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Doctoral Dissertation Research - Academic Overview

EdTech Fatigue, Motivation Architecture,
and the Bifurcated Learning Model

A dissertation study examining whether a purpose-built platform can simultaneously measure and reduce EdTech Fatigue while improving student learning outcomes.

Abstract

This explanatory sequential mixed-methods study investigates the relationship between educational technology platform consolidation and teacher EdTech Fatigue (EFS-12) in K-12 settings. Drawing on the Technology Acceptance Model (TAM) framework, this research examines whether Gregarious - a unified learning OS designed to replace 6 discrete platforms - produces measurable reductions in teacher-reported fatigue while maintaining or improving student academic growth as measured by the Growth Above Replacement (GAR) metric.

Phase 1 (quantitative) will analyze pre/post EFS-12 scores, sprint completion rates, and GAR distributions across pilot schools (N target = 200 teachers). Phase 2 (qualitative) will employ semi-structured interviews with purposively sampled teachers showing extreme EFS-12 trajectories to explain quantitative patterns. Integration of strands will follow a joint display approach.

Data collection is pending pilot school enrollment. This study will contribute the first empirical validation of the EFS-12 instrument in a live platform context and introduce the bifurcated mastery/studio model as a novel motivation architecture framework. Preliminary findings will be reported as pilot data becomes available.

Keywords
EdTech fatigue, TAM, mixed methods, motivation architecture, mastery learning, GAR
IRB Protocol
#2025-0847 - Approved. Designed for FERPA compliance. Data anonymized.
Target Journal
Computers and Education (IF: 11.2). Submission: Winter 2026.
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Research Design

Explanatory Sequential Mixed Methods. Quantitative Phase 1 guides qualitative Phase 2. Quant findings explain WHAT; qual interviews explain WHY.

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Theoretical Framework

Technology Acceptance Model (Davis, 1989) - Perceived Usefulness and Perceived Ease of Use as predictors of adoption. Extended with EdTech Fatigue as a third construct.

Research Questions

RQ1: Does Gregarious reduce EFS-12 scores at 8 weeks? RQ2: What TAM factors predict sustained teacher adoption? RQ3: How do teachers with low EFS scores describe their experience?

Study Framework: Quantitative then Qualitative

Platform Use
Gregarious deployment Pilot schools, 8 weeks
EFS-12 + TAM
Pre/post quantitative surveys, target n=200+
GAR + Sprint Data
Continuous student outcome collection
Interviews
Purposive sample Extreme EFS cases
Integration
Joint display Dissertation + publication

Research Timeline

Phase 1: Instrument DevelopmentComplete
Fall 2024
\u2022EFS-12 item generation via expert panel (n=7 teachers, n=3 researchers)
\u2022Cognitive interviews to refine item clarity
\u2022Pilot reliability testing (Cronbach alpha target: 0.85+)
\u2022IRB application submitted and approved (#2025-0847)
Phase 2: Platform IntegrationComplete
Spring 2025
\u2022EFS-12 embedded as 6-item weekly pulse (split-half administration)
\u2022TAM survey integrated at onboarding and 8-week follow-up
\u2022Quant dashboard built for real-time EFS monitoring
\u2022Data pipeline to anonymized research dataset
3
Phase 3: Pilot Data CollectionIn Progress
Fall 2025 - Spring 2026
\u2022Target: 47 schools across 3 districts for pilot enrollment
\u2022Pre/post EFS-12 administration planned (8-week intervals)
\u2022GAR and sprint completion data pipeline ready for collection
\u2022Target: 200+ teacher participants for quantitative phase
4
Phase 4: Qualitative PhaseUpcoming
Summer 2026
\u2022Semi-structured interviews with extreme-score teachers (high/low EFS)
\u2022Interview protocol based on quantitative findings
\u2022Member checking and triangulation
\u2022Integration of qual and quant strands
5
Phase 5: Dissertation and PublicationUpcoming
Fall 2026
\u2022Dissertation defense scheduled
\u2022Manuscript submission: Computers and Education
\u2022SBIR application to IES/ED upon solicitation opening
\u2022Conference presentation: AERA 2027

Interested in Research Collaboration?

We welcome inquiries from IES, AERA, and university research teams. Open to data sharing agreements, co-PI arrangements, and collaborative study design.

IRB #2025-0847 - EdTech Fatigue Scale (EFS-12) - TAM Framework - Explanatory Sequential Mixed-Methods