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Chelsia Shanen Panekenan
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Elementary Education Researcher

Chelsia Shanen Panekenan

Where school rituals wound and AI can either widen the gap or heal it — the teacher's critical empathy is what decides.

chelsia@afirmasi.org
Indonesia
San Marcos, Texas, USA

About

Chelsia Shanen Panekenan works at the intersection of childhood identity formation, critical pedagogy, and the ethics of AI in elementary education — a research space that is rarely populated with the intellectual urgency it deserves.

An LPDP Scholar pursuing her Master of Arts in Elementary Education at Texas State University (August 2025 – May 2027), Chelsia has maintained a perfect academic record across both completed terms: GPA 4.00/4.00, across coursework spanning Science Curriculum, Advanced Early Childhood Development, Multicultural Teaching and Learning, Second Language Acquisition and Development, Human Development, and English as a Second Language Teaching and Materials.

Her academic formation is both quantitatively rigorous and qualitatively deep. She is trained in the ethnographic and critical theoretical traditions that allow her to ask the questions most educational technology researchers avoid: not just whether AI works in classrooms, but what it does to the identity of the child sitting in front of it — especially the child who has already been told, through ritual and routine, that they do not quite belong.

In April 2026, Chelsia presented her paper at the American Educational Research Association (AERA) Annual Meeting in Los Angeles — one of the most prestigious venues in global education research. Her work, presented in the Roundtable Session "Teaching with AI: Identities, Challenges, and Burnout," directly confronts the ethical stakes of AI in education through the lens of figured worlds, class hegemony, and the lasting psychological damage of school shaming rituals.

She brings to AFIRMASI what most AI-in-education researchers lack: a humanizing lens. Her work insists that before any technology enters a classroom, we must ask what emotional and social architecture already exists in that room — and whether the technology will reinforce it or disrupt it for the better.

Activity Gallery

AERA 2026 — Academic discussion session

AERA 2026 — Academic discussion session

Roundtable session on education policy

Roundtable session on education policy

Scholarly exchange with global researchers

Scholarly exchange with global researchers

Collaborative working group session

Collaborative working group session

Vision

An educational system — and an AI ecosystem — where no child's identity is wounded by the very institution meant to develop it. Where technology enters classrooms already held accountable to the emotional and social realities of the children inside them.

Mission

Research the ethical dimensions of AI in elementary education with the same rigor we apply to curriculum design. Train educators to be critical filters, not passive adopters. Center the experiences of children from marginalized communities in every design decision about educational technology.

Why AFIRMASI?

Because AFIRMASI asks the uncomfortable questions about AI in education — not just 'does it work' but 'who does it work for, and at whose expense.' That is exactly the question my research is built around. The intersection of identity, schooling, and emerging technology is not a boutique academic interest — it is the central ethical challenge of our moment in education. AFIRMASI is where that challenge can be addressed with both scientific rigor and genuine humanistic commitment.

Critical Empathy as Method
Child-Centered Ethics
Humanizing Pedagogy
Equity Before Efficiency
Scholarly Courage

Research Focus

Education

M.A. in Elementary Education
Texas State University, San Marcos · LPDP Scholar
Bachelor's Degree in Elementary Teacher Education
Indonesia

Selected Work

Figured Worlds, Class Hegemony, School Rituals, and AI: Ethnographic and Ethical Perspectives on Identity, Harm, and Humanizing Pedagogy in Education
2026 · AERA Annual Meeting, Los Angeles · Roundtable: Teaching with AI: Identities, Challenges, and Burnout — Apr 9–10, 2026

Journals on AFIRMASI

Leveraging AI and Adaptive Scaffolding to Enhance Self-Regulated Learning and Career Decision-Making: A Comprehensive Review
April 29, 2026
Self-Regulated Learning, Motivation, and Career Decision-Making: Effects of the SCORE Intervention Versus Traditional Approaches
April 29, 2026
The Psychological Architecture of Career Decision-Making: Mechanisms Mediating the SCORE Framework
April 29, 2026
The Paradox of AI in Educational Frameworks: Enhancing Student Autonomy While Risking Dependency
April 29, 2026
While career interventions show lasting benefits, real-life transfer is limited and mixed
April 29, 2026
Data Sovereignty and the Village: An Ethnographic View of Digital Equity, Privacy, and Local Wisdom
March 25, 2026
Empowering Teachers Before Deploying Technology: Why Educator Understanding is Essential for Effective AI Integration
March 5, 2026
Educators’ and Local Policymakers’ Interpretation and Trust of AI-Generated Recommendations in High-Uncertainty Environments
April 29, 2026
AI-Based Education Policies in Indonesia: Infrastructure Gaps and Governance Misalignment
April 29, 2026
AI-Assisted Teacher Allocation Models: Overcoming Shortages in 3T Regions Compared to Traditional Policy Mechanisms
April 29, 2026
Structural Factors Determining Whether AI Becomes an Equalizing or Stratifying Force in Frontier Education Systems
April 29, 2026
Decentralized Governance and the Adoption of AI-Driven Education Policy Tools in Indonesian Districts
April 29, 2026
AI-Driven Data Systems: Enhancing Evidence-Based Decision-Making in Low-Capacity Education Bureaucracies
April 29, 2026