Using Assessment Point Accumulation as a Guide to Identify Students at Risk for Interrupted Academic Progress
| Autor: | Leslie Marchand, Juan C. Cendan, Mary Beth Soborowicz, Basma R Selim, Oloruntomi Joledo |
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| Rok vydání: | 2018 |
| Předmět: |
Students
Medical 020205 medical informatics Metaphor media_common.quotation_subject education MEDLINE 02 engineering and technology Risk Assessment Education Undergraduate methods 03 medical and health sciences 0302 clinical medicine ComputingMilieux_COMPUTERSANDEDUCATION 0202 electrical engineering electronic engineering information engineering Humans 030212 general & internal medicine Retrospective Studies media_common Medical education Point (typography) General Medicine Identification (information) ROC Curve Florida Educational Measurement Risk assessment Psychology Education Medical Undergraduate |
| Zdroj: | Academic Medicine. 93:1663-1667 |
| ISSN: | 1040-2446 |
| DOI: | 10.1097/acm.0000000000002270 |
| Popis: | Interruptions in academic progress (IP) are problematic for students and educational programs alike. Early identification of students at risk for IP, to provide remediation, could be beneficial.Considering the clinically familiar pediatric growth curve as a metaphor, researchers hypothesized they could identify students at risk of IP. They organized course-related examination performance data for 518 students in five classes (2013-2014 through 2017-2018), adding students' percentage scores cumulatively over time. At every examination point, they analyzed the data for dis-tribution and calculated a mean class score. They plotted each student's accumulated points and accommodated a linear fit. Using the mean of the class as the horizontal axis, students gaining points against the mean show a positive slope; conversely, students losing points reveal a negative slope. The authors compared their findings against students who had faced IP-those who had repeated at least one course or an academic year, or who had left medical school.Using a receiver operating characteristic approach, the authors identified a slope of -5 as an excellent screening test with 85% accuracy (sensitivity = 82%, specificity = 86%, area under curve = 0.917). Of 38 students facing IP, 25 would have been identified at risk for IP as early as the fifth assessment using a slope of -5.Given the outcomes of this innovative, inexpensive, highly accurate approach to identifying students at risk of IP, the authors have plans to optimize interventions and to validate the approach at other programs. |
| Databáze: | OpenAIRE |
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