Han, F.Pardo, A.Ellis, R.A.2023-10-272023-10-272020Journal of Computer Assisted Learning (JCAL), 2020; 36(6):969-9800266-49091365-2729https://hdl.handle.net/2440/139806This study examines the extent to which the learning orientations identified by student self-reports and the observation of their online learning events were related to each other and to their academic performance. The participants were 322 first-year engineering undergraduates, who were enrolled in a blended course. Using students' self-report on a questionnaire about their approaches to learning and perceptions of the blended learning environment, ‘understanding’ and ‘reproducing’ learning orientations were identified. Using observations of student activity online, a Hidden Markov Model (HMM) and agglomerative sequence clustering detected four qualitatively different patterns of online learning orientations. Cross-tabulations showed significant and logical associations amongst the learning orientations derived by the self-report and observational methods. Significant differences were also consistently found in the students' academic performance across the mid-term and final assessments based on their learning orientations detected by both self-report and observational methods, results which have important implications for learning research.en© 2020 John Wiley & Sons Ltd.blended university course design; learning analytics; learning orientations; observed data; self-report data; student approaches to learningJournal article10.1111/jcal.124532023-10-272-s2.0-85084974962659573Pardo, A. [0000-0002-6857-0582]