How Early is Early Enough: Correlating Student Performance with Final Grades.

Williams, Lloyd; Titus, Kimberly J.; Pittman, Jason M.

doi:10.1145/3437914.3437972

Cited by 4 publications

(1 citation statement)

References 7 publications

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“…The earliest and best predictor for non-thriving found by the model was missing two or more weekly preparation homework assignments. This model is in line with previous models in the sense that early grade points and early engagement cues were found to be predictive of the course final grade (Gray & Perkins, 2019;Williams et al, 2021), hence allowing for early prediction that is actionable and useful in assisting at-risk students (Balfanz & Byrnes, 2019;McMahon & Sembiante, 2020).…”

Section: Fye and Intro To Eg And The Non-thriving Prediction Modelssupporting

confidence: 88%

Insights of Instructors and Advisors into an Early Prediction Model for Non-Thriving Students

Hershkovitz

Ambrose

2022

Learning Analytics

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In this qualitative study (N=6), we explored insights of first-year students’ instructors and advisors into an early identification system aimed at detecting non-thriving students in the context of an all-campus first-year orientation course for undergraduates. Following the development of that prediction model in a bottom-up manner, using a plethora of available data, we focus on how its end-users could help us understand the underlying mechanisms that drive the identification of non-thriving students. As findings suggest, participants were appreciative overall of the prediction and its timing and came up with various behaviours that could explain non-thriving, mostly motivation and engagement. They suggested additional data that could predict non-thriving, including background information, academic engagement, and learning habits.

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