Trace data is the dominant data type LA uses to support feedback in higher education (36% of coded data types)¶

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 identified 65 data-type codes grouped into six groups, with trace data the dominant type (23 codes, 36%), used to generate reflective, personalized and predictive feedback. → 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

Systematic review coding of 46 studies identified 65 data-type codes grouped bottom-up into six groups. The review states of trace data that "this is the dominant data type used by LA to support feedback in higher education" (Table 6: 23 codes, 36%), followed by assessment data (18%).

"According to the reviewed studies, this is the dominant data type used by LA to support feedback in higher education."

Discussion¶

Related Claims¶

• LA is used in higher-education feedback studies for a range of objectives beyond improving feedback itself, with reflection the most common (43% of studies) — related
• Deploying a trace-capturing Parsons tool in two university courses surfaced recurring difficulty patterns including exception-type misidentification, return-for-throw confusion, and incorrect control-flow ordering — a narrower finding that bears on this claim
• K-means clustering of K–8 students' platform trace data yields seven distinct engagement profiles — related