙂 17 | 00:27:45 Anastasis Georgoulas: Do we have the hackmd link for this week? (to look at the links mentioned!) 18 | 00:30:17 Mishka Nemes (she/her) | Alan Turing Institute: HackMD link: we will be adding links as we share them here and will extract them from the presentations after this call 🙂 https://hackmd.io/P8F8b33rSpKUgAlwkGALmQ?both 19 | 00:34:48 jakemarshall: Also good to stay away from func, func2, func_final etc! 20 | 00:35:49 Andrew Moles: Totally agree about adding in fun examples! 21 | 00:35:50 Doschmund: Is there a reason behind complete black screen with white letters? 22 | 00:38:03 Eric Atwell: Many students have limited time, and choose not to do formative exercises (action), as a waste of their time - they only do practical exercises if there are marks (summative) ... how do we solve this? 23 | 00:40:50 Adnane Ez-zizi: @Arron what tool are you using to make your slides? 24 | 00:41:06 Kieran Baker: Was just about to ask that! 25 | 00:41:51 Adnane Ez-zizi: ;-) 26 | 00:42:10 jakemarshall: Omg I love that picture, real world data is such a different beast 27 | 00:42:12 Eric Atwell: MWE = Multi Word Expression. (in natural language processing0 28 | 00:42:16 Andrew Moles: I'd guess https://github.com/yihui/xaringan or https://quarto.org/ but excited to find out! 29 | 00:42:52 jakemarshall: Kaggle is awesome for codealongs! We recently used it in our data science festival at the ONS 😄 30 | 00:48:28 Mishka Nemes (she/her) | Alan Turing Institute: Please keep the questions coming! 😄 31 | 00:49:26 Arron Lacey: @eric on assignment i like to drop, for 25% of the marks “discuss the theory behind back propagation" - that usually helps! 32 | 00:55:30 Helen Clare (Jisc, UK): David and I didn't plan this! 33 | 00:57:23 Adnane Ez-zizi: Question for both @Helen and @David: Storytelling is clearly a powerful tool, but how to create and find your stories to use in the class? 34 | 01:00:18 Helen Clare (Jisc, UK): This guide can help with building stories (not the ideas part!) https://www.jisc.ac.uk/guides/vision-and-strategy-toolkit/narrative-thinking-and-communication 35 | 01:05:50 Adnane Ez-zizi: Thanks @Helen - looks great 36 | 01:07:49 Malvika Sharan (she/her): We will curate the questions and add on Slack where the speakers can respond. 37 | -------------------------------------------------------------------------------- /2022/cc9-collaboration-between-industry-and-academia/ABOUT.md: -------------------------------------------------------------------------------- 1 | # Collaboration between industry and academia (panel session): Thursday 21 Juy 2022, 10 - 11:00am (GMT+1) 2 | 3 | ### This call will cover the following points: 4 | Introductions: 5 | - A little bit about you, who you are and where you're joining from. 6 | - What is your role? 7 | - How does Data Science and AI feature in your role? 8 | 9 | General questions: 10 | - What challenges or barriers have you faced in the planning/delivery of data science, AI or both? 11 | - What key learnings have you taken from these challenges? 12 | - How did you use these learnings to start to overcome/overcome these challenges? 13 | 14 | Wrap-up questions: 15 | - Top tips? 16 | - What 'easy wins' can you recommend? 17 | 18 | ### Today's speakers 19 | - Matt Forshaw (Chair) 20 | - Graham Cole, Newcastle University 21 | - Eric Daub, The Alan Turing Institute 22 | - [Carrie Anne Philbin MBE](https://www.linkedin.com/in/carrieannephilbinmbe/), [Raspberry Pi Foundation](https://www.raspberrypi.org/) 23 | 24 | ### Collaborative document from the call 25 | [HackMD](https://hackmd.io/ohIMf55ZS_eeThplfd-ERg?both) 26 | 27 | ### Recording 28 | -------------------------------------------------------------------------------- /2022/cc9-collaboration-between-industry-and-academia/CC9 - Collaboration between industry and academia CHAT.txt: -------------------------------------------------------------------------------- 1 | 00:18:20 Malvika Sharan (she/her): Aww. I am sorry Luisa. Thank you for joining. I hope you feel better soon. 2 | 00:18:25 Maarya Sharif: Edinburgh, Scotland only 16°C 3 | 00:18:45 Ayesha Dunk (she/her): Yes - feel better soon Luisa! 4 | 00:18:54 Malvika Sharan (she/her): Maarya, It’s similar in London right now. 5 | 00:19:09 Andrew Csizmadia: 17°C with a grey cloud cover here in North Wales. 6 | 00:19:19 Riddhima Kedia: lovely 19C here in Southampton 7 | 00:20:34 Nancy Ruzycki: oh, you are not too hot! that is so nice. 8 | 00:28:43 Nancy Ruzycki: Are simple models sufficient? Would you want them to have more complex model experience with more parameters or are simple models sufficient to show competency? 9 | 00:28:51 Maryleen: Data study groups are amazing! 10 | 00:29:43 jakemarshall: So there is no opportunity for those at 'entry level' then? Those who have just left masters for example will have only done projects in the academic sense, so I imagine it's hard for them to find that hands on experience when they can't get jobs because of a lack of it, if that makes sense? 11 | 00:29:51 Eric Atwell: Q: when you ask “have they built a neural net” - do you mean “have they implemented a NN algortihm in Python" or do you mean “have they used a state-of-the-art NN python tool, eg AraBERT, to slove a practical task?" 12 | 00:31:36 Matt Forshaw (he/him): Thank you so much for your questions. Please keep them coming in and i'll make sure we get to each of them during the session. 🙂 13 | 00:32:30 Eric Atwell: We teach Computing and AI Degree Apprentices at Leeds (Accenture apprentices!), they use existing NN tools and resources (eg in COLAB), is this not relevant to industry? 14 | 00:33:26 Maryleen: Q: What are your thoughts on degree apprenticeships as an initiative to bridge the gap between academia and industry, what are the challenges and opportunities? 15 | 00:33:57 Maryleen: +1 Eric 16 | 00:35:02 jakemarshall: Yes that self awareness of failure as well is really important in a well rounded Data Scientist 😄 17 | 00:35:13 Luisa Cutillo: Q: any suggestion on how to approach industry and involve them for hands on experiences with our master students? 18 | 00:35:35 jakemarshall: Yeah absolutely 😛 I wanted to check that those kinds of examples would also be relevant as well, rather than just direct hands on experience! Thanks so much 😄 19 | 00:37:44 Nancy Ruzycki: Yes access to large computing resources like GPT3 or a super computer is difficult for many students in terms of projects even at well resourced universities. There is not equitable access to computing resources which could exclude students from careers. 20 | 00:38:38 RYAN CROSBY: My query would be how does that work with widening participation / edi. Should we in HE not be putting these practical experiences in the course? 21 | 00:38:55 Eric Atwell: Surely ALL AI and Data Science graduates (BSc and MSc) HAVE done practical implementation projects?? This is a requirement for BCS accreditation of our computing degrees at Leeds Uni. Does Industry value BCS accreditation? 22 | 00:38:56 RYAN CROSBY: What about students who dont have time / ability to do extra outside of the course that they're doing? 23 | 00:39:11 Doschmund: There seems to be more focus on PhDs, Wouldn't that exclude large proportion of capable students at Masters level 24 | 00:42:25 Malvika Sharan (she/her): Very good point Doschmund. 25 | 00:42:29 Eric Atwell: @Richard - do you mean you bring together AI/DS practitioners with “users”/“clients” who dont have AI/DS expertise? Do all your projects involve non-AI/DS partners? 26 | 00:45:22 Maryleen: Very relatable, Richard. I was a 2020 DSG facilitator. It was a very valuable experience for my career. 27 | 00:46:01 Matt Forshaw (he/him): @Maryleen, that's wonderful to hear. I think our paths crossed during the 2020 DSG. 28 | 00:46:46 Maryleen: Thanks, Matt 29 | 00:47:23 Richard Plant: Thanks Maryleen, I'm very happy it was a good experience for you! 30 | 00:48:02 Luisa Cutillo: @graham do you struggle with different students knowledge background? 31 | 00:49:43 Nancy Ruzycki: Would this have to do with the fact many faculty have had little industry experience or experience with industry problems? 32 | 00:50:11 Salomey Afua Addo: Nancy I think so. 33 | 01:03:17 Eric Atwell: Accenture is a big company. Does anyone else have experience of link to a small specialist company, eg SketchEngine is a market leader in text analytics and has long-term collaboration with Leeds and other UK universities in corpus linguistics and text analytics 34 | 01:04:36 Doschmund: @Darren, it is very good to hear that there is focus on inclusivity from Accenture. 35 | 01:06:08 Doschmund: People who work within Industry myself included are well aware of the difficulties in recruiting and retaining skills. There is a significant budget allocated to skill development retention. 36 | 01:06:09 Darren Seymour-Russell: Thank you. It's hard to say this without sounding cliched. But inclusivity and social mobility and hugely important for the company and we work hard to break down barriers - at all levels 37 | 01:06:10 RYAN CROSBY: Thank you for your answers - I know it was a loaded / difficult question 38 | 01:06:17 Matt Forshaw (he/him): https://groupgti.com/ai-scholarships 39 | 01:06:28 Nancy Ruzycki: We work with Citrine in our department to create projects for AI in Materials 40 | 01:07:19 Richard Plant: In terms of projects of varying scale, it might be worth taking a look at the Turing Internship Network: https://www.turing.ac.uk/collaborate-turing/internships 41 | 01:07:23 Kieran Baker: really interesting session, thanks! 42 | 01:07:24 Nancy Ruzycki: thanks 43 | 01:07:24 Kwong-Cheong Wong: Thank you 44 | 01:07:26 Noorhan: Thank you very much 45 | 01:07:27 jakemarshall: Thanks 😄 46 | -------------------------------------------------------------------------------- /2022/graduation-session-1/ABOUT.md: -------------------------------------------------------------------------------- 1 | ## Session Zoom chat 2 | [Graduation Session 1 CHAT.txt](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/9281369/Graduation.Session.1.CHAT.txt) 3 | 4 | ## Collaborative document 5 | [HackMD](https://hackmd.io/HeWzjj6-STeHSXk0LYAQmA) 6 | -------------------------------------------------------------------------------- /2023/README.md: -------------------------------------------------------------------------------- 1 | A folder for the 2023 run of the Data Science and AI Educators' Programme. 2 | -------------------------------------------------------------------------------- /2023/carpentries-pedagogy-week-1/README.md: -------------------------------------------------------------------------------- 1 | **_Week 1: 3 and 4 May 2023, Initial Pedagogy Sessions_** 2 |
3 | ## Collaborative documents 4 | [3 and 4 May collaborative etherpad](https://pad.carpentries.org/2023-05-03-ATI) 5 | 6 | ## Slides 7 | [Instructor Training Day 2 - Live coding is a skill & Preparing to Teach.pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11440523/Instructor.Training.Day.2.-.Live.coding.is.a.skill.Preparing.to.Teach.pdf)
8 | [3-Teaching is a skill .pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11440524/3-Teaching.is.a.skill.pdf)
9 | [2-Motivation and Demotivation.pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11440525/2-Motivation.and.Demotivation.pdf)
10 | [1-Memory and Cognitive Load.pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11440527/1-Memory.and.Cognitive.Load.pdf)
11 | [Instructor Training Day 1 - Building Skills with Practice & Feedback .pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11440528/Instructor.Training.Day.1.-.Building.Skills.with.Practice.Feedback.pdf)
12 | [Equity, inclusion and accessibility.pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11440529/Equity.inclusion.and.accessibility.pdf) 13 | 14 | ## Speakers 15 | - Lisanna Paladin
16 | - Malvika Sharan
17 | - Ayesha Magill
18 | 19 | ## Recordings 20 | [Day 1 - Zoom chat.txt](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11450186/Day.1.-.Zoom.chat.txt)
21 | [Day 2 - Zoom chat.txt](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11450187/Day.2.-.Zoom.chat.txt)
22 | [Day 1 recording](https://youtu.be/I09LVHs3zK4)
23 | [Day 2 recording](https://youtu.be/F9rZvTPCSFk) 24 | -------------------------------------------------------------------------------- /2023/cc1-identifying-learner-needs/README.md: -------------------------------------------------------------------------------- 1 | # CC1: Identifying Learner Needs 2 | 3 | ## Speakers 4 | - Vera Matser, Head of Skills, The Alan Turing Institute 5 | - Matt Forshaw, Senior Advisor for Skills, The Alan Turing Institute 6 | 7 | ## Resources 8 | 1. [CC1: 'Identifying learner needs' slides](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11507807/CC1.Identifying.learner.needs.pdf)
9 | 2. [HackMD](https://hackmd.io/cxvp9Up_Qd-X5XYn-cEsEg)
10 | 3. [Collaborative Miro board](https://miro.com/app/board/uXjVMKqctcE=/) 11 | 12 | ## Recordings 13 | [CC1 recording](https://youtu.be/jFnC6SnAKU8)
14 | [CC1 Zoom chat](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11518030/CC1.Zoom.chat.txt) 15 | 16 | -------------------------------------------------------------------------------- /2023/cc1-identifying-learner-needs/learner-needs.md: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | Identify where in the book this chapter lives 5 | - guide: communication 6 | - chapter: open scholarship (renaming TBC) 7 | - subchapter: new titled *identifying learner needs* 8 | 9 | 10 | 11 | 12 | # Identifying Learner Needs 13 | Designing effective learning products begins with a deep understanding of your learners. Every educator's objective is to prepare the best learning material ahead of any lesson. Whether you are developing a course, demonstrating software, or providing training, your aim is to use the best ideas, communication strategies, and learning outcomes. However, what is considered the "best" can vary according to the context and audience. This chapter compiles the experiences of educators from diverse fields, especially those involved in Data Science and Education study groups, to guide you in creating learning personas and designing educational content tailored to your learners' needs. 14 | 15 | Key ideas covered in this chapter: 16 | - [Designing your learning products](#designing-your-learning-products) 17 | - [Start with research](###Start-with-research) 18 | - [Show and Tell](###Show-and-Tell) 19 | - [Empathy](###Empathy) 20 | - [Never assume, deconstruct bias](Never-assume,-deconstruct-bias) 21 | - [Include everyone, accessibility (eg. neurodiversity)](###Include-everyone,-accessibility-(eg.-neurodiversity)) 22 | - [Learning Persona](##Learning-Persona) 23 | - [Group Activities to Identify Learner Needs](###Group-Activities-to-Identify-Learner-Needs) 24 | - [Learner Surveys](####Learner-Surveys) 25 | - [Feedback Circles](####Feedback-Circles) 26 | - [Brainstorming sessions](####Brainstorming-sessions) 27 | - [ Competency Profiles and Professional Standards](##Competency-Profiles-and-Professional-Standards) 28 | - [What is a competency?](###What-is-a-competency?) 29 | - [Key aspects of the competency-based approach](###Key-aspects-of-the-competency-based-approach) 30 | - [Competency frameworks and accreditation](###Competency-Frameworks-and-Accreditation) 31 | - [T-Shaped competency framework](####T-Shaped-Competency-Framework) 32 | - [Professionalization and Accreditation of Data Science](####Professionalization-and-Accreditation-of-Data-Science) 33 | - [AdvanceHE: Professional Standards Framework for Educators - A Case Study ](####AdvanceHE:-Professional-Standards-Framework-for-Educators--A-Case-Study) 34 | 35 | ## Designing your learning products 36 | Among the possible ways of starting your teaching material design, a great consensus in the educators' cohorts is to focus on your user experience (UX), using the so called UX principles. In the following we identify and describe 5 UX principles that can be pitched for your particular kind of users: the 'learners'. 37 | ### Start with research 38 | In designing effective educational content, begin by conducting thorough research early on to aid your overall preparation. First step could be to form a clear picture of the topics your delivery will cover, making sure to touch on all the relevant problems and questions related to it (**Key Topics Identification**). Which are the relevant questions you should address? A way to find out is to research such questions and also brainstorm with your team (**Relevant Questions**). If you do not have one, you could share a document with colleagues or experts in the field for feedback and discussion (**Feedback and Discussion**). It is also very important to clarify from the beginning how you would measure the success of your product (**Success Metics**). After this phase, you could start specifying goals and objectives, problems and solutions, timeline, delivery modalities, measures of success, in a specification document. 39 | ![RPD](https://hackmd.io/_uploads/HkHpx2aNC.png) 40 | 41 | ### Show and Tell 42 | A natural further step is to show your drafted plan to a selected expert audience (ideally your team). This will allow quick feedback to inform interatively a revision of your delivery plan as well as objectives and principles. You could reiterate this process, maybe involving a different audience, till you are happy with the overall result and consensus. The final product could be your prototype that you could test on a small set of users. Feedback from the users will be essential to refine your delivery project. You will be finally ready for delivery to your learner audience. 43 | 44 | ### Empathy 45 | 46 | One essential element of designing learning material is to do it with empathy for your users. This literally means being able to understand the learner perspectives, challenges and struggles. When designing you should be aware of learners' struggles and challenges. A good way to collect this information and embed empathy in you project could be to consult your potential audience (when possible), surveying their backgrounds, challenges and expectations. This will help you design material that addresses the learners' specific needs and fits well into their learning context. 47 | ![Empathy](https://hackmd.io/_uploads/rkGp5l1BC.png) 48 | 49 | 50 | 51 | ### Never assume, deconstruct bias 52 | When creating learning resources, it is important to be aware of biases and assumptions. Biases can unconsciously impact how you come up with new ideas, and therefore affect how you design and build the resources. Deconstructing biases means re-examining the knowledge and beliefs we all have, be open to feedback and developing new ways of thinking to guide the work moving forward. For instance, you can ask yourself: 53 | - Which parts of my thinking show bias or lack verification? 54 | - What other perspectives or data am I leaving out of my analysis? 55 | - If I step into someone else's shoes, how might they view this design differently? 56 | - What unconscious stereotypes or generalizations could I be making that need to be confronted? 57 | 58 | Questioning preconceived notions and presumptions is a crucial principle that every user experience (UX) designer must adopt. Designers should strive to eliminate their existing biases and assumptions by embracing diverse perspectives, challenging their thought processes, and developing a deep understanding of their target users. 59 | 60 | 61 | ### Include everyone, consider accessibility (eg. neurodiversity) 62 | Considering accessibility from the outset of the learning resources design process is crucial. Accessible design entails creating a solution that is inclusive and usable for a diverse range of learners, including those with disabilities. By prioritising accessibility early on, educators can ensure that the final learning resources cater to the needs and abilities of a broader audience, fostering an environment of inclusivity and equal opportunities. 63 | 64 | Some key factors to be considered: 65 | - **Multimodal Content Presentation:** Provide content in multiple formats such as text, audio, video, and interactive elements. This accommodates different learning styles and preferences, as well as learners with disabilities (e.g., visual impairments, hearing impairments). 66 | - **Clear and Simple Language:** Use plain language that is easy to understand, avoiding complex jargon or technical terms unless they are properly explained. This helps learners with cognitive or language barriers. 67 | - **Adjustable Font Size and Colour Contrast:** Allow users to adjust font sizes and ensure sufficient colour contrast between text and background. This improves readability for learners with visual impairments or specific visual needs. 68 | - **Captioning and Transcripts:** Provide captions for audio and video content, as well as transcripts for audio materials. This accommodates learners with hearing impairments or those who prefer reading over listening. 69 | - **Keyboard and Assistive Technology Compatibility:** Ensure that all interactive elements, such as navigation menus, buttons, and forms, are fully accessible through keyboard input and compatible with assistive technologies like screen readers. 70 | - **Logical and Consistent Structure:** Organize content in a logical and consistent manner, using clear headings, subheadings, and navigation cues. This helps learners with cognitive or attention-related disabilities follow the material more easily. 71 | - **Culturally Responsive and Inclusive Content:** Represent diverse cultures, backgrounds, and perspectives in the learning materials, avoiding stereotypes or biases. This promotes inclusivity and makes learners from different backgrounds feel valued and represented. 72 | - **Customisable and Flexible Delivery:** Offer options for learners to customise the learning experience according to their needs and preferences, such as adjusting the pace, sequence, or format of the content. 73 | - **Accessible Assessment and Feedback:** Design assessments and provide feedback in an accessible manner, considering the diverse needs of learners and offering alternative formats or accommodations as necessary. 74 | 75 | By incorporating these factors, learning resources can become more inclusive and accessible to a wide range of learners, regardless of their abilities, backgrounds, or learning preferences. 76 | 77 | ## Learning Personas 78 | A learning persona is a detailed and data-driven representation of a specific part of your target audience for educational content. It is based on real data and insights about your learners' attributes such as demographics, behaviours, goals, challenges, and preferences. The identification of learning personas is essential to help educators create more targeted, effective, and engaging learning experiences by understanding and addressing the unique needs of different learner groups. 79 | 80 | ### Group Activities to Identify Learner Needs 81 | Educators can use various group activities to collaboratively identify and define learning personas. These activities help gather insights about different learner segments, ensuring that the educational content is tailored to meet diverse needs. Examples include brainstorming sessions, focus groups, interactive polls and quizzes, and feedback circles. Some of these activities like live polls and quizzes can be conducted with a wide audience and anonimously. On the other hand, in order to facilitate sharing, the activities that involve learners more personally will have best results if conducted with smaller groups. This will facilitate sharing and empathy. Before staing any of these activities it is essential to set ground rules to establish guidelines and to ensure respectful and constructive behaviour. In the following, we describe a few group activities useful for the identification of learning personas within your target audience. 82 | 83 | #### Learner Surveys 84 | This activity has the objective of collecting quantitative data on learner demographics, preferences, and challenges that will be useful to make necessary changes in your teaching material and practice. You could create a mix of question types to gather comprehensive data focussing on about learning habits, preferences, goals, and obstacles. For example you can use multiple-choice, Likert scale, open-ended or ranking questions to capture different aspects of the learners' experiences. The analysis of the responses should aim to identify patterns, trends, key insights and learner groups. 85 | 86 | #### Feedback Circles 87 | This activity has the objective to create a safe and supportive environment where your audience can share constructive feedback. Ideal group size is between 6 and 12 participants. You could start with an icebreaker to build rapport and to create a comfortable atmosphere. Each person shares their thoughts about specific aspects of their learning experience they want to discuss, such as teaching methods, classroom environment, materials used, or any particular challenges they face. The rest of the group will provide feedback and this will be followed by a brief discussion to reiterate suggestions and agree on possible solutions. This process can be continued until each learner has had the opportunity to share and receive feedback. 88 | 89 | #### Brainstorming Sessions 90 | A brainstorming session has similar goals to the feedback circles, but it is less structured. This can involve an entire class or smaller selected representative groups. It is important to emphasize the importance of being open and to not criticise ideas during brainstorming, but to reflect contrusctively and to build on others’ ideas. Ideally, you can start the activity with an icebreaker and define a focus area. For example, you could clearly state the focus question: "What are the biggest challenges you face in your learning?" then give students a few minutes to write down as many ideas as they can think of individually. Ideas can be then shared freely and you could map them on a whiteboard, large paper or electronic dashboard such as Miro. You could close your session by summarizing and defining an action plan. 91 | 92 | ## Competency Profiles and Professional Standards 93 | ### What is a competency? 94 | To effectively identify learners' needs, educators should have access to and utilize specific competency profiles and professional standards relevant to their field of instruction. A competency is a combination of skills, knowledge, and behaviors/attitudes that an individual must have to perform a specific job or task effectively. It encompasses not only technical abilities and expertise but also personal attributes such as problem-solving, communication, teamwork, and adaptability. Competencies are often used in educational contexts to assess and develop individuals' abilities to meet specific standards or achieve particular goals. 95 | Here is an example of knowledge, skills, and behavior in the context of teaching data science in higher education: 96 | - **Knowledge**: Understanding advanced data science concepts and methodologies. 97 | - Example: A data science educator has in-depth knowledge of machine learning algorithms, statistical analysis, and data visualization techniques, which they use to inform their curriculum and lectures. 98 | - **Skills**: The ability to effectively teach and apply data science techniques. 99 | - Example: The educator skilfully designs and conducts hands-on projects and coding labs, allowing students to apply theoretical knowledge to real-world datasets using programming languages like Python and tools like Jupyter Notebooks. 100 | - **Behaviour/Attitude**: Demonstrating professional and ethical behaviour in an educational setting. 101 | - Example: The educator shows a commitment to academic integrity by promoting ethical data usage, encouraging collaboration over competition, and providing constructive feedback to support student development. 102 | 103 | ### Key aspects of the competency-based approach 104 | A competency-based approach for educators focuses on ensuring that both teaching and learning are centered around clearly defined competencies—specific skills, knowledge, and behaviors that students need to master. This approach emphasizes the outcomes of the learning process rather than the traditional time-based methods. 105 | Please hover over the bubbles to read more about the key aspects of competency-based approach: 106 | 107 | 134 | 135 | 136 |
137 | Focus on Outcomes 138 |
139 | Emphasising the desired outcomes or competencies that learners must achieve, rather than the time spent in a course or the specific content covered. 140 |
141 |
142 | 143 |
144 | Personalization and Flexibility 145 |
146 | Allowing learners to progress at their own pace, based on their individual needs and prior knowledge. In addition, offering flexibility in how learning occurs, which can include online, in-person, or hybrid models, and recognizing prior learning and experiences. 147 |
148 |
149 | 150 | 151 |
152 | Continuous Improvement 153 |
154 | Encouraging ongoing reflection and adaptation of the educational program based on feedback and assessment data to ensure it meets the evolving needs of learners and the industry. 155 |
156 |
157 | 158 |
159 | Relevance to Real-World Applications 160 |
161 | Ensuring that competencies are aligned with real-world skills and requirements, making the education directly applicable to professional and practical scenarios. 162 |
163 |
164 |
165 | Clear Competency Definitions and Assessments 166 |
167 | Establishing well-defined and measurable competencies that specify the skills, knowledge, and behaviours required. Also, using various assessment methods to evaluate whether learners have achieved the defined competencies, often requiring the demonstration of skills through practical applications or projects which can be collected in a portfolio. 168 |
169 |
170 | 171 | ### Competency Frameworks and Accreditation 172 | Competency frameworks for educators are structured outlines that define the skills, knowledge, behaviors, and attitudes educators need to perform their roles effectively. These frameworks provide clear expectations and benchmarks for professional development, instructional practice, and career progression. In the following we describe the T-shaped competency framework and give details about professionalization and accreditation in Data Science education. 173 | #### T-Shaped Competency Framework 174 | A T-shaped competency refers to a model for skills and expertise characterised by two dimensions: 175 | 1. **Depth of Knowledge (the vertical bar of the "T")**: 176 | - This represents deep expertise and proficiency in a specific area or discipline. It indicates a strong foundation and advanced skills in a particular field, allowing the individual to be highly competent and specialised in that domain. 177 | 178 | 2. **Breadth of Knowledge (the horizontal bar of the "T")**: 179 | - This represents a wide range of knowledge across multiple disciplines or areas. It indicates the ability to collaborate across different fields, understand various perspectives, and apply knowledge from other areas to their specialised field. 180 | 181 | In a nutshell, T-shaped competencies describe professionals who possess deep expertise in one area while also having broad knowledge across other areas, making them versatile and effective in collaborative and interdisciplinary environments. This model is particularly valued in domains that require innovation, teamwork, and adaptability like data science. 182 | 183 | You can access a number of different competency frameworks using this link [https://competency.ebi.ac.uk/](https://competency.ebi.ac.uk/) 184 | 185 | 186 | #### Professionalization and Accreditation of Data Science 187 | Accreditations for educators vary depending on the country and the specific area of education. The general aim of accreditations is to ensure that educators, whether individual teachers or educational institutions, meet established standards of quality and effectiveness. 188 | 189 | 190 | In the data science and AI domain, there are several accreditation and professionalization bodies serving various purposes. Due to the rapid growth and evolution of these fields, multiple bodies ensure that certifications and standards keep pace with technological advancements. Additionally, data science and AI find diverse applications across industries like healthcare, finance, and marketing, prompting different accreditation bodies to cater to specific needs and standards within these sectors. Moreover, accreditation bodies play a crucial role in standardizing skills and knowledge, ensuring that certified professionals meet predetermined levels of competency and adhere to best practices. Furthermore, different regions and countries may have their own accrediting bodies to maintain local standards and practices, thereby promoting global recognition and mobility. Certification and accreditation also provide a pathway for continuous professional development, enabling individuals to stay abreast of new tools, techniques, and industry standards. Employers value certifications from recognized bodies as they instill confidence in the skills and knowledge of their employees, aiding in recruitment and career advancement. Finally, ethical standards in data science and AI are paramount, and accreditation bodies contribute to establishing and enforcing ethical guidelines within the profession. Examples of professional accreditation bodies are: 191 | - The Alan Turing Institute
192 | - The BCS (The Chartered Institute for IT)
193 | - Royal Academy of Engineering
194 | - The Operational Research Society
195 | - Institute of Mathematics and its Applications
196 | - Royal Statistical Society 197 | 198 | Some examples of higher education professional bodies: 199 | - In Africa, The Association of African Universities (AAU) 200 | - In the USA, American Council on Education (ACE) 201 | - In the UK, AdvanceHE 202 | - In Italy, ANVUR (Agenzia Nazionale di Valutazione del Sistema Universitario e della Ricerca) 203 | - In Australia, Tertiary Education Quality and Standards Agency (TEQSA) 204 | - In Canada, Universities Canada 205 | 206 | 207 | #### AdvanceHE: Professional Standards Framework for Educators - A Case Study 208 | We give in this section a case study specific for professional standards framework in the UK. The [Professional Standards Framework (PSF'23)](https://www.advance-he.ac.uk/teaching-and-learning/psf) is a competency framework which governs teaching and supporting learning in the UK higher Education context. AdvanceHE operates a ["Fellowship Category Tool"](https://www.advance-he.ac.uk/form/fellowship-decision-tool-2023) which allows you to demonstrate personal and institutional commitment to professionalism in learning and teaching in higher education. It breaks down competency around professional values, core knowledge and areas of activity. We list in the following some of the professional values and core knowledge that this entails. 209 | 210 | **Professional Values** 211 | - **V1** respect individual learners and diverse groups of learners 212 | - **V2** promote engagement in learning and equity of opportunity for all to reach their potential 213 | - **V3** use scholarship, or research, or professional learning, or other evidence-informed approaches as a basis for effective practice 214 | - **V4** respond to the wider context in which higher education operates, recognising implications for practice 215 | - **V5** collaborate with others to enhance practice 216 | 217 | **Core Knowledge** 218 | - **K1** how learners learn, generally and within specific subjects 219 | - **K2** approaches to teaching and/or supporting learning, appropriate for subjects and level of study 220 | - **K3** critical evaluation as a basis for effective practice 221 | - **K4** appropriate use of digital and/or other technologies, and resources for learning 222 | - **K5** requirements for quality assurance and enhancement, and their implications for practice 223 | **Areas of Activity** 224 | - **A1** design and plan learning activities and/or programmes 225 | - **A2** teach and/or support learning through appropriate approaches and environments 226 | - **A3** assess and give feedback for learning 227 | - **A4** support and guide learners 228 | - **A5** enhance practice through own continuing professional development 229 | 230 | ## Summary 231 | Understanding the needs of learners is fundamental to designing effective learning products. Insights from various educators are compiled in this chapter to help create learning personas and tailor content accordingly. When designing learning products, a strong focus should be on user experience (UX) principles. The initial step involves thorough research to identify key topics, relevant questions, and metrics for success. Plans should be presented to experts for feedback and refined based on their input. 232 | 233 | Designing with empathy requires understanding the perspectives and challenges of learners. It is crucial to avoid assumptions and be open to diverse perspectives to deconstruct biases. Ensuring inclusivity means considering the needs of all learners, including those with disabilities. Creating detailed representations of different learner groups, known as learning personas, helps tailor educational content. Group activities, such as brainstorming sessions, focus groups, and feedback circles, are effective methods for gathering insights about learner needs. 234 | 235 | To effectively identify learners' needs, educators should have access to and utilize specific Competency Profiles and Professional Standards relevant to their field of instruction. We focused on the competency-based approach that combines skills, knowledge, and behaviors needed to perform tasks effectively, focusing on outcomes, personalization, continuous improvement, real-world relevance, and clear competency definitions. The T-shaped competency framework combines deep expertise in one area with broad knowledge across multiple areas. 236 | 237 | Finally, we described the role of various accreditation bodies to ensure standardization, quality, and ethical practices in data science and AI. We provided 'The AdvanceHE Professional Standards Framework' as a case study, to outline professional values, core knowledge, and areas of activity essential for educators in higher education in the UK. 238 | 239 | ## Further reading & useful resources 240 | 241 | To be added here -------------------------------------------------------------------------------- /2023/cc10-making-teaching-relevant-to-real-world-problems/ReadME.md: -------------------------------------------------------------------------------- 1 | # CC10: Embedding ethics: making teaching relevant to real world problems 2 | 3 | ## Speakers 4 | - Dr Zachary Goldberg, Ethics Innovation Manager, Trilateral Research 5 | 6 | ## Resources 7 | 1.[Bridging Industry and Academia.pptx](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/12026116/Bridging.Industry.and.Academia.pptx)
8 | 2. [HackMD](https://hackmd.io/tjH4C-gnQLKS3F9ClWLMJw)
9 | 10 | ## Recordings 11 | -------------------------------------------------------------------------------- /2023/cc2-challenges-with-teaching-ds-and-ai/ReadME.md: -------------------------------------------------------------------------------- 1 | # CC2: Challenges with teaching DS and AI 2 | 3 | ## Speakers 4 | - Matt Forshaw, Senior Advisor for Skills, The Alan Turing Institute 5 | - David Stern, Director, IDEMS International 6 | - Ogerta Elezaj, Lecturer in Computer Science, Birmingham City University 7 | - Graham Cole, Lecturer in Enterprise, Newcastle University 8 | 9 | ## Resources 10 | 1. [HackMD](https://hackmd.io/x03xAVgBQnCPTvEBYtVCfQ) 11 | 12 | ## Recordings 13 | [CC2 recording](https://youtu.be/FSS5dY2-XA4)
14 | [CC2 Zoom chat.txt](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11679272/CC2.Zoom.chat.txt) 15 | 16 | 17 | -------------------------------------------------------------------------------- /2023/cc3-post-pandemic-teaching/ReadME.md: -------------------------------------------------------------------------------- 1 | # CC3: Post-pandemic teaching - what does it look like? 2 | 3 | ## Speakers 4 | - Richard Waites, University Professor and Director for students in the biosciences, University of York 5 | 6 | ## Resources 7 | 1. Slides to go here 8 | 2. [HackMD]((https://hackmd.io/2CwAH3cnQMCeSG8rQDexVA)
9 | 10 | ## Recordings 11 | [CC3 recording](https://youtu.be/wCPulHjzKO4)
12 | [CC3 Zoom chat.txt](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11679137/CC3.Zoom.chat.txt) 13 | -------------------------------------------------------------------------------- /2023/cc4-making-learning-memorable/ReadMe.md: -------------------------------------------------------------------------------- 1 | # CC4: Making Learning Memorable 2 | 3 | ## Speakers 4 | - Aline Nardo, Lecturer in Philosophy of Education, University of Edinburgh 5 | - David Perez-Suarez, Senior Research Software Developer, UCL 6 | - Arron Lacey, Senion Community Manager, EDoN and The Alan Turing Institute 7 | 8 | ## Resources 9 | 1. [CC4: slides](https://github.com/alan-turing-institute/ds-ai-educators-programme/tree/main/2022/cc8-making-learning-memorable)
10 | 2. [HackMD](https://hackmd.io/zFu59NY8S8-l3mcoQnwZFw)
11 | 12 | ## Recordings 13 | [CC4 recording](https://youtu.be/TpQfIRe_H7k)
14 | [CC4 Zoom chat.txt](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11679229/CC4.Zoom.chat.txt) 15 | 16 | 17 | -------------------------------------------------------------------------------- /2023/cc5-embedding-ethics-the-background/ReadME.md: -------------------------------------------------------------------------------- 1 | # CC5: Embedding ethics: the background 2 | 3 | ## Speakers 4 | - Mhairi Aitken, Ethics Fellow, The Alan Turing Institute 5 | - Janis Wong, Senior Research Associate, The Alan Turing Institute 6 | 7 | ## Resources 8 | 1. [Janis Wong - slides.pptx](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11685770/Janis.Wong.-.slides.pptx)
9 | 2. [HackMD](https://hackmd.io/0PJTIjlKQsGHM3LzRKbIGg)
10 | 11 | ## Recordings 12 | [CC5 Zoom chat.txt](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11679266/CC5.Zoom.chat.txt)
13 | [CC5 recording](https://youtu.be/3I07Zli2b2o) 14 | 15 | -------------------------------------------------------------------------------- /2023/cc6-embedding-ethics-the-practicals/ReadME.md: -------------------------------------------------------------------------------- 1 | # CC6: Embedding ethics: let's get practical 2 | 3 | ## Speakers 4 | - Dr Janis Wong, Senior Research Associate, The Alan Turing Institute 5 | - Dr Mona Jaber, Lecturer, QMUL 6 | - Dr Richard Clegg, Lecturer, QMUL 7 | 8 | ## Resources 9 | 1. [Embedding ethics pt 2.pptx](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/12025882/Embedding.ethics.pt.2.pptx)
10 | 2. [HackMD](https://hackmd.io/YnCGCwvfTqmFS3C6CSAJvQ)
11 | 12 | ## Recordings 13 | [CC6 recording](https://youtu.be/QX4T6d-2OEM)
14 | 15 | -------------------------------------------------------------------------------- /2023/cc8-collaborative-development-and-delivery-of-teaching-materials/ReadME.md: -------------------------------------------------------------------------------- 1 | # CC8: Collaborative development and delivery of teaching materials 2 | 3 | ## Speakers 4 | - Ayesha Magill, Training Officer, The Alan Turing Institute 5 | - Samantha Ahern, Senior Digital Research Trainer, UCL 6 | - Claudia Fischer, Postdoctorial Research Associate, The Alan Turing Institute 7 | - Luke Kaye, Student, Newcastle University 8 | 9 | ## Resources 10 | 1. [HackMD](https://hackmd.io/0SobK4JVT3CpLi7fF1Sx4w)
11 | 12 | ## Recordings 13 | [CC8 recording](https://youtu.be/tI-YVtmxG0w)
14 | -------------------------------------------------------------------------------- /2023/cc9-working-together-to-embed-data-science-across-disciplines/ReadME.md: -------------------------------------------------------------------------------- 1 | # CC9: Working together to embed data science across disciplines 2 | 3 | ## Speakers 4 | - Dr Serge Sharoff, Professor of Language Technology, University of Leeds 5 | - Dr Eilis Hannon, Senior Research Fellow, University of Exeter 6 | 7 | ## Resources 8 | 1. [Working together to embed data science across disciplines.pptx](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/12026081/Working.together.to.embed.data.science.across.disciplines.pptx)
9 | 2. [HackMD](https://hackmd.io/JNE4HEDwT5KSE5flMkRR1w)
10 | 11 | ## Recordings 12 | [CC9 recording](https://youtu.be/wtufgkLSfSs)
13 | -------------------------------------------------------------------------------- /2023/intro-and-housekeeping-slides/ReadME.md: -------------------------------------------------------------------------------- 1 | ## All housekeeping and introdocutory slides can be found here: 2 | 3 | [Week six.pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11679343/Week.six.pdf) - Embedding ethics into teaching: the background
4 | [Week five.pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11679345/Week.five.pdf) - Making Learning Memorable
5 | [Week four.pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11679346/Week.four.pdf) - Post-pandemic teaching: what does it look like?
6 | [Week three.pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11679347/Week.three.pdf) - The Challenges of Teaching DS and AI
7 | [Week two.pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11679348/Week.two.pdf) - Identifying Learner Needs
8 | [Week one.pdf](https://github.com/alan-turing-institute/ds-ai-educators-programme/files/11679349/Week.one.pdf) - Carpentries Pedagogy Session
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Affirmer understands and acknowledges that Creative Commons is not a 120 | party to this document and has no duty or obligation with respect to 121 | this CC0 or use of the Work. 122 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # The Data Science and AI Educators' Programme 2023 2 | 3 | Welcome to the second run of the Data Science and AI Educators' Programme. 4 | Here, you will find all information, resources and relevant materials concerning the programme. They have been developed openly to be used, downloaded and amended as you need. 5 | 6 | | Week | Session(s) | Time | Date | Slides | Recordings | Collaborative document | 7 | | ----------| ------------------------------| --------| -------------| -------| -----------------|-------------------- | 8 | | 1 | Pedagogy session 1 and 2 | 9am - 12:30pm (GMT+1) | Wednesday 3 May/Thursday 4 May | [All slides](https://github.com/alan-turing-institute/ds-ai-educators-programme/tree/main/2023/carpentries-pedagogy-week-1) | [Day 1](https://youtu.be/I09LVHs3zK4)
[Day 2](https://youtu.be/F9rZvTPCSFk) | [Etherpad document](https://pad.carpentries.org/2023-05-03-ATI) | Complete | 9 | | 2 | CC1: Identifying learner needs | 10:30 - 12:00 (GMT+1) | Thursday 11 May | [Slides](https://github.com/alan-turing-institute/ds-ai-educators-programme/blob/main/2023/cc1-identifying-learner-needs/README.md) | [CC1 recording](https://youtu.be/jFnC6SnAKU8) | [Miro Board](https://miro.com/app/board/uXjVMKqctcE=/)
[HackMD](https://hackmd.io/cxvp9Up_Qd-X5XYn-cEsEg) | Complete | 10 | | 3 | CC2: Challenges of teaching DS and AI | 13:30 - 15:00 (GMT+1) | Wednesday 17 May | n/a | [CC2 recording](https://youtu.be/FSS5dY2-XA4) | [HackMD](https://hackmd.io/x03xAVgBQnCPTvEBYtVCfQ) | Complete | 11 | | 4 | CC3: Post-pandemic teaching: what does it look like? | 13:30 - 15:00 (GMT+1) | Wednesday 24 May | | [CC3 recording](https://youtu.be/wCPulHjzKO4) | [HackMD](https://hackmd.io/2CwAH3cnQMCeSG8rQDexVA) | 12 | | 5 | CC4: Making learning memorable | 13:30 - 15:00 (GMT+1) | Wednesday 31 May | [Slides](https://github.com/alan-turing-institute/ds-ai-educators-programme/tree/main/2022/cc8-making-learning-memorable) | [CC4 recording](https://youtu.be/TpQfIRe_H7k) | [HackMD](https://hackmd.io/zFu59NY8S8-l3mcoQnwZFw) | Complete | 13 | | 6 | CC5: Embedding ethics into teaching: the background | 13:30 - 15:00 (GMT+1) | Wednesday 7 June | [Slides](https://github.com/alan-turing-institute/ds-ai-educators-programme/blob/main/2023/cc5-embedding-ethics-the-background/ReadME.md) | [CC5 recording](https://youtu.be/3I07Zli2b2o) | [HackMD](https://hackmd.io/0PJTIjlKQsGHM3LzRKbIGg) | Complete | 14 | | 7 | CC7: Embedding ethics into teaching: let's get practical | 13:30 - 15:00 (GMT+1) | **Wednesday 21 June** |[Slides](https://github.com/alan-turing-institute/ds-ai-educators-programme/tree/main/2023/cc6-embedding-ethics-the-practicals) |[CC7 recording](https://youtu.be/QX4T6d-2OEM) | [HackMD](https://hackmd.io/YnCGCwvfTqmFS3C6CSAJvQ) | Complete | 15 | | 8 | CC6: Assessment and feedback | Asynchronous | **w/c 12 June** | n/a | n/a | [HackMD](https://hackmd.io/N_dhTEebSkS6MjZeEABhmQ) | Complete | 16 | | 9 | CC8: Collaborative development and delivery of teaching materials | 13:30 - 15:00 (GMT+1) | Wednesday 28 June | | [CC8 recording](https://youtu.be/tI-YVtmxG0w) | [HackMD](https://hackmd.io/FnFm5SpvS7-OjXnXSf_Cug) | Complete | 17 | | 10 | CC9: Working together to embed data science across disciplines | **10:30 - 12:00 (GMT+1)** | Wednesday 5 July | [Slides](https://github.com/alan-turing-institute/ds-ai-educators-programme/tree/main/2023/cc9-working-together-to-embed-data-science-across-disciplines) | [CC9 recording](https://youtu.be/wtufgkLSfSs) | [HackMD](https://hackmd.io/JNE4HEDwT5KSE5flMkRR1w) | Complete | 18 | | 11 | CC10: Making teaching relevant to real-world problems | 13:30 - 15:00 (GMT+1) | Wednesday 12 July | [Slides](https://github.com/alan-turing-institute/ds-ai-educators-programme/tree/main/2023/cc10-making-teaching-relevant-to-real-world-problems) | [CC10 recording](https://youtu.be/iC6z5nHop3Y) | [HackMD](https://hackmd.io/tjH4C-gnQLKS3F9ClWLMJw) | Complete | 19 | | G | Graduation 1 | 11:00 - 12:00 (GMT+1) | Thursday 13 July | | | [HackMD](https://hackmd.io/4W5uyUieQ4KGp1A44cUYKQ) | Complete | 20 | | G | Graduation 2 |15:00 - 16:00 (GMT+1) | Tuesday 18 July | | |[HackMD](https://hackmd.io/_SyJdNqwQ2aGSJJzxL3rHA) | Complete | 21 | | G | Graduation 3 | 12:00 - 13:00 (GMT+1) | Wednesday 19 July | | |[HackMD](https://hackmd.io/k-7c_r7KQWimeIfVNOQsKQ) | Complete | 22 | 23 | All training materials will be uploaded into the relevant folder as soon as possible after the sessions have taken place.

24 | Content from the inaugural run of the Data Science and AI Educators' Programme, including course recordings and materials, can be found in the [2022 folder](https://github.com/alan-turing-institute/ds-ai-educators-programme/tree/main/2022). 25 | 26 | 27 | ## DOI 28 | 29 | [![DOI](https://zenodo.org/badge/490649123.svg)](https://zenodo.org/badge/latestdoi/490649123) 30 | 31 | -------------------------------------------------------------------------------- /code-of-conduct.md: -------------------------------------------------------------------------------- 1 | # Code of Conduct 2 | 3 | We value the participation of every member of our community and want to ensure that every contributor has an enjoyable and fulfilling experience. 4 | Therefore, everyone who participates in the Data Science and AI Educators' Programme is expected to show respect and courtesy to other community members at all times. 5 | 6 | All project members are dedicated to a ***harassment-free experience for everyone***, regardless of gender, gender identity and expression, sexual orientation, disability, physical appearance, body size, race and heritage, age or religion. **We do not tolerate harassment by and/or of members of our community in any form**. 7 | 8 | We are particularly motivated to support new and/or anxious collaborators, people who are looking to learn and develop their skills, and anyone who has experienced discrimination in the past. 9 | 10 | To make clear what is expected, we ask all members of the community to conform to the following Code of Conduct. 11 | 12 | * [1 Introduction](#1-introduction) 13 | * [2 Code of Conduct](#2-code-of-conduct) 14 | * [2.1 Expected Behaviour](#21-expected-behaviour) 15 | * [2.2 Unacceptable Behaviour](#22-unacceptable-behaviour) 16 | * [2.3 Consequences of Unacceptable Behaviour](#23-consequences-of-unacceptable-behaviour) 17 | * [2.4 Feedback](#24-feedback) 18 | * [3 Incident Reporting Guidelines](#3-incident-reporting-guidelines) 19 | * [3.1 Contact points](#31-contact-points) 20 | * [3.2 Alternate contact points](#32-alternate-contact-points) 21 | * [3.3 What to do if someone is in physical danger](#33-what-to-do-if-someone-is-in-physical-danger) 22 | * [3.4 Code of Conduct Enforcement](#34-code-of-conduct-enforcement) 23 | * [4 Enforcement Manual](#4-enforcement-manual) 24 | * [4.1 The Code of Conduct Committee](#41-the-code-of-conduct-committee) 25 | * [4.2 Urgent Situations: Acting Unilaterally](#42-urgent-situations-acting-unilaterally) 26 | * [4.3 Less-Urgent Situations](#43-less-urgent-situations) 27 | * [4.4 Resolutions](#44-resolutions) 28 | * [4.5 Conflicts of Interest](#45-conflicts-of-interest) 29 | * [5 Acknowledgements](#5-acknowledgements) 30 | 31 | ## 1 Introduction 32 | 33 | The Data Science and AI Educators' Programme is a community-oriented project. 34 | We value the involvement of everyone in the community. 35 | We are committed to creating a friendly and respectful place for learning, teaching and contributing. 36 | All participants in online communications (or in-person events) are expected to show respect and courtesy to others at all times. 37 | 38 | To make clear what is expected, everyone participating in activities associated with the Data Science and AI Educators' Programme is required to conform to this Code of Conduct. 39 | This Code of Conduct applies to all spaces managed by the Data Science and AI Educators' Programme Team including, but not limited to, in-person focus groups and workshops, and communications online via GitHub, Slack or email. 40 | 41 | Ayesha Dunk, a training officer at the Alan Turing Institute, is responsible for enforcing the Code of Conduct. 42 | She can be contacted by emailing [adunk@turing.ac.uk](mailto:adunk@turing.ac.uk). 43 | You may contact [Mishka Nemes](mailto:mnemes@turing.ac.uk) or [Malvika Sharan](mailto:msharan@turing.ac.uk) if you would prefer not to contact Ayesha. 44 | 45 | Reports may be reviewed by other members of the core development team, unless there is a conflict of interest, and will be kept confidential. 46 | 47 | ## 2 Code of Conduct 48 | 49 | The Data Science and AI Educators' Programme team are dedicated to providing a welcoming and supportive environment for all people, regardless of background or identity. 50 | As such, we do not tolerate behaviour that is disrespectful to our community members or that excludes, intimidates, or causes discomfort to others. 51 | We do not tolerate discrimination or harassment based on characteristics that include, but are not limited to: gender identity and expression, sexual orientation, disability, physical appearance, body size, citizenship, nationality, ethnic or social origin, pregnancy, familial status, veteran status, genetic information, religion or belief (or lack thereof), membership of a national minority, property, age, education, socio-economic status, technical choices, and experience level. 52 | 53 | Everyone who participates in the Data Science and AI Educators' Programme activities is required to conform to this Code of Conduct. 54 | This Code of Conduct applies to all spaces managed by the Data Science and AI Educators' Programme Team including, but not limited to, in-person focus groups and workshops, and communications online via GitHub, Slack or email. 55 | By participating, contributors indicate their acceptance of the procedures by which the Data Science and AI Educators' Programme Team resolves any Code of Conduct incidents, which may include storage and processing of their personal information. 56 | 57 | ### 2.1 Expected Behaviour 58 | 59 | We are confident that our community members will together build a supportive and collaborative atmosphere at our events and during online communications. 60 | The following bullet points set out explicitly what we hope you will consider to be appropriate community guidelines: 61 | 62 | * **Be respectful of different viewpoints and experiences**. Do not engage in homophobic, racist, transphobic, ageist, ableist, sexist, or otherwise exclusionary behaviour. 63 | * **Use welcoming and inclusive language**. Exclusionary comments or jokes, threats or violent language are not acceptable. Do not address others in an angry, intimidating, or demeaning manner. Be considerate of the ways the words you choose may impact others. Be patient and respectful of the fact that English is a second (or third or fourth!) language for some participants. 64 | * **Do not harass people**. Harassment includes unwanted physical contact, sexual attention, or repeated social contact. Know that consent is explicit, conscious and continuous, not implied. If you are unsure whether your behaviour towards another person is welcome, ask them. If someone tells you to stop, do so. 65 | * **Respect the privacy and safety of others**. Do not take photographs of, or record others without their permission. Do not share other participant’s personal experiences without their express permission. Note that posting (or threatening to post) personally identifying information of others without their consent ("doxing") is a form of harassment. 66 | * **Be considerate of others’ participation**. Everyone should have an opportunity to be heard. In update sessions, please keep comments succinct so as to allow maximum engagement by all participants. Do not interrupt others on the basis of disagreement; hold such comments until they have finished speaking. 67 | * **Don’t be a bystander**. If you see something inappropriate happening, speak up. If you don't feel comfortable intervening but feel someone should, please feel free to ask a member of the Data Science and AI Educators' Programme team for support. 68 | * As an overriding general rule, please **be intentional in your actions and humble in your mistakes**. 69 | 70 | All interactions should be professional regardless of platform: either online or in-person. 71 | See [this explanation of the four social rules](https://www.recurse.com/manual#sub-sec-social-rules) - no feigning surprise, no well-actually's, no back-seat driving, no subtle -isms - for further recommendations of inclusive behaviours. 72 | 73 | ### 2.2 Unacceptable Behaviour 74 | 75 | Examples of unacceptable behaviour by the Data Science and AI Educators' Programme community members at any event or on any platform include: 76 | 77 | * written or verbal comments which have the effect of excluding people on the basis of membership of any specific group 78 | * causing someone to fear for their safety, such as through stalking, following, or intimidation 79 | * violent threats or language directed against another person 80 | * the display of sexual or violent images 81 | * unwelcome sexual attention 82 | * nonconsensual or unwelcome physical contact 83 | * sustained disruption of talks, events or communications 84 | * insults or put downs 85 | * sexist, racist, homophobic, transphobic, ableist, or exclusionary jokes 86 | * excessive swearing 87 | * incitement to violence, suicide, or self-harm 88 | * continuing to initiate interaction (including photography or recording) with someone after being asked to stop 89 | * publication of private communication without consent 90 | 91 | ### 2.3 Consequences of Unacceptable Behaviour 92 | 93 | Participants who are asked to stop any inappropriate behaviour are expected to comply immediately. 94 | This applies to all events and platforms for the Data Science and AI Educators' Programme, either online or in-person. 95 | If a participant engages in behaviour that violates this Code of Conduct, any member of the the Data Science and AI Educators' Programme team may warn the offender, ask them to leave the event or platform (without refund), or impose any other appropriate sanctions (see the [enforcement manual](#4-enforcement-manual) for details). 96 | 97 | ### 2.4 Feedback 98 | 99 | This Code of Conduct is not intended as a static set of rules by which everyone must abide. 100 | Rather, you are invited to make suggestions for updates or clarifications by contacting Ayesha Dunk at [adunk@turing.ac.uk](mailto:adunk@turing.ac.uk) or by making a pull request to this document on GitHub. 101 | 102 | ## 3 Incident Reporting Guidelines 103 | 104 | ### 3.1 Contact points 105 | 106 | If you feel able to, please contact Ayesha Dunk by email at [adunk@turing.ac.uk](mailto:adunk@turing.ac.uk). 107 | 108 | ### 3.2 Alternate contact points 109 | 110 | You may contact [Mishka Nemes](mailto:mnemes@turing.ac.uk) or [Malvika Sharan](mailto:msharan@turing.ac.uk) if you would prefer not to contact Ayesha. 111 | 112 | ### 3.3 What to do if someone is in physical danger 113 | 114 | If you believe someone is in physical danger, please contact the appropriate emergency responders. 115 | 116 | ### 3.4 Code of Conduct Enforcement 117 | 118 | A detailed enforcement policy is available in the Enforcement Manual below. 119 | 120 | ## 4 Enforcement Manual 121 | 122 | This is the enforcement manual followed by the Turing Way project research team. 123 | It's used when they respond to an issue to make sure they're consistent and fair. As such, the Data Science and AI Educators' Programme team will use this manual. 124 | Enforcement of the Code of Conduct should be respectful and not include any harassing behaviours. 125 | 126 | ### 4.1 The Code of Conduct Committee 127 | 128 | The Code of Conduct committee is: 129 | 130 | * Ayesha Dunk: adunk@turing.ac.uk 131 | * Mishka Nemes: mnemes@turing.ac.uk 132 | * Malvika Sharan: msharan@turing.ac.uk 133 | 134 | As the community grows, we will seek to build a larger committee including members outside of the core development team. 135 | 136 | ### 4.2 Urgent Situations: Acting Unilaterally 137 | 138 | If the incident involves physical danger, or involves a threat to anyone's safety (e.g. threats of violence), any member of the community may -- and should -- act unilaterally to protect the safety of any community member. 139 | This can include contacting law enforcement (or other local personnel) and speaking on behalf of the Data Science and AI Educators' Programme team. 140 | 141 | If the act is ongoing, any community member may act immediately, before reaching consensus, to diffuse the situation. 142 | In ongoing situations, any member may at their discretion employ any of the tools available in this enforcement manual, including bans and blocks online, or removal from a physical space. 143 | 144 | In situations where an individual community member acts unilaterally, they must inform Ayesha Dunk as soon as possible, and report their actions for review within 24 hours. 145 | 146 | ### 4.3 Less-Urgent Situations 147 | 148 | Upon receiving a report of an incident, the CoC committee will review the incident and determine, to the best of their ability: 149 | 150 | - whether this is an ongoing situation 151 | - whether there is a threat to anyone's physical safety 152 | - what happened 153 | - whether this event constitutes a Code of Conduct violation 154 | - who, if anyone, was the bad actor 155 | 156 | This information will be collected either in person or in writing. 157 | The CoC committee will provide a written summary of the information surrounding the incident. 158 | All participants will be anonymised in the summary report, referred to as "Community Member 1", "Community Member 2", or "Research Team Member 1". 159 | The "de-anonymising key" will be kept in a separate file and only accessed to link repeated reports against the same person over time. 160 | 161 | The CoC committee will aim to have a resolution agreed upon within one week. 162 | In the event that a resolution can't be determined in that time, a member of the CoC committee will respond to the reporter(s) with an update and projected timeline for resolution. 163 | 164 | ### 4.4 Resolutions 165 | 166 | The CoC committee will seek to agree on a resolution by consensus of all members investigating the report in question. 167 | If the committee cannot reach consensus and deadlocks for over a week, Ayesha Dunk, Mishka Nemes or Malvika Sharan, will break the tie. 168 | 169 | Possible responses may include: 170 | 171 | * A mediated conversation or agreement between the impacted community members. 172 | * A request for a verbal or written apology, public or private, from a community member. 173 | * A public announcement clarifying community responsibilities under the Code of Conduct. 174 | * Nothing, if the issue reported is not a violation or outside of the scope of this Code of Conduct. 175 | * A private in-person conversation between a member of the research team and the individual(s) involved. 176 | In this case, the person who has the conversation will provide a written summary for record keeping. 177 | * A private written reprimand from a member of the research team to the individual(s) involved. 178 | In this case, the research team member will deliver that reprimand to the individual(s) over email, cc'ing Ayesha Dunk for record keeping. 179 | * A public announcement of an incident, ideally in the same venue that the violation occurred (i.e. on the listserv for a listserv violation; GitHub for a GitHub violation, etc.). 180 | The committee may choose to publish this message elsewhere for posterity. 181 | * An imposed "time out" from online spaces. 182 | Ayesha Dunk will communicate this "time out" to the individual(s) involved. 183 | * A permanent or temporary ban from some or all of the Data Science and AI Educators' Programme spaces (GitHub, online events, Slack etc). 184 | The Data Science and AI Educators' Programme team will maintain records of all such bans so that they may be reviewed in the future, extended to a Code of Conduct safety team as it is built, or otherwise maintained. 185 | If a member of the community is removed from an event they will not be reimbursed for any part of the event that they miss. 186 | 187 | Once a resolution is agreed upon, but before it is enacted, a member of the CoC committee will contact the original reporter and any other affected parties and explain the proposed resolution. 188 | The CoC committee member will ask if this resolution is acceptable, and must note feedback for the record. 189 | However, the CoC committee is not required to act on this feedback. 190 | 191 | ### 4.5 Conflicts of Interest 192 | 193 | In the event of any conflict of interest such that the team members named above are not able to evaluate or enforce the reported violation, Matt Foreshaw will take their place. 194 | 195 | ## 5 Acknowledgements 196 | 197 | This code is adapted from the [Turing Way Code of Conduct] (https://github.com/alan-turing-institute/the-turing-way/blob/main/CODE_OF_CONDUCT.md), [Carpentries Code of Conduct](https://docs.carpentries.org/topic_folders/policies/code-of-conduct.html) with sections from the [Alan Turing Institute Data Study Group Code of Conduct](https://docs.google.com/document/d/1iv2cizNPUwtEhHqaezAzjIoKkaIX02f7XbYmFMXDTGY/edit). 198 | All are used under the creative commons attribution license. 199 | 200 | The Carpentries Code of Conduct was adapted from guidelines written by the [Django Project](https://www.djangoproject.com/conduct/enforcement-manual/), which was itself based on the [Ada Initiative template](http://geekfeminism.wikia.com/wiki/Conference_anti-harassment/Responding_to_reports) and the [PyCon 2013 Procedure for Handling Harassment Incidents](https://us.pycon.org/2013/about/code-of-conduct/harassment-incidents/). 201 | Contributors to the the initial document are Adam Obeng, Aleksandra Pawlik, Bill Mills, Carol Willing, Erin Becker, Hilmar Lapp, Kara Woo, Karin Lagesen, Pauline Barmby, Sheila Miguez, Simon Waldman, and Tracy Teal. 202 | In 2018, the Code of Conduct was revised to add a summary, straightforward examples of both beneficial and unwanted behaviors, and evaluating intent. 203 | Reporting guidelines were also revised to include alternate contact points and a reporting form with the procedure was added. 204 | Contributors of these revised documents are Ethan White, Kari L. Jordan, Karin Lagesen, Malvika Sharan, Samantha Ahern, and Simon Waldman. 205 | Additional language was added by Otter Tech from the PyCon U.S. 2018 Code of Conduct (licensed CC BY 3.0). 206 | 207 | The Turing Institute Data Study Group Code of Conduct was heavily adapted from the [Citizen Lab Summer Institute 2017 Code of Conduct](https://citizenlab.ca/summerinstitute/codeofconduct.html) and used under a CC BY 2.5 CA license. 208 | Citizen Lab based their Code of Conduct on the [xvzf Code of Conduct](http://xvzf.io/#coc), the [Contributor Covenant](http://contributor-covenant.org/), the [Django Code of Conduct and Reporting Guide](https://www.djangoproject.com/conduct/) and we are also grateful for [this guidance from Ada Initiative](http://geekfeminism.wikia.com/wiki/Conference_anti-harassment/Responding_to_reports). 209 | 210 | We really appreciate the work that all of the communities linked above have put into creating such a well-considered process. 211 | 212 | This Code of Conduct is licensed under a [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/) (CC BY 4.0 CA) license which means you are free to share and adapt the work so long as the attribution to Kirstie Whitaker and the Turing Way community is retained, along with the attribution to the Carpentries, the Alan Turing Institute Data Study Group organising team, Citizen Lab and the other resources. 213 | --------------------------------------------------------------------------------