Segmenting students by noncognitive attributes as a promising but unproven approach to improving postsecondary success¶

Strategy · All strategies
Evidence · 1 claim (1 for) · 1 study (1 review), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description¶

The review reports that although no published example documents colleges using segmentation to improve students' success, research authors "hypothesize about the potential applications of their research," and experts interviewed for the study "agree that such approaches have promise for segmenting students to improve postsecondary success." The strategy would classify student populations using noncognitive assessment instruments and tailor institutional supports accordingly, but the review found no documented instance of this having been done.

Design Implications¶

Context¶

Requirements¶

• Instruments to assess students' noncognitive attributes
• Institutional capacity to classify or segment student populations using assessment results

Constraints¶

• No published research example describes colleges using segmentation to improve students' success; support is limited to author hypotheses and expert opinion

Target Learners¶

• college students
• postsecondary institutions

Target Learning Goals¶

• improving postsecondary student success

Claims¶

• No published research describes colleges using segmentation to improve student success, though authors and experts see promise in the approach [+W]

Related Strategies¶

Examples¶

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Key Sources¶

• Ann E. Person, Scott E. Baumgartner, Kristin Hallgren, Betsy Santos. (2014). Measurement and Segmentation of College Students' Noncognitive Attributes: A Targeted Review. Oakland, CA: Mathematica Policy Research. https://www.mathematica.org/publications/measurement-and-segmentation-of-college-students-noncognitive-attributes-a-targeted-review