Academics piloting SPPA provided effective interventions and held positive views of the framework¶

Claim · All claims
Evidence · 1 study (2 entries) · design r2 · q2
Currency · newest study 2024 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? In a six-course tertiary evaluation, academics were able to use SPPA to deliver effective interventions and reported a positive outlook on the framework and its features. → Alalawi 2024 q2 i? Academic views were assessed via interviews analysed with thematic analysis (Sub RQ4). → Alalawi 2024 (2)

Evidence¶

Alalawi 2024¶

Alalawi, K., Athauda, R., & Chiong, R. (2024). An Extended Learning Analytics Framework Integrating Machine Learning and Pedagogical Approaches for Student Performance Prediction and Intervention. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-024-00429-7

q2 · i? · design · r2

Evaluation across six courses with four academics who piloted LAIs; quantitative and qualitative data were collected and analysed. The article reports this overall positive outcome for the framework evaluation.

"Academics were able to provide effective interventions using SPPA and also had a positive outlook on using SPPA and its features."

Alalawi 2024 (2)¶

Alalawi, K., Athauda, R., & Chiong, R. (2024). An Extended Learning Analytics Framework Integrating Machine Learning and Pedagogical Approaches for Student Performance Prediction and Intervention. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-024-00429-7

q2 · i? · qualitative · r?

Qualitative strand of the evaluation: interviews with the four academics were transcribed and content classified into themes and concepts using thematic analysis chosen for its versatility (Braun & Clarke, 2006, as cited).

"We conduct interviews with academics who used SPPA to collect qualitative data and analysed them. A thematic analysis was undertaken to interpret and analyse interview data."

Discussion¶

Related Claims¶

• A self-service course-level framework lowers the infrastructure barrier to piloting learning analytics interventions — related
• Grounding LAI feedback in constructive alignment and the Hattie–Timperley feedback model structures personalised interventions — related
• Course-specific prediction models may outperform institution-wide one-size-fits-all models because instructional conditions vary — related