Digital Skills Lab Case Study

The Department of Statistics at the London School of Economics (LSE) partnered with the Digital Skills Lab (DSL) to enhance students' digital capabilities and better prepare them for academic success and future careers. This collaboration, led by Dr Pik Liew, Associate Professor (Education), BSc Actuarial Science Programme Director & Student Experience Strategic Lead, focused on embedding essential tools like Excel, R, and Python into the curriculum. 

Background

Dr Liew recognised a growing need to embed practical digital competencies into undergraduate teaching at the Department of Statistics. “With many students expected to pursue careers in the financial services sector, it is essential that we equip them with tools such as Excel, R, and Python from the outset of their academic journey.” 

The Challenge 

The first-year course ST111 Business Analytics requires students to work with real-world business data, draw insights, and present findings effectively. However, Dr Liew noted that “many students entering the course lacked foundational digital skills, particularly in Excel, which are crucial for data analysis and visualisation in the financial services sector.” 

"There simply wasn't time in the academic schedule to teach basic Excel functions," she added. "I needed to spend the course time on application - data collection, cleaning, modelling, and visualisation - not explaining how to open a file or format a chart." 

Without these foundational skills, students struggle to engage with the course content effectively and require significant time to catch up while in class, ultimately limiting their ability to engage fully with the course content and successfully complete assessments. 

Partnering with the Digital Skills Lab 

To address this challenge, Dr Liew collaborated with the DSL to design and implement a set of digital skills training resources. This partnership ensured that the sessions were tailored to specific needs of the department’s students, focusing on industry-relevant tools.  The training content includes examples aligned with statistics and actuarial science, increasing the relevance of the sessions and students ‘engagement. 
 
To maximise impact, the sessions are scheduled into students' timetables and made compulsory, ensuring high attendance and consistent skill levels. 

What sets this collaboration apart is its co-design ethos.  Dr Liew adds: "I don't delegate training to the DSL’s team; I see them as partners. We design together, tweak together, and keep improving the content based on what works for our students." 

This collaborative effort resulted in an all-day Excel Bootcamp tailored to first year students taking the Business Analytics course. This intensive 8-hour session, led by DSL Learning Development Lead Nedelin Velikov, provides students with the foundational Excel skills needed to hit the ground running. 

Key components include: 

-Data entry and formatting 

-Functions and formulas 

-Data handling, cleaning, and visualisation using charts and graphs 

-Practical examples drawn from statistics, actuarial science, and the finance sector to maximise students’ engagement  

In addition to Excel, the department worked with the DSL to develop pre-sessional Moodle modules for R and Python. These self-learning online resources are designed as prerequisites for the department’s students to support their foundational learning. 

Furthermore, building on the success of the pre-sessional Excel bootcamp, a one-day R Bootcamp will be introduced in the new academic year for all undergraduate statistics students. Compulsory to attend and embedded in the students' timetables, it will ensure students have the necessary skill levels in R to confidently start their course.   

Impact and Results 

The collaboration delivered immediate and measurable results: 

Academic Performance 

• Improved learning outcomes: Students can apply their technical skills immediately to their coursework, leading to higher-quality submissions featuring robust data visualisations from the start of the academic year 

• Enhanced student engagement: Students can start their course feeling confident and prepared, allowing Dr. Liew to focus on teaching advanced analytics concepts rather than troubleshooting software or teaching basic digital skills 

• Time efficiency: By being able to teach advanced concepts from the get-go, Dr. Liew can focus on making progress on her course schedule and optimise its delivery  

Student Development 

• Increased confidence: Students are more prepared and up to speed with the course’s demands, resulting in better performance in seminars and assessments 

• Extended learning: Students become more proactive in attending the Digital Skills Lab’s additional workshops and exploring further development opportunities in their own time 

• New learning opportunities: Several ST111 students participated in and won prizes at the Optiver Excel Challenge: Mastering Probabilistic Decisions, applying their Excel skills to real-world scenarios in the current financial market 

Looking Ahead 

The Department of Statistics is keen to explore further training opportunities with the DSL, including exploring integration of tools like Power BI and training material on responsible use of generative AI. “I want to ensure our students remain equipped with industry-relevant skills as technology evolves”, adds Dr Liew. 

Conclusion 

Through a collaborative, agile and student-centred approach, students become more confident, academics’ teaching becomes more efficient, ultimately improving learning outcomes and giving students a real advantage from day one of their academic journey. 

“The DSL team is incredibly supportive and collaborative. Their workshops save us time and help students start strong. It's a win-win for everyone. It's a service I wouldn't want to do without. The time we invest up front with the DSL saves us time later and gives our students a real advantage from day one."