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Implementation Fidelity of DPDP Governance of University Learning Analytics

Governance of higher education learning analytics under statutory data protection regimes demands a systematic alignment between legal fiduciary mandates and digital pedagogical workflows. Evaluating implementation fidelity requires examining how universities navigate statutory consent mechanisms, student rights, and infrastructural compliance without compromising academic analytics. Such institutional accountability establishes a necessary benchmark for safeguarding digital nagriks within algorithmic campus ecosystems.

कार्य का लक्ष्य

To evaluate how Indian universities implement DPDP Act fiduciary mandates across learning analytics platforms while maintaining pedagogical integrity.

कार्यप्रणाली

Qualitative comparative regulatory analysis of statutory texts, draft compliance rules, and higher education algorithmic governance policy documents.

वैज्ञानिक नवीनता

Provides the first framework evaluating DPDP Act compliance fidelity specifically tailored to algorithmic learning analytics in Indian higher education.

दस्तावेज़ विवरण

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Master's Dissertation

Degree:
Implementation Fidelity of DPDP Governance of University Learning Analytics

Author:

Group

First M. Last

Advisor:

Dr. First Last

City, 2026

Contents

Certificate
Declaration
Abstract
1.1 Institutional Context of Learning Analytics
1.2 Problem Formulation and Research Questions
2. Statutory Framework and Theoretical Foundations
2.1 The DPDP Act and Data Fiduciary Architecture
2.2 Algorithmic Governance and Pedagogical Autonomy
3. Methodological Strategy and Evaluative Framework
3.1 Documentary Corpus and Comparative Criteria
3.2 Fidelity Assessment Parameters
4. Analysis of Institutional Implementation Fidelity
4.1 Consent Architecture and Rights Management
4.2 Technical Safeguards and Algorithmic Audits
5. Critical Discussion and Strategic Governance Pathways
Introduction
Conclusion
Bibliography

Introduction

The codification of India's Digital Personal Data Protection (DPDP) Act establishes a comprehensive fiduciary framework designed to safeguard individual privacy across data-driven ecosystems [2], [8]. Within higher education, the rapid adoption of learning analytics and algorithmic governance reconfigures institutional administration and academic monitoring [7]. Universities operate as Data Fiduciaries, managing sensitive behavioral trails and academic records of digital nagriks under heightened regulatory expectations [1], [8].

Translating statutory privacy mandates into functional educational analytics presents severe operational friction [1], [5]. Institutional fidelity remains complicated by ambiguities in subordinate rules, the governance of consent management, and the friction between algorithmic oversight and pedagogical autonomy [6], [7]. While commercial and financial sectors have initiated infrastructural adaptations [2], university ecosystems struggle with balancing automated academic interventions against statutory rights of correction and erasure [1], [6].

Existing scholarship predominantly examines national data protection models through broad comparative legal lenses or sector-specific financial compliance [2], [3]. However, higher education remains under-theorised regarding how statutory obligations alter algorithmic power dynamics and learning governance [3], [7]. Empirical and institutional literature frequently overlooks the specific mechanisms through which educational institutions reconcile statutory compliance obligations with real-time predictive student analytics [5], [7].

This research evaluates the implementation fidelity of DPDP governance within university learning analytics architectures using systematic policy analysis and comparative regulatory synthesis [3], [6]. By critically examining statutory fiduciary duties, consent structures, and student rights mechanisms, the inquiry establishes an evaluative matrix for institutional compliance [1], [2]. The findings illuminate structural pathways for aligning algorithmic student governance with India's emerging data protection paradigm [3], [8].

5.1 Institutional Alignments, Pedagogical Tensions, and Governance Limits

Scholarly examinations of the Digital Personal Data Protection framework emphasize that treating institutional entities as data fiduciaries mandates explicit consent mechanisms, robust security safeguards, and active user rights management (Encrypt or Perish, 2026). However, operationalizing statutory compliance entails substantial investments in infrastructure upgrading, personnel training, and consent architecture, while procedural ambiguities in statutory execution persist (Operational Considerations, 2026). When transferred to higher education, fiduciary obligations intersect directly with algorithmic decision-making systems that increasingly shape teaching, student evaluation, and institutional administration (Where is the Learning in Higher Education, 2026). Although statutory frameworks conceptualize data protection through individual rights and fiduciary duties, critical analyses demonstrate that digital learning analytics reconfigure pedagogical autonomy and reinforce managerial modes of educational governance (Where is the Learning in Higher Education, 2026). A critical research gap remains in understanding how higher education institutions can reconcile statutory fiduciary duties with the operational realities of predictive learning analytics. Existing scholarship predominantly addresses data privacy within financial and clinical domains, largely overlooking the pedagogical friction generated when monitoring student progress under statutory consent mandates. Methodologically, this study is constrained by the evolving regulatory architecture, as subordinate rules and institutional enforcement guidelines remain under active governmental formulation. Additionally, the lack of standardized auditing metrics for pedagogical algorithms limits the empirical generalizability of implementation fidelity assessments across diverse campus environments. Addressing these structural limitations requires longitudinal evaluations of institutional compliance practices and algorithmic accountability mechanisms.

References

  1. India’s Digital Personal Data Protection (DPDP) Act 2023 and draft Digital Personal Data Protection rules 2025: Operational considerations for psychiatric practice in India
    Amit Chail, Ranjit S. Lahel, Vinay S. Chauhan et al.
    DOI लिंक
  2. Encrypt or Perish: How DPDP Act 2023 Reshapes Financial Data Governance
    Vedansh Pathak
    DOI लिंक
  3. INDIA'S DPDP ACT AND THE RISE OF A THIRD MODEL OF DATA GOVERNANCE
    Chaitanya Singh
    DOI लिंक
  4. An Evaluation of Digital Personal Data Protection (DPDP) Act, 2023
    Dr. Mayura Prakashrao Borde
  5. Digital Personal Data Protection Act, 2023: A New Compliance Frontier for Indian Businesses
    Shubhi Tiwari
  6. Compliance Obligations under the Digital Personal Data Protection Act, 2023: A Critical and Comparative Analysis with the GDPR
    Subrata Das
  7. Where is the learning in Higher Education learning analytics? Digital governance and the meaning of ‘higher learning’
    Ana Francisca Monteiro
  8. Putting Interests of Digital Nagriks First: Digital Personal Data Protection (DPDP) Act 2023 of India
    Charru Malhotra, Udbhav Malhotra

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