Leveraging AI to Improve Learner Outcomes and Learner Records

Key Findings Include:

• Forty-five percent of respondents have a role in academic technology at their institution, 42% are involved in learning design, 16% in information technology, and 12% in student support. Forty percent are from small institutions, 30% from medium institutions, and 30% come from large institutions.
• Sixty-one percent are extremely or very involved with developing learner experiences and/or tracking learner outcomes at their institution, while 36% are somewhat involved.
• Nearly half (49%) of participants said their institution does not currently use any AI-driven tools to enhance learner experience and improve outcomes, while 31% are from institutions that do use them, and 21% were not sure. Among those who use AI-driven tools, 52% use predictive analytics for student success, 52% use AI-driven feedback systems for student assignments, 39% adaptive learning platforms, and 39% stimulated classroom experiences.
• When participants were asked what challenges they have encountered when leveraging AI-driven tools to improve learner experiences and outcomes, 71% said academic integrity or quality concerns, 57% data privacy concerns, 52% insufficient training for faculty/staff, and 52% tool effectiveness.
• Forty-two percent said their institution has not implemented a digital comprehensive learner record, while 36% were unsure/don’t know, 19% said not yet, but they are actively working towards implementation, and just two of 67 respondents (3%) said their institution has implemented a digital comprehensive learner record.
• Over half (52%) said their institution issues digital credentials, while 42% said it does not, and 7% were unsure.
• Among those who said their institution does issue digital credentials, 55% said strategic institutional goals have influenced the adoption of these credentials, 52% said student demand for digital credentials, and 45% said employer demand for skills validation.