Use LCF risk clusters to target Supplemental Instruction recruitment and resource allocation¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article recommends using LCF-identified risk subgroups to decide which students to recruit into Supplemental Instruction and how to allocate constrained SI resources, since SI is resource intensive, space constrained, and voluntary. The authors state their goal to "identify groups of students that will benefit most from SI to guide resource allocation decisions and understand how to best meet the needs of all students." Cluster choice should prioritize ease of interpretation for educators and administrators.

Design Implications¶

Context¶

Requirements¶

• Administrative stakeholder input on the number of risk groups, and a cluster solution chosen for ease of interpretation and model simplicity rather than an objective criterion

Constraints¶

• SI is resource intensive and constrained by available classroom space, and its voluntary nature does not necessarily support all students in a given course

Target Learners¶

• students in high challenge, large enrollment bottleneck courses, particularly those in identified high-risk subgroups

Target Learning Goals¶

• increase course success and retention by directing intervention resources to the subgroups that benefit most

Affordances¶

Related Strategies¶

• Use early-session timing signals, interpreted relative to proficiency, to identify students needing adaptive support

Examples¶

-

Key Sources¶

• Pelaez, K., Levine, R. A., Guarcello, M., Laumakis, M., & Fan, J. (2019). Using a Latent Class Forest to Identify At-Risk Students in Higher Education. Journal of Educational Data Mining, 11(1). https://jedm.educationaldatamining.org/index.php/JEDM/article/view/283