Using an adaptive learning platform (ALEKS) to support first-year university mathematics students: Two case studies

Source abstract

The mathematical knowledge of university entrants can differ greatly, which poses challenges in designing first-year mathematics programmes. Addressing these differences can be aided by adaptive assessment and personalised digital learning, which engages students using formative, data-driven feedback. This study explores how assessment and learning analytics can inform the design of first-year support programmes, drawing on two case studies involving an adaptive learning platform, ALEKS, and course-level analytics. ALEKS – Assessment and Learning in Knowledge Spaces – is a web-based learning system based on theoretical research in mathematical cognitive science. In case study 1, ALEKS modules were designed and integrated into the first-year mathematics curriculum for engineering students at the University of Cape Town to strengthen their pre-calculus skills. After six weeks, and following the first test, 88 students transitioned to the extended curriculum programme. Analysis of data from the National Benchmark Test (NBT), ALEKS, and the written tests of these extended curriculum students demonstrated that greater engagement with ALEKS was associated with improved overall performance and better preparation for calculus. Case study 2, conducted with first-year science extended curriculum students at Rhodes University, tailored ALEKS modules to support students’ university-level mathematical skills. The progress of 56 students was tracked across the NBT, ALEKS, and test and exam data. Students who passed the exam had an 18% higher ALEKS pie progress count on average, signalling a link between ALEKS engagement and exam success. Both case studies show how adaptive platforms like ALEKS can provide personalised support to help students from varied backgrounds transition to university mathematics.