From Learning Analytics to Action: An Integrated MTSS Framework for College and Career Readiness in Digital Higher Education

Abstract

Digital learning environments generate extensive evidence about participation, performance and interaction, learning analytics does not clearly define how this evidence should be used to provide differentiated support to the institution. This conceptual-methodological study proposes a multi-tiered system of support (MTSS) framework for college and career readiness (CCR) in digital higher education that is supported by learning analytics. The framework is grounded in learning analytics, MTSS, CCR, and self-determination theory, and connects approved data collection, indicators that are interpretable, professional review, tier assignment, intervention delivery, progress monitoring, and recalibration. A public dataset with 14,003 records is only used as a measurement-adequacy demonstration as it lacks direct measures of analytics exposure, MTSS delivery, validated engagement, and multidimensional CCR. No significant associations with examination performance were found with equal-weight or alternative-weight proxy summaries, and principal-component diagnostics indicated poor dimensional coherence. These results do not confirm or disconfirm the proposed relationships, but rather indicate that construct misalignment cannot be overcome by large samples and reproducible analysis. The study presents an operational workflow of analytics-to-action, governance and intervention needs, conceptual propositions for future testing and a construct aligned data specification for a potential institutional pilot.

Implications for Practice or Policy

• The use of analytics alerts should be viewed as a call to action for professional review, not as automatic tier assignments.


• Intervention type, dosage, fidelity, uptake and response should be documented for intervention across MTSS tiers by faculty and support teams.

• The researchers should test the framework over time with direct measures of analytics exposure, student engagement and multidimensional CCR