Saleh Alghamdi: Analytics of Temporal Patterns of Self-regulated Learners: A Time Series Approach

Описание: https://cic.uts.edu.au/events/saleh-a...

Analytics of Temporal Patterns of Self-regulated Learners: A Time Series Approach

Saleh Alghamdi, Monash University

Abstract: Understanding self-regulated learning (SRL) requires more than identifying which processes learners use; it also requires examining when and how these processes unfold over time. This webinar draws on my recent study, which proposes a time-series analytics approach for modelling temporal SRL patterns during a complex multi-text writing task. Using trace data from a 120-minute session, the study captures both dimensions of temporality—event order and passage of time—through clustering. The analysis reveals five distinct SRL strategies characterised by different trajectories of cognitive and metacognitive engagement. The talk will focus on conceptual and methodological questions emerging from this work, including how temporal SRL strategies should be theoretically interpreted, how analytics can inform the timing of interventions, and how this approach may extend to GenAI-supported learning environments.

Bio: Saleh Alghamdi is a third-year PhD candidate in Learning Analytics at COLAM: Centre for Learning Analytics Monash, Monash University. His research focuses on self-regulated learning, temporal learning analytics, and time-series methods for modelling learners’ cognitive and metacognitive processes during writing tasks. He is also affiliated with the College of Computer and Information Sciences at Imam Mohammed Ibn Saud University, KSA.