Session 4: The Long-term Impact of Covid on Student Learning

Day 3, Friday 30 June 2023

3pm-4.30pm BST//10am-11.30am EDT

Chair: Annika Johnson (University of Bristol, and CTaLE Associate)


The impact of Covid-19 on Teaching and Learning Quantitative and Statistical Methods in Economics

Muhammad Farid Ahmed, Imperial College London, co-presenting with Adeel Tariq, The University of Manchester


Covid-19 disrupted learning universally across the education sector. In this article we try to estimate the impact of this disruption on students’ learning and preparedness for quantitative and statistical courses in Economics. We conduct a standard Statistics assessment at a prominent University in Pakistan to gauge learner’s retention of quantitative and statistical methods taught during the pandemic via remote/hybrid learning methods. We find that students who had their first quantitative and statistical courses in economics taught during the pandemic have significantly poorer performance and retention compared to students who were taught the same courses post-pandemic and mostly in-person. This highlights a key challenge that will be faced by learners and educators of courses in Econometrics as these students may need additional learning support before they are prepared to handle more advanced quantitative courses in economics, including Econometrics. While our results are specific to a particular context, they nevertheless hold important lessons for econometrics lecturers who may wish to re-design initial phases of their econometrics courses to account for the likely impact the pandemic may have had on their own students.

Continuous e-assessment and the impact on students’ engagement and performance

Panagiotis Giannarakis, University of Southampton


Engagement in online materials available on Blackboard has been a critical issue especially during the pandemic, where face to face teaching flipped to synchronous or asynchronous teaching and blended learning. The aim of educators during the COVID period was to find innovative ways to engage students via blended learning. One tool for engaging students with the online materials is continuous e-assessment. Continuous e-assessment has many positive externalities on students’ performance and engagement. Holmes (2015 & 2018), among others found that introduction of e-assessments led to a significant increase in virtual learning environment activity. The question that arises is how successful continuous e-assessment on engaging students with the online materials during the pandemic was and whether this had any impact on students’ performance.

In this research I investigate the impact of continuous e-assessment on students’ engagement and performance. I focus on first year Maths for Economics and third year Applied Economics modules. In the first year of the pandemic, online tests were introduced in both modules only as a method of engagement, where full marks were given upon completion of the tests. After the pandemic, online tests in these modules were used as a method of engagement and assessment. This natural experiment allows me to test the impact of formative and summative e-assessments on students’ engagement with online materials and on their performance in their final exams. More specifically, I test whether weekly formative or summative e-assessments lead students to engage more with the online materials of each topic on Blackboard. I also test whether formative or summative e-assessments are associated with better performance in students’ final assessment. Preliminary results show that summative e-assessments plays a significant higher role on students’ engagement and performance than formative e-assessments.

Building Econometrics Skills and Confidence through Community-Engaged “Data Fest” Events

Caroline Krafft, St. Catherine University


Courses that use big data applied to social issues have been shown to recruit and retain underrepresented students in economics (Bayer, Bruich, Chetty and Housiaux 2020). This research describes a “Data Fest” approach that combines big data and social issues with a collaborative and community-engaged event. Data Fest is a series of events where groups of students of all academic backgrounds address real-world economic and social issues. Students undertake data analysis using R and Stata in a hands-on environment with peers. They ultimately present their findings to a community partner. In this paper we describe Data Fest, including structuring the events to be collaborative and confidence-building, as well as the details of activities that help students build analytical skills. We also present quantitative and qualitative analyses from two years of pre- and post-surveys of Data Fest events, from 109 participants. Changes from pre- to post-survey in student beliefs and attitudes suggest Data Fest led students to be both more confident and knowledgeable in economic analysis skills. Student narratives illustrate the importance of a fun, collaborative environment as well as the relevance and accountability to a community stakeholder as motivating their success and progress. The results show how students from a wide breadth of backgrounds can collaborate, learn new economics and econometrics skills, and build confidence through community-engaged data analysis events.