April 12, 2024, by Laura Nicholson

Creating a Community and Scaling-Up Feedback in a Degree Apprenticeship

Throughout the 2023–4 academic year, we are running a new feature on the Learning Technology (LT) blog: a faculty takeover month! Each month, we will feature posts from different faculty members at the university. Every Friday, posts will highlight interesting work and ideas related to technology in teaching and learning and showcase unique projects from within the various disciplines across the UoN. So far, we’ve featured content from all the faculties at the University. This month, we welcome posts from degree apprenticeship programmes at UoN.

Our second post is written by the Data Science Degree Apprenticeship teaching team.

The Level 6-degree apprenticeship in Data Science commenced in September 2020. Apprentices study for the degree whilst working. In the first year of delivery, there was a small cohort of apprentices, which allowed the teaching team to deliver a course that was personalised with lots of opportunities for specific feedback. The number of apprentices has grown in subsequent years and the most recent cohort has three times the number of apprentices of the original cohort. We describe some of our learnings from delivering the degree apprenticeship and how digital tools have helped us.

Creating a community

One potential challenge when delivering the degree apprenticeship is that apprentices may feel isolated and not have the identity of a student. Each year, apprentices come to in-person days at the University 7–12 times a year. Discussions between apprentices are encouraged very early on in year 1, when they are encouraged to discuss a data science problem on Microsoft Teams in the first three weeks of the degree.

On the in-person days, there are lots of team-building exercises to try and build community within the cohort. To strengthen this community when apprentices are studying remotely, we have weekly Wednesday online sessions on Microsoft Teams. The use of break-out rooms and discussions within these sessions encourages apprentices to maintain relationships with their peers. There are private Teams channels that the apprentices use to talk with each other in a more comfortable forum. In the second year, there are group project assessments and students then develop skills in working together on data science projects using Teams and other tools to succeed in this.

Tracking and feedback

In the first year of delivery, cohort numbers were small, which resulted in us having very clear ideas on the progress of apprentices and to be able to support them. However, the larger cohort numbers in 2023/24 pushed for a new approach in tracking apprentices’ progress and giving them feedback. Early on in year 1, a formative assessment tool called Plickers is used at an in-person day to quickly get an idea of the understanding by apprentices of the early material. Each apprentice has a card that can be used to show their answer and the lecturer uses a laptop or smartphone to quickly see all apprentices’ answers.

This has been successful this year and has allowed us to offer early intervention support to apprentices who might benefit from it. Throughout the first three years of delivery, we have adapted our approach to feedback to benefit students whilst also coping with the larger number of apprentices. One such approach used by some delivery staff has been using Audacity to provide audio feedback rather than written feedback.

HTML interactive notes and STACK questions

Due to the nature of the apprentices being away from the University most of the time, we aimed to create materials that support this learning mode. From the start of the programme, we have expanded our use of HTML interactive notes created using R Bookdown. Within these notes, we can embed materials, such as quizzes and interactive diagrams, which allow apprentices to receive automatic feedback and be able to visualise mathematical concepts for example. HTML notes also have the benefit that mathematical notation can be more accessible for screen reader users. We have also used the STACK question type in Moodle to create mathematics questions that give automatic feedback and allow students to practise multiple questions.

Future ideas

We are facing new challenges in our teaching with the larger cohorts and scaling up the previous teaching and assessment blocks. We have been preparing for these future challenges with our current large year 1 cohort. One approach that we have started using this year for a wider rollout in subsequent academic years is Power Automate to lessen some of the repetitive, time-consuming tasks. Some successful uses of this include allowing apprentices to automatically verify whether their proposed datasets for assessments are ok, without lots of emails and manual feedback from the lecturer, and a quick way for apprentices to anonymously give feedback to each other on in-person days.

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