---
# System prepended metadata

title: 'Data Science and AI Educators'' Programme: Peer-mentoring notes'
tags: [DS-AI-Educators'-Programme, peer-mentoring meeting]

---

Data Science and AI Educators' Programme: Peer-mentoring notes
===

###### tags: `peer-mentoring meeting` `DS-AI-Educators'-Programme`

:::info
- **Call time and day**: Mixed
- **Meeting chair**: Everyone
- **Meeting note-taker** Everyone
- **Meeting time-keeper** Everyone
- **Call joining link**: [Here](https://teams.microsoft.com/l/meetup-join/19%3ameeting_NzM3ZDZjYmMtNTFkNC00OTNhLTk3NjUtNjg1OGU0ZjRlYmM1%40thread.v2/0?context=%7b%22Tid%22%3a%228370cf14-16f3-4c16-b83c-724071654356%22%2c%22Oid%22%3a%22a1ab481d-50c0-47e3-a13b-834e9ace3659%22%7d)


:::

The peer-mentoring sessions are an opportunity for you to discuss your learning, any challenges you are currently experiencing and any challenges you might face moving forward. We encourage you to use these sessions as a safe space to share best practice and support one another in your development as Data Science and AI educators.

To make the most of this opportunity, it is important that you meet weekly. Please try to find a mutually convenient time each week to meet for between 45 minutes and 1 hour. It may be useful to assign a meeting chair, note-taker and time-keeper. You can use the blue box, above, to take note of who will fulfill these roles.

Below, you will find a suggested structure for each week's call. There may be sessions where you naturally mentor one another, without the need for a structure. This is perfectly fine - the structure is there as a prompt, should you need to use it.

**Table of contents**

[TOC]


## Week 1 : w/c 16 May 2022

**Roll call**

Kieran Baker
Andy Maclachlan
Nancy Ruzycki
Martin Goodfellow

### Agenda and Notes for Week 1

- Introductions - get to know each other

Andy - Lecturer in spatial data science and visualisation,CASA, UCL. Classes on geographical Information systems and science + remote sensing 

Nancy - University of Florida, Teaches in materials science and engineering, PhD physics. Has large grants to provide professional development to teachers for data science and AI. Developing curriculum frameworks for the state for K12 programs in data science and AI.

Martin - Teaching Fellow in Computer and Information Sciences at the University of Strathclyde. Teach classes on Java programming and big data fundamentals, tools and techniques. Taught CS to students from primary school to postgraduate level.

Kieran - PhD Student studying Statistics at King's College London. Have taught as a teaching assistant on various undergraduate courses at KCL, and always loved teaching having been working as a maths tutor since I was 16.

- Tell your peers about yourself - where you work/why you applied to the programme etc.
  - Martin:
      - To learn the best techniques for teaching data science and AI.
     
- Set some personal goals: what do you hope to achieve through participation in this programme? Where would you like to be by the end of this programme?
  - Kieran:
      - Better understanding of best practice when teaching Data Science and AI related courses
      - How best to account for a diverse learning base both when designing and teaching courses.
      - Practically where can we host courses that we develop, are there any open source platforms that are best to use?
  - Andy :
      - Reflect and improve on current teaching practice
      - Tools to reduce attainment gaps 
  - Martin:
      - Learn best techniques to teaching data science and AI (including ideas for engaging lessons)
      - Get involved in more research projects for data science and AI education and find potential collaborators in this area
      - Learn from other participants in the course
      - How to effectively teach students from different backgrounds in a similar way and ensuring they leave with the same level of understanding while
        putting in the same amount of effort

  - Nancy:
     - improve practices for teaching data science and AI
     - Gain new ideas to implement in the PD of teachers
     - Meet like minded persons to create engaging activities to teach lower school students about AI and Data Science
    
- What are your plans to take this programme/new learning into your own community?
  - Nancy 
      - Take into my own teaching at the university, take into work with teacher PD

  - Kieran:
      - I would like to design my own courses and learning materials in Statistics and Data Science, both for students in HE, but also younger students going through highschool - it's not a subject widely talked about and exposing younger people to some of the ideas in DS might inspire them to target a career in the field.

  - Martin:
    - Incorporate what I've learned into my teaching
    - Share with colleagues in my department as well as other departments in the university
    - Share through the Scottish Informatics and Computer Science Alliance (SICSA) 

  -  Andy 
      -  Integrate methods / tools/  ideas into current modules where possible. Can also make changes at programme level if appropriate.



- What teaching or 'educator' experience do you have and how do you hope the programme will add to this experience?
  - Nancy 
      - multiple years (10) at the university and working with developing of curriculum and PD. Hope to add new tools and techniques for best practices

  - Kieran:
      - TA in undergraduate courses at KCL & Tutoring GCSE/A Level students
  - Martin:
      - Ran coding clubs in Scotland for 8-17 years olds backed with Scottish Government funding
      - Worked with Glasgow City Council running these coding clubs in libraries
      - Wrote a couple of books on learning Python programming for young people
      - Worked in Strathclyde University for almost 5 years teaching a variety of classes and developing new classes and degrees
      - Hope to learn new techniques for teaching that I can use to enhance my teaching and give the students the best possible learning experience

  - Andy 
      - 7 years of teaching a diverse range of modules with some sort of geographical focus. I hope this will challenge my views on teaching and develop my practice. 

_**Meeting logistics & Reminders**_

- Decide on a time and a day that works to meet every week. If you cannot find a mutual day every week (and in advance), agree to co-ordinate on a week-by-week basis the best time to meet. Will you set up a poll? Who will co-odinate this?

Next meeting will be at 3pm on Thursday 26th May

_**Task after this call**_

- If you haven't done so already, complete the pre-programme survey. Keep a record of your answers so that you can reflect back on these at the end of the programme.

## Week 2 : w/c 23 May 2022

**Roll call**

- Kieran
- Nancy
- Martin
- Andrew
- 

### Agenda and Notes for Week 2

Quick check in - how are you all doing? 

Spend some time reflecting on the learning from Week 1 (Carpentries pedagogy sessions). Think about the following questions as prompts for discussion:
  - What did you learn that you didn't know before?
    - Andy:
      -  Just reflecting on how people interpret teaching material as opposed to deciding to teach a topic and doing it how i would expect. The beginner, novice and expert sections were useful on this.
    - Nancy:
      -  I have taken multiple cartpentry courses and like them. They often start at a low level of programming and then scale quickly to higher level data analysis. I like being able to see how other people approach how to teach the content. 
    - Kieran:
      -  I have learn't to appreciate the depth of consideration needed for the psycological aspects of learning, and how to prevent congitive loading and helping students retain knowledge using knowledge graphs and other techniques.
    - Miracle:
      -  [TAKE NOTES HERE]
    - Martin:
      -  Learning about the carpentries. It was also really useful to see how agile processes could be used for developing teaching materials.
      
  - Was there anything unusual or interesting that came up during the sessions?
    - Andy:
      - Commonalities about networking, people don't like it or don't know how to do it well especially in relation to teaching that is often individual 
    - Nancy:
      -  Many people are still teaching virtually
    - Kieran:
      -  The struggle to find others to collaborate with on curriculum development - no obvious places to go for funding educational research and development
    - Miracle:
      -  [TAKE NOTES HERE]
    - Martin:
      - There's more education funding opportunities in the UK than I realised but still seems to be hard to find money for educational research.
      
  - Was there a concept that you found challenging? Why?
    - Andy:
      -  No
    - Nancy:
      -  not really
    - Kieran:
      -  No
    - Miracle:
      -  [TAKE NOTES HERE]
    - Martin:
      -  Not really but gave me things to think about I hadn't considered before.
      
  - Are there any concrete examples that you could apply in your role as an educator?
    - Andy:
      -  Reducing the amount i talk and increasing the number of tasks that students are completing. Plus the range of tasks - from simple code problem solving to critically reflecting on the content 
    - Nancy:
      -  breaking things down into chunks is something I do, but thinking about the smallest way to chunk is important
    - Kieran:
      -  Using concept maps to show students how I think about problem solving and relate different sections of the courses together
    - Miracle:
      -  [TAKE NOTES HERE]
    - Martin:
      -  Taking agile approaches with other staff to develop new classes

  - Useful resources:
      - https://www.nfer.ac.uk/
      - https://www.imperial.ac.uk/about/leadership-and-strategy/provost/vice-provost-education/the-excellence-fund-for-learning-and-teaching-innovation/
      - https://royalsociety.org/topics-policy/projects/computing-education/
      - https://www.grantsonline.org.uk/news/schools-and-colleges/
      - https://edu.google.com/intl/ALL_uk/

Task: Find the money!

Interesting article from UK Gov on funding in higher education [here](https://commonslibrary.parliament.uk/research-briefings/cbp-7973/)

  - Support through the funding council for teaching fell even before the 2012 reforms and was cut particularly quickly from 2012 to 2015. **The 2021-22 total for teaching is 78% below the 2010-11 figure in real terms.**

## Week 3 : w/c 30 May 2022

**Roll call**

- Martin
- Nancy
-  
- 
-

### Agenda and Notes for Week 3

Quick check in - how are you all doing?

Recap from last week - anyone find any sizable funding opportunities for teaching research in DS and AI?

 - https://commonslibrary.parliament.uk/research-briefings/cbp-7973/
     - Reduced spending on teaching might correlate with lack of funding for pedagogical research?
 - Multiple resources for funding in the US NSF ITest, other NSF funding. Department of Education funding, even Department of Defense funding.
 - [NOTES]
 - [NOTES]

This week, we would like you to focus on the 'Building Skill With Practice' module from Week 1. The session discussed how formative assessment tools can be used to help identify learner misconceptions during a course/lesson/programme etc. 
With your group, please discuss the following and take notes where appropriate. _You should use your own teaching/instructing/educating experience to inform your discussion and give concrete, useful examples where possible._
- Consider a lesson that you have taught (or plan to teach). What potential misconceptions might your learner encounter?
  -  Andy:
      -  that assigning projections and transforming them are different - students often simply reassign a geographic projection and not transform them. Another example is when referring to projections people often ask (and write) is your data projected when this usually means is it in a local (not global) coordinate reference system
  -  Nancy:
      -  I am teaching teachers in python, and they tend to memorize code and try and reuse memorized code rather than thinking first what they want the program to do and then designing code that will work for the program. 
  -  Kieran:
      -  Not realising that $p(X|\theta)$ is exactly the same as $L(\theta|X)$, just taking a different perspective of the function.
  -  Miracle:
      -  [TAKE NOTES HERE]
  -  Martin:
      -  That abstract classes are different from interfaces in Java and situations where they are appropriate.
- How can you ensure that your material and delivery mitigates this misconception?
  -  Andy:
      -  Specific instructions to beginners - using correct terms and not interchanging. However, in this example they do need to be aware of what other people might ask them in industry for example. So using the correct terms whilst making them aware of what they could encounter. 
  -  Nancy:
      -  Building in time for teachers to design code and not just code code. 
  -  Kieran:
      -  Carefully working through explicit examples to show how the same function can be thought of in two different ways, one in which the parameter is known, and the other in which the data is known.
  -  Miracle:
      -  [TAKE NOTES HERE]
  -  Martin:
      -  I give loads of examples of each and situations when to use them. I also give them MCQs on the topic using think pair share for example, what would you use in this situation and then get them to discuss why.
      
- How could you use a formative assessment strategy(such as multiple choice questions) to mitigate this misconception? 
  -  Andy:
      -  Short quiz using st_transform or st_crs and the difference. Same for data in local or geographic coordinate reference systems 
  -  Nancy:
      -  Sometimes I do pre/post tests to allow me to see if they have built the concept.
  -  Kieran:
      -  Questions where the question is set up, and students have to identify the correct likelihood function.
  -  Miracle:
      -  [TAKE NOTES HERE]
  -  Martin:
      -  I could use futher formative assessment to help initiate discussions and to help understand what misconceptions students have and then use it to structure future lessons to help mitigate this.
      
- Again, considering your own experiences and practice, what other examples of formative assessment could you use? Think about how this would apply to a lesson that you plan to teach (or have taught).
  -  Andy:
      -  Individual per student such as submitting report outlines or project proposals that get comments, but can take a lot of resource to mark. Or in person quizzes, such as mentimeter or vevox. One i like is explaining Git and GitHub then assigning students roles and getting them to act out collaborating on a document (with signs for each role). However, this isn't directly formative assessment but they do get live feedback from me. 
  -  Nancy:
      -  We do in class small activities, chats and exit tickets
  -  Kieran:
      -  Taking a question, breaking it down into smaller deductive steps, and using a quiz that runs through each of these steps. This will also help me identify which steps the students are struggling with the most.
  -  Miracle:
      -  [TAKE NOTES HERE]
  -  Martin:
      -  I could add in some example programming exercises presented in an automated marking system similar to Leetcode to give further practice and to help initiate more discussions that will hopefully get rid of the misconceptions. This would help in Java lessons where I teach about multiple inheritance.

_**Task after this call**_

For next week's call, you will be looking at memory and cognitive load in the context of a session/lesson/training that you have led (or participated in). Please bring this teaching material to your next peer-mentoring session. An overview with approximate timings of the session, plus the content covered will suffice.


## Week 4 : w/c 6 June 2022

**Roll call**

- Kieran
- Andy
- Nancy
- 
-

### Agenda and Notes for Week 4

Quick check in - how are you all doing? 

This week, we would like you to focus on the 'Memory and Cognitive Load' module from Week 1. The session discussed the benefits of guided practice and formative assessment, as well as some tips for consolidating content.

With your group, please discuss the following and take notes where appropriate.
- Looking at the materials you have brought with you today, imagine yourself as a learner in this lesson. Is the information presented in short chunks, followed by an opportunity for consolidation of the concept(s) taught (through some kind of formative assessment)? If not, work together to re-jig the session, adding opportunities for consolidation, where possible.
  -  Andy:
      -  There are a few challenges here:
          -  requirement to complete all the material to complete the module
          -  balancing student ability - programmers vs complete beginners
      -  In response:
          -  Break the session into 15 minute sections where each topic is discussed afterwards - allowing advanced students to go ahead if they want
          -  Create decision trees - if you know this then go to section x or if you can pass this quiz go to section x 
  -  Nancy:
      -  yes, there are small projects which build toward larger content goals
      -  Agree on the balancing of student ability how to support all learners on a spectrum of ability
  -  Kieran:
      -  [TAKE NOTES HERE]
  -  Miracle:
      -  [TAKE NOTES HERE]
  -  Martin:
      -  [TAKE NOTES HERE]
- In order to reduce cognitive load on a learner, we can also use a strategy called scaffolding. This introduces small, easily-digestible concepts step-by-step until they reach the final 'learning goal'. How could you scaffold _your_ session to support your learners?
  -  Andy:
      -  See above, the sessions are already in sections which could easily be divided into digestible concepts, but more instructor guidance would be required.
  -  Nancy:
      -  I already block and scaffold for the lessons in programming
  -  Kieran:
      -  [TAKE NOTES HERE]
  -  Miracle:
      -  [TAKE NOTES HERE]
  -  Martin:
      -  [TAKE NOTES HERE]
- How could you incorporate some guided practice into your session? What is the value of guided practice?
  -  Andy:
      -  I sort of do this to a small extent in most cases - i usually talk about an example in a lecture and then in a practical we explore a similar or slightly different question but with a specific research question or aim. This somewhat follows the i do, we do, you do approach but the i do is primarily a lecture and could be more programmatic / student led / collaborative.  
  -  Nancy:
      -  I do the guided practice as well, we use "I do, we do, you do" structure
  -  Kieran:
      -  [TAKE NOTES HERE]
  -  Miracle:
      -  [TAKE NOTES HERE]
  -  Martin:
      -  [TAKE NOTES HERE]

_**Task after this call**_

Before next week, please prepare a short, 5-minute session to deliver to your group. This will be an opportunity to 'teach' and receive feedback from your peers. You can teach any concept you like, providing that, by the end of your 5-minutes, your learners will have grasped the concept! You will each receive feedback on both your delivery _and_ your content, so please ensure that you have started to consider/incoporate pedagogical elements that you have learned so far.
If you would like to pair up to deliver a 10-minute session together, you may.

## Week 5 : w/c 13 June 2022

**Roll call**

- Nancy
- Martin
-  
- 
-

### Agenda and Notes for Week 5

Quick check in - how are you all doing? 

This week, we would like you to focus on the 'Teaching is a Skill' module from Week 1. The session was an opportunity to practice teaching and receive feedback on your delivery. Today, you will repeat the exercise, this time thinking about giving feedback on delivery _and_ content. You should consider elements such as memory and cognitive load, opportunities for assessment as well as the overall delivery.

- Andy
  - [FEEDBACK HERE]
- Nancy
  - Trying to spend more time developing some small chunks of programming to support conceptual development. 
- Kieran
  - ICE - Identification, Calculation and Evaluation: breaking problems down into these stages helps with understanding and problem solving skills. Encouraging them to think about what they have within their mathematical tool box, and what they need to solve problems.
- Miracle
  - [FEEDBACK HERE]
- Martin
  - Think, pair, share.


## Week 6 : w/c 20 June 2022

**Roll call**

- Martin
- Kieran
- Nancy
- Miracle
-

### Agenda and Notes for Week 6

Quick check in - how are you all doing? 

This week, we would like you to focus on last week's Ethics in the Context of Training cohort call.

  - What did you learn that you didn't know before?
    - Andy:
      -  [TAKE NOTES HERE]
    - Nancy:
      -  Learning about the way international students become a stand in for broadening participation as opposed to developing local students 
    - Kieran:
      -  Designing courses flexibly to ensure that the course is accessible to a diverse audience. Important to encourage a safe and open learning space.
    - Miracle:
      -  [TAKE NOTES HERE]
    - Martin:
      -  The concept of ungrading. 
  - Was there anything unusual or interesting that came up during the sessions?
    - Andy:
      -  [TAKE NOTES HERE]
    - Nancy:
      -  The role of assessments in prepartory programs and the ungrading. Also, I agree on the role of finances and personal capital (power) in being able to attain education in this area. 
    - Kieran:
      -  Importance of financial barriers to AI eduction - this is why Open Source courses are so important. Why is it that diversity in UK HE Institutions being driven by international students.
    - Miracle:
      -  [TAKE NOTES HERE]
    - Martin:
      -  Removing barriers for education that might not be so obvious, for example, Internet only being available at specific times of day. Also consideration of removing financial barriers to education.
  - Was there a concept that you found challenging? Why?
    - Andy:
      -  [TAKE NOTES HERE]
    - Nancy:
      -  no
    - Kieran:
      -  [TAKE NOTES HERE]
    - Miracle:
      -  [TAKE NOTES HERE]
    - Martin:
      -  Not particularly just gave me things to think about that aren't always obvious.
  - Are there any concrete examples that you could apply in your role as an educator?
    - Andy:
      -  [TAKE NOTES HERE]
    - Nancy:
      -  making sure to create more accessible ways for people to interact with progamming in a low stakes manner and engaging practices
    - Kieran:
      -  Taking more care in the design of courses to try and maximise accessibility - actively considering this through impact reports.
    - Miracle:
      -  [TAKE NOTES HERE]
    - Martin:
      -  Asking the students about what might impact their studies so we can ensure we are catering for all student needs. We have rules around accessibility, etc., but class lecturers rarely ask the students directly instead we react based on the support we are asked to give by the universities evaluation of students in class. 

## Week 7 : w/c 27 June 2022

**Roll call**

- 
- 
-  
- 
-

### Agenda and Notes for Week 7

Quick check in - how are you all doing?

This week, we would like you to focus on the 'Motivation and Building Positive Learning Environments' module from Week 1. The session focused on aspects such as growth mindset, encouraging participation and creating a positive, safe learning environment.

Today, you're going to think about what has motivated you to become an 'educator' and write a short explanation. This should take about 5 minutes. When you've finished, share it with the group - you can also save this as part of your teaching philosophy for future reference.

- Andy:
  -  [TAKE NOTES HERE]
- Nancy:
  -  [TAKE NOTES HERE]
- Kieran:
  -  [TAKE NOTES HERE]
- Miracle:
  -  [TAKE NOTES HERE]
- Martin:
  -  [TAKE NOTES HERE]

- What do you notice about the motivations you have to teach?
- Is there some diversity amongst your group? Is this a good thing?
- Why would it be important for the learner to embrace their errors?
- Why would it be important for the educator to embrace their errors too?

## Week 8 : w/c 4 July 2022

**Roll call**

- 
- 
-  
- 
-

### Agenda and Notes for Week 8

Quick check in - how are you all doing?

Last week, there was a cohort call panel on **The Challenges of Teaching Data Science and AI**. With your peers, consider discussing the following questions:

- What is the main challenge that you face (or have faced) when teaching Data Science and AI?
  -  Andy:
      -  [TAKE NOTES HERE]
  -  Nancy:
      -  [TAKE NOTES HERE]
  -  Kieran:
      -  [TAKE NOTES HERE]
  -  Miracle:
      -  [TAKE NOTES HERE]
  -  Martin:
      -  [TAKE NOTES HERE]
- Now that you are 8 weeks through the programme, what learning can you take away to help you overcome these challenges? 
  -  Andy:
      -  [TAKE NOTES HERE]
  -  Nancy:
      -  [TAKE NOTES HERE]
  -  Kieran:
      -  [TAKE NOTES HERE]
  -  Miracle:
      -  [TAKE NOTES HERE]
  -  Martin:
      -  [TAKE NOTES HERE]


## Week 9 : w/c 11 July 2022

**Roll call**

- 
- 
-  
- 
-

### Agenda and Notes for Week 9

Quick check in - how are you all doing? 

This week, we are going to think about 'Preparing to Educate'. You will never know everything about your learners. Thinking deeply about them as people will help you to prepare and create the most inclusive environment for everyone. Today you will have two activities:

- Take a moment to imagine a learner who might attend your class/workshop/programme/session etc. What is their background? What problems do they face? What do they have to gain from attending this session? Create a learner profile and share this with your group. How are you going to meet their needs?
  -  Andy:
      -  [TAKE NOTES HERE]
  -  Nancy:
      -  [TAKE NOTES HERE]
  -  Kieran:
      -  [TAKE NOTES HERE]
  -  Miracle:
      -  [TAKE NOTES HERE]
  -  Martin:
      -  [TAKE NOTES HERE]
- Take a moment to think of a learning objective from a workshops/class/session that you have led (or intend to lead).
  -  Suppose a learner has mastered this objective and wanted to try someting more cognitively challenging on the exact same topic. Take some time to brainstorm what objective they could work towards next. Share this with the group.
  -  Andy:
      -  [TAKE NOTES HERE]
  -  Nancy:
      -  [TAKE NOTES HERE]
  -  Kieran:
      -  [TAKE NOTES HERE]
  -  Miracle:
      -  [TAKE NOTES HERE]
  -  Martin:
      -  [TAKE NOTES HERE]
  -  Suppose a learner struggled to meet the specified objective. What might they be missing? How would you support them? Indentify one more fundamental thing the learner needs to be able to do in order to be successful in meeting this objective.
  -  Andy:
      -  [TAKE NOTES HERE]
  -  Nancy:
      -  [TAKE NOTES HERE]
  -  Kieran:
      -  [TAKE NOTES HERE]
  -  Miracle:
      -  [TAKE NOTES HERE]
  -  Martin:
      -  [TAKE NOTES HERE]

## Week 10 : w/c 18 July 2022

**Roll call**

- 
- 
-  
- 
-

### Agenda and Notes for Week 10

Quick check in - how are you all doing?

This week, we are going to think about working with a team/collaboratively to develop training materials (TBC - details to follow soon)

## Week 11 : w/c 25 July 2022

**Roll call**

- 
- 
-  
- 
-

### Agenda and Notes for Week 11

Quick check in - how are you all doing?

This week will be about preparing for the graduation (TBC - details to follow soon)


## Week 12 : w/c 1 August 2022

**Roll call**

- 
- 
-  
- 
-

### Agenda and Notes for Week 12

Quick check in - how are you all doing?

This will be your final week of the programme. Take a look back at the goals you set for yourself at the beginning of the programme. Have you met them? If there are any that you didn't meet, or only partially met, what steps can you take to ensure that you work towards meeting the goal? Can your peers support you in this?

- Andy
  - [TAKE NOTES HERE]
- Nancy
  - [TAKE NOTES HERE]
- Kieran
  - [TAKE NOTES HERE]
- Miracle
  - [TAKE NOTES HERE]
- Martin
  - [TAKE NOTES HERE]