Data storytelling: framing learning-platform data as rich narratives of individual learners' journeys to guide support and theory development¶

Theory · All theories
Evidence · 1 claim (1 for) · 1 study (1 design), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description¶

The paper organizes its argument around the metaphor of learning theories as stories positioning the learner as protagonist, with the platform supplying setting and plot. It argues that when a DLP captures learner, process, and context, "learners' stories can be told in ways that hold constant or systematically vary features of the learner, the context, or the process so that empirical tests of an educational theory can be reconciled." Instructors follow stories to adaptively support learners, while researchers apply multiple theoretical lenses as narrators to describe and test learning processes.

Design Implications¶

Context¶

Requirements¶

• Data platforms that collect data essential for describing learners, process, and context in detail
• Tools to enrich raw data with the setting and plot established by an institution, course, and learning task

Constraints¶

• The article notes qualitative accounts of individual journeys are not meant to provide opportunities for generalization or empirical testing of educational theories

Target Learners¶

• educators, educational researchers, and platform developers in higher education

Target Learning Objectives¶

• understanding and describing learners' engagement and learning processes to provide adaptive instructional support

Claims¶

• Instructor co-designed tagging transforms raw LMS log data into structured event data reflecting course design and temporal context [+W]

Related Theories¶

Examples¶

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Key Sources¶

• Bernacki, M.L., and Plumley, R.D. (2026, February). CLICKSTREAM: Essential educational infrastructure to promote student learning and educational theory development. Digital Promise. https://doi.org/10.51388/20.500.12265/285