Low-performing students tended to procrastinate more on graded problem-solving exercises and on video watching with formative MCQs¶

Claim · All claims
Evidence · 1 study · associational r1 · q2
Currency · newest study 2023 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? The midterm subtracted network showed low performers had stronger catching-up connections to summative exercises and to videos with formative MCQs, suggesting more procrastination. → Raković 2023

Evidence¶

Raković 2023¶

Raković, M., Ahmad Uzir, N., Matcha, W., Eagan, B., Jovanović, J., Shaffer, D. W., Pardo, A., & Gašević, D. (2023). Network Analytics to Unveil Links of Learning Strategies, Time Management, and Academic Performance in a Flipped Classroom. Journal of Learning Analytics, 10(3), 64–86. https://doi.org/10.18608/jla.2023.7843

q2 · i? · associational · r1

Subtracted epistemic network (Figure 8) comparing midterm high- and low-performing groups. High performers had stronger connections in almost every activity except M catching.up–S summative assess and M catching.up–S videos and form assess, from which the authors draw the procrastination interpretation.

"the results suggest that the students with low performance tended to procrastinate more on problem solving and exercises that counted toward the final course mark. They also procrastinated more in watching videos and doing the associated formative MCQs."

Discussion¶

Related Claims¶

• In examination weeks, students revisited prior topics and used exercises, whose deadlines had passed, as formative practice for the exams — related
• On the final exam, high performers had more dominant strategy–time-management links than low performers, who showed dominant catching-up, ahead-with-errors, and video-revision links — related
• Students in the flipped classroom most often used the preparing and revisiting time management modes together with the summative assessment learning strategy — related
• Low performers completed activities on time for fewer topics and showed less catching-up only in early topics, while high performers showed no catching-up on later topics — related
• High- and low-performing students did not differ significantly on the midterm-exam ENA network dimensions despite detected network differences — related
• High- and low-performing students differed significantly on the final-exam ENA network X dimension but not the Y dimension — related
• Video-watching sequences involving pausing and rewinding are negatively correlated with math task performance in a flipped precalculus lesson — related
• Viewing of the personalized AI videos declined sharply across the quarter, with views of the first week-9 video set suggesting fewer than 10% of the course population was watching voluntarily by the end of the course — related
• The analytics agent surfaced a Module 2 dead zone — students stopping around the 42-minute lecture mark where exercises ended — and the instructor revised the exercise set in response — related