2.2. Algorithmic Profiling, Automated Tracking, and Purpose Limitation Breaches
The deployment of algorithmic tracking within university learning analytics platforms creates profound operational friction with statutory purpose limitation requirements under the Digital Personal Data Protection Act. Higher education institutions collect extensive digital footprints across institutional learning management systems, academic repositories, and virtual classrooms. When automated systems aggregate these behavioural traces to profile academic trajectories or predict student performance, institutions frequently exceed the initial boundaries of educational delivery for which data was gathered. Under statutory fiduciary principles, data processing remains lawful only when anchored to clear, specified purposes that prevent secondary processing deviations without renewed authorization ("Compliance Obligations under the Digital Personal Data Protection Act", 2026). This creates an acute vulnerability because automated analytics models dynamically evolve, inferring sensitive behavioral attributes that students never explicitly authorized. Furthermore, statutory provisions mandate that consent must be free, specific, informed, unambiguous, and fully revocable through accessible mechanisms ("India’s Digital Personal Data Protection", 2026). The structural asymmetry between university administrations and enrolled learners undermines this standard, as students rarely possess genuine autonomy to refuse pervasive automated monitoring without jeopardizing academic standing. Educational fiduciaries face heightened statutory responsibilities to establish verifiable data governance architectures that guarantee data principals the right to correction and erasure ("India’s Digital Personal Data Protection", 2026). Without rigorous purpose bounding and auditable consent records, the continuous algorithmic surveillance embedded in modern educational platforms risks classification as unauthorized data processing ("Compliance Obligations under the Digital Personal Data Protection Act", 2026). Consequently, universities must implement strict institutional limits on predictive profiling to reconcile pedagogical innovation with mandatory legal accountability.