Editorial: Beyond Cognitive Ability


  • Srecko Joksimovic
  • George Siemens
  • Yuan Elle Wang
  • M. O. Z. San Pedro
  • Jason Way




The past 70 years of research in learning has primarily favoured a cognitive perspective. As such, learning and learning performance were measured based on factors such as memory, encoding, and retrieval. More sophisticated learning activities, such as perspective changes, still relied on a fundamental cognitive architecture (Dunlosky & Rawson, 2019). Early researchers advocating for a constructivist learning lens, such as Piaget, also assessed development on a range of cognitive tasks. Over the past several decades, this view of learning as cognitive has given rise to a range of augmenting perspectives. Researchers increasingly focus on mindsets, social learning, peer effects, self-regulation, and self-perception to evaluate the broader scope of learning. For learning analytics (LA), this transition has important implications for data collection and analysis, tools and technologies used, research design, and experimentation. This special issue continues existing conversations around LA and emerging competencies (Dawson & Siemens, 2014; Buckingham Shum & Crick, 2016) but also reflects the growing number of researchers engaging with these topics.


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How to Cite

Joksimovic, S., Siemens, G., Wang, Y. E., San Pedro , M. O. Z., & Way, J. (2020). Editorial: Beyond Cognitive Ability. Journal of Learning Analytics, 7(1), 1–4. https://doi.org/10.18608/jla.2020.71.1



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