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Most research on learning technology uses clickstreams and questionnaires as their primary source of quantitative data. This study presents the outcomes of a systematic literature review of empirical evidence on the capabilities of multimodal data (MMD) for human learning. This paper provides an overview of what and how MMD have been used to inform learning and in what contexts. A search resulted in 42 papers that were included in the analysis. The results of the review depict the capabilities of MMD for learning and the ongoing advances and implications that emerge from the employment of MMD to capture and improve learning. In particular, we identified the six main objectives (ie, behavioral trajectories, learning outcome, learning‐task performance, teacher support, engagement and student feedback) that the MMLA research has been focusing on. We also summarize the implications derived from the reviewed articles and frame them within six thematic areas. Finally, this review stresses that future research should consider developing a framework that would enable MMD capacities to be aligned with the research and learning design (LD). These MMD capacities could also be utilized on furthering theory and practice. Our findings set a baseline to support the adoption and democratization of MMD within future learning technology research and development. ; publishedVersion ; © 2020 The Authors. British Journal of Educational Technology published by John Wiley & Sons Ltd on behalf of British Educational Research Association This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Purpose Governments and organizations worldwide are concerned over the declining number of young people choosing to study Science, Technology, Engineering and Mathematics (STEM), especially after the age of 16. Research has foregrounded that students with positive attitudes toward science are more likely to find it relevant and aspire to a science career. This study aims to understand the factors shaping students' attitudes as these are pivotal in promoting science learning. Design/methodology/approach This study uses the framework of science capital to understand what shapes young people's engagement with or resistance to science. The authors conducted four Computational Thinking making-based workshops with 106 children aged 15–16 years, of which 58 filled in a questionnaire and 22 were interviewed. Statistical and content analyses were performed respectively. Findings The results indicate that children who are more exposed to science-related activities and contexts are more likely to have higher self-efficacy, and that those with higher prior coding experience scored higher in their self-efficacy and science capital. Six themes emerged from the content analysis, highlighting the diverse factors shaping students' attitudes, such as teaching methods, stereotypes and the degree of difficulty encountered while engaging with science in and out of school. Originality/value By combining qualitative and quantitative methods with the use of science capital, the authors found a number of aspects of the school experience that shape students' attitudes to science learning in and out of school, as well as their science career aspirations. ; publishedVersion