Content-Focused Formative Feedback Combining Achievement, Qualitative and Learning Analytics Data

Abstract

Research that integrates Learning Analytics (LA) with formative feedback has been shown to enhance student individual learning processes and performance. Debates on LA-based feedback highlight the need to further understand what data sources are appropriate for LA, how soon the feedback should be sent to students and how different types of feedback promote learning. This study describes an empirical case of LA-based feedback in higher education and analyzes how content-focused feedback promotes student achievement. The model combines quantitative achievement indicators with qualitative data about student learning challenges to develop feedback. Data sources include student pretest results, participation in practice exercises as well as midterm and final exam grades. In addition, in-depth interviews with high-, medium- and low-performing students are conducted to understand learning challenges. Based on their performance, students receive content-focused feedback every two weeks. The results show statistically significant improvements in final grades, in addition to a higher rate of problem-solving participation among students who receive feedback compared to their peers who opt out of the study. The contributions to the area of LA-based formative feedback are the following: (a) a model that combines quantitative with qualitative data sources to predict and understand student achievement challenges, (b) templates to design pedagogical and research-based formative feedback, (c) quantitative and qualitative positive results of the experience, (d) a documented case describing the practical implementation process.