OLC: Using Learning Analytics, Faculty Collaboration, and Human-in-the-Loop AI to Engineer Student Success

Responsible digital innovation is not defined by adopting the newest technology. It begins with student learning needs, is guided by evidence, is strengthened through faculty collaboration, and uses artificial intelligence to augment—not replace—human expertise and judgment. This webinar presents a higher education case study in which learning analytics, instructional redesign, faculty collaboration, and human-in-the-loop AI were integrated to address performance and retention challenges in online Anatomy and Physiology courses. Participants will examine how the institution moved through a complete improvement cycle: identifying academic risk patterns, collaborating with faculty to interpret the findings, redesigning course and remediation processes, developing a faculty-facing AI assistant, evaluating results, and scaling effective practices into a second course.

The case demonstrates how AI can reduce repetitive faculty workload and support more timely, consistent, and individualized remediation while preserving faculty judgment, accountability, and oversight. Participants will also explore strategies for engaging faculty as partners in innovation, designing AI-supported workflows around clearly defined instructional problems, and maintaining human review of AI-generated analyses and resources. This webinar will benefit professionals seeking a realistic, scalable approach to leveraging existing LMS data and emerging AI tools to improve student outcomes and address faculty workload challenges. Attendees will leave with a practical model for connecting course-level analytics, faculty development, and responsible AI adoption to student success and institutional continuous improvement.

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