# Connections workshop planning

## Working title - RSE/RDS

:::info
**Lay person blurb:**

Provide an immersive and hands-on learning opportunity about the tasks, responsiblities and type of projects an RSE / RDS would do.

**Target audience**: Year 2 and 3 PhD students (at CDTs/ DTPs connected with Turing

**Audience Capacity**: 40 students in groups of 5 = 8 groups

**Purpose of the workshop**: Attendees will leave the workshop with a broader understanding of the tasks, responsibilities and project types of software engineers and data scientists in the research environment. They will also engage in practical exercises akin to the challenges handled by these groups.

**Pre-requisites**: having worked with research data and intermediate programming experience (to define specifically once the workshop outline is drafted)

**Trainer profile**: Current Research Software Engineer or Research Data Scientist working at The Alan Turing Institute.

**Mode of delivery**: In-person at The Alan Turing Institute, London office

**Workshop length** 2 days, 10-13h.
:::

## Workshop objectives

- introduce learners to concepts / key skills and tasks required in a RSE / RDS role
- expose the learners to different types of activities and project tasks (_ensure variety of projects to allow the learners identify themselves with at least one project_)
- gain hands-on experience in working with a challenge owner
- develop/consolidate/reflect on RSE / RDS skills through applied group project work
- reflective exercise of personal skills and attributes with regards to a RSE skillset
- define pathways for transitioning to an RSE / RDS role following a PhD

## Learning outcomes

- To identify and articulate the key tasks and skills within a RSE / RDS role
- To be able to exemplify project types, and to make links between personal skillset and the RSE / RDS portfolio of projects
- To act as a RSE / RDS in response to a challenge / project, and to present the process and the findings to peers
- To collaborate with peers and the challenge owner throughout the RSE / RDS process
- To review and comment on the findings and presentations from the other groups
- To be able to define pathways for transitioning to a RSE / RDS role following a PhD

## Pedagogical considerations

:::info
**Workshop Planning Guidance:**
- When designing the workshops, there are clear learning objectives to work backwards from.
- Any practical skills taught are clear for the ‘educator’ and communicated to the learner.
- Consider the diversity of learners and be sure to represent diverse groups in all session materials (i.e. protected characteristics and, research areas)
- The workshops have clear opportunities for learner assessment. E.g. multiple-choice questions/Parson’s problems/fill-in-the-blank problems/practical tasks/Q and A sessions of carefully curated questions.
- Any practical activities and challenges are appropriate to the learning and have considered the learners’ cognitive loads.
- - Present short chunks of information, to avoid cognitive overload for the learner, followed by short activities or breaks. Provide examples from your work to compliment concepts discussed (where possible).
- Consider common misconceptions, particularly of more complex concepts, and try to address these during the session(s).
- Present information clearly and concisely but try to embed variation in your session. Pictures, videos, examples and interactive sessions can make all the difference.
- The workshops have a clear flow.

**Delivering the workshop:**
- Keep a steady pace. Nothing too slow or too quick.
- Keep screen-sharing tidy: only have necessary tabs open.
- Set expectations at the beginning – ensure your learners know how to communicate with you. Is it via a button? Do they raise their hand?
- Communicate the learning objectives at the beginning of each session.
- Turn off notifications or alerts on your computer (e.g. MS Teams, Slack, Zoom etc.)
- Talk with passion. The more positive and excited you are about the information you are presenting, the more people will pay attention to you.
:::

:::info
**Reproducibility considerations:**
- There are educator notes to cover the teaching element of all modules. This might look like (but not be limited to) any of the following: notes to describe the purpose of a video; notes to accompany a more complex concept; notes on more general concepts covered within each module etc. It should also be clear to an ‘educator’ where to find such notes.
- There is a clear course breakdown, timeline and suggested timings for delivery of each module. We suggest you provide a cover sheet to guide the educator/self-paced learner through the order of modules, suggested timings, what should be prepared in advance and any follow-up tasks etc.
- The course contains clear signposting to any previously adapted materials.
- All course materials are easily accessible and reproducibility instructions are available.
- There is a consistent syntax across modules.
- There is a housekeeping checklist.
- There is a checklist for what to do in the run up to the course delivery.
- There are clear instructions for how to use the assessment activities as a tool for assessment.
:::

## Connections workshop template format
- Prework
- Self-learning assessment which feeds into evaluation approach
- Introduction to Learning Outcomes
- Scene setting/context
- Challenges
- Group work
- Self-reflecton
- Feedback to group

## Questions to REG

- Distinction or combine RDS/RSE role
- Personnel interest from within REG? (min 2 per workshop)

## Consider for later
- Vitae
- Online workshop for future runs
- Non-Turing venue

## Useful references

[Why science needs more research software engineers](https://www.nature.com/articles/d41586-022-01516-2?utm_term=Autofeed&utm_campaign=nature&utm_medium=Social&utm_source=Twitter#Echobox=1654028506)

[Job spec at the Turing](https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fcezanneondemand.intervieweb.it%2Fturing%2Fjobs%2Fresearch_data_scientistresearch_software_engineer_23892%2Fen%2F&data=05%7C01%7Cmnemes%40turing.ac.uk%7Ce11ebd9e2896446498b308da43bf7ba8%7C4395f4a7e4554f958a9f1fbaef6384f9%7C0%7C0%7C637896786942961027%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=TwuAPrO8TpP7xm8UiBT%2BJno67wniPvy71qxiSVh%2Fsck%3D&reserved=0)

[Resources from the Society of RSE](https://society-rse.org/resources-database/)

## Catchup 21/7/22

Harriet, Jack, Nick, Ed, Pam

#### Agenda

- Dates
- Intros
- Who does what?
- Rough plans/ideas for content
- AOB

#### Rough overview of content:

- 2 longer exercises/hack sessions (one scivision, maybe 1st module RDS course other - can they link together?)
- General workshop intro
- Talks about RSE/RDS roles (+RCP?)
- Career paths (vs. traditional academia/industry)
- National/international RSE/RDS
- History/landscape/why RSE exists
- Diversity of backgrounds
- Q+A session/panel/conversation
- Project lightning talks (including presenter intro/cofee chat)
- Networking sessions
- Self-reflection and feedback at the end

#### Workshop

- In-person
- Pre-requisites?
- Basic AI/data science understanding
- Let Harriet know of others as material develop
- Define learning outcomes
- Think about anything REG would like evaluation/survey in

#### Dates, Organisation etc.

- Weds 28 - Thurs 29 September held in Enigma
- Otherwise October (but RSE course is 10-21st October)
- Harriet can sort catering, registration etc.
- **Meet 22nd August**