Understanding Learner Behavior Through Learning Design Informed Learning Analytics

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" summary

A learning‑design‑aware analysis of an edX Python MOOC codes videos and exercises with a revised Bloom taxonomy, builds a learner resource access transition matrix and shows it as a heat map visualization, and uses SNA degree counts to rank resource roles. The transition matrix produces a diagonal (sequence following) plus mirror‑image clusters (review/resume events). Overview and summary videos surface as frequent triggers and targets. Higher‑education and higher‑skill completers show higher in/out degree to complex problem sets; prior programming experience has little effect.

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1. 0:00Start
2. 0:49More meaningful feedback needs learning design perspectives, which is yet to be investigated. "Learning analytics needs to build on and better connect with the existing body of research knowledge about learning and teaching" (Gaševic, D. Dawson, S. & Siemens, 2015)
3. 1:44Learning resource access transitions: the learning behavior to understand A transition is a sequence of connected resource traversals each starting from a trigger leading to a target. • A learning trajectory is the path along which learning may proceed and consists of a sequence of transitions. • Learners can decide their own learning trajectories in MOOCs.
4. 6:07Social Network Analysis (SNA) . We adopt the notion of degree from SNA to analyze the trigger and target resources. • In-degree represents the number of transitions going to a resource, while out degree shows the number of transitions leaving from a resource.

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