PROGRAMMATIC ASSESSMENT AND LEARNING ANALYTICS FOR CONTINUOUS PROGRESS MONITORING IN S2 PAI UNZAH
Keywords:
Programmatic Assessment, Learning Analytics, Longitudinal Evidence, Feedback, Graduate Islamic EducationAbstract
This article develops a programmatic assessment and learning analytics framework for continuous progress monitoring in the S2 PAI Program at Universitas Islam Zainul Hasan Genggong. Conventional assessment often treats assignments, midterm examinations, final examinations, and research products as separate events, making it difficult to interpret students' development across semesters. Using qualitative descriptive library research, the study synthesizes programmatic assessment, formative assessment, feedback literacy, learning analytics, and Islamic higher education literature. The findings indicate that graduate competence should be inferred from multiple low- and medium-stakes evidence points collected over time, including analytical papers, teaching designs, presentations, research milestones, oral defenses, and reflective revisions. A dashboard can summarize trends, but academic decisions must remain based on human judgment, narrative feedback, and contextual interpretation. Progress committees, evidence maps, remediation plans, and data-governance rules are required to prevent fragmented scoring and reductive quantification. The study concludes that programmatic assessment can strengthen continuity, early intervention, and accountability in S2 PAI when analytics supports rather than replaces pedagogical judgment
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