Inhaltszusammenfassung

Predictive analytics platforms now guide many universities’retention and advising strategies, yet their rapid adoption raises urgentequity questions. This paper examines three issues: (1) how educationinstitutions currently deploy predictive models; (2) which ethical andpractical risks like bias, privacy loss, and ’at risk’ labeling emerge inreal-world use; and (3) how such tools can be integrated with teachingpractices to support students without amplifying inequality. We combinea theory-dri...Predictive analytics platforms now guide many universities’retention and advising strategies, yet their rapid adoption raises urgentequity questions. This paper examines three issues: (1) how educationinstitutions currently deploy predictive models; (2) which ethical andpractical risks like bias, privacy loss, and ’at risk’ labeling emerge inreal-world use; and (3) how such tools can be integrated with teachingpractices to support students without amplifying inequality. We combinea theory-driven literature review drawing on Self-Determination Theory,the Community of Inquiry framework, the Technology AcceptanceModel, and sociological perspectives with forthcoming empirical demonstrationson two open datasets. The study offers actionable guidance forresearchers, developers, and decision-makers pursuing responsible learninganalytics by mapping adoption patterns, surfacing risk mechanisms,and outlining equity-centred design principles.» weiterlesen» einklappen

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