Warning-only LA feedback can increase mental load, whereas pairing warnings with encouragement leads to higher emotional and cognitive engagement¶

Claim · All claims
Evidence · 1 study · review r2 · q2
Currency · newest study 2022 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? The review reports, citing Sun et al. (2019), that warning-only LA feedback can increase mental load while warnings combined with encouragement lead to higher emotional and cognitive engagement. → Seyyed Kazem Banihashem 2022

Evidence¶

Seyyed Kazem Banihashem 2022¶

Seyyed Kazem Banihashem, Omid Noroozi, Stan van Ginkel, Leah P. Macfadyen, Harm J.A. Biemans. (2022). A systematic review of the role of learning analytics in enhancing feedback practices in higher education. Educational Research Review. https://doi.org/10.1016/j.edurev.2022.100489

q2 · i? · review · r2

The review reports, citing Sun et al. (2019), a study using survey data including a cognitive load scale, that "it can increase the mental load" for warning-only feedback, while adding encouragement raises engagement; the review concludes LA feedback should include encouragement.

"If LA-based feedback relies only on warning systems, then it can increase the mental load, while putting warning systems with the encouragement of what to do can lead to higher emotional and cognitive engagement (Sun et al., 2019)."

Discussion¶

Related Claims¶

• LA-based feedback shows potential to save educators time compared with traditional one-by-one feedback provision — related
• Strong early-warning monitoring systems paired with strong norms and routines help students recover emotionally and engage academically — related
• Warning labels alone did not improve performance or reduce reliance on GenAI advice, and students sometimes adopted incorrect AI answers — related
• In an AI-based early warning system, the predictive importance of CAM dimensions shifted over an instructional unit, with affect/metacognition self-reports leading early and cognitive artifacts gaining accuracy toward the end — related