ContextTechnology has been helpful in the field of education for the design, delivery, and assessment of courses. Though academicians quickly adopted the new technology for delivery, they still use the traditional written exams to assess student learning, even in professional courses, including medical, engineering, yoga, and music education systems.
PurposeThe paper focuses on the investigation of how recent technological advancements help capture the hidden and accurate learning indicators of student learning, what devices are found helpful by researchers towards capturing the latent learning indicators, what the trends are, and what are the publicly available datasets that can catalyze the research in the field of learning analytics.
MethodsThe study was carried out by adopting the PRISMA template of Systematic Literature Review (SLR), and the four phases, including identification, screening, selection, and inclusion methods, were carried out towards investigating the research questions.
OutcomesThis paper helps academicians and researchers in the field of education and learning analytics to get an overview of the current trend and identify the research gaps towards integrating data from multiple sources and connecting the educational theories with the captured parameters.
ConclusionA drift has been observed from unimodal data sources to multimodal sources, capturing the data from the perceived behavior of the student to the hidden cognitive and affective domain characteristics.