Amelia Tersol Navejas
Effective instructional decision-making in mathematics education requires more than evaluating learning outcomes after instruction; it demands timely, evidence-based insights that inform pedagogical interventions throughout the learning process. This study proposes a Learning Analytics Framework for Data-Driven Instructional Decision-Making grounded in Pedagogical Content Knowledge (PCK) to support the design, evaluation, and continuous improvement of learning modules for Mathematics in the Modern World. Using a design research approach, the study examined how mathematics professors in Teacher Education Institutions (TEIs) integrate PCK into instruction and translated these practices into an analytics-informed instructional framework. The framework incorporates constructivist learning principles, collaborative and discovery-based learning, contextualized mathematics instruction, and learner-centered pedagogies as key instructional indicators for evidence-based teaching decisions. The developed learning module was evaluated as acceptable across physical design, learning outcomes, mathematical content and processes, instructional design, learning activities, assessment procedures, and relevance to PCK development. Student performance analysis demonstrated significant improvement following exposure to the module, while qualitative findings indicated enhanced learner engagement, meaningful learning experiences, and greater appreciation of mathematics through interactive and authentic learning activities. Building on these findings, the proposed learning analytics framework identifies instructional indicators: including learner performance, engagement, activity completion, and PCK-based teaching strategies, this is to support continuous monitoring and data-driven instructional decision-making. The study contributes a conceptual foundation for integrating learning analytics with PCK, enabling instructors to make timely instructional adjustments that improve teaching effectiveness and student learning in higher mathematics education.