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Prompt Details

Model
Chat - (gpt-5.2)
Token size
334
Example input
[TOPIC]: User Adoption of Metaverse Platforms in Educational Settings [FIELD]: Educational Technology, Metaverse Studies [KEYWORDS]: metaverse, virtual reality, education, user adoption, student engagement [METHOD]: Quantitative survey, Mixed methods [REFERENCES]: Early stage, no references yet
Example output
Section 1: Research Gap Analysis Your research examines metaverse adoption in educational settings. Key gaps: limited empirical studies on student learning outcomes in metaverse environments, insufficient research on institutional adoption barriers, lack of longitudinal engagement studies. Section 2: Optimized Search Queries 1. metaverse AND education AND adoption 2. virtual world AND learning AND acceptance 3. immersive technology AND classroom AND engagement Section 3: Recommended Prior Studies 1. Park, S. & Kim, Y. 2024. Metaverse adoption in higher education: TAM perspective. Computers & Education, 195, 104815. Relevance: Applies Technology Acceptance Model to university metaverse adoption Method: Quantitative survey N=456 Findings: Perceived usefulness predicts adoption 2. Lee, H. et al. 2023. Virtual reality in K-12 education: Systematic review. Educational Technology Research, 71, 456-489. Relevance: Comprehensive VR implementation review Method: Systematic review 87 studies Findings: Identifies cost and training barriers Section 4: Literature Categories Theoretical: TAM, UTAUT frameworks Methodological: Survey designs, mixed methods Empirical: Case studies in universities Contrasting: Benefits vs challenges Section 5: Database Strategy Primary: Scopus, Web of Science, ERIC Secondary: IEEE Xplore, Google Scholar Section 6: Key Researchers Dr. Sarah Park Seoul National, Dr. Michael Chen Stanford VR Lab
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Academic Literature Finder For Chatgpt

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GPT-5.2
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Find precise academic prior research for your thesis/paper. Generates comprehensive literature review strategies, curated reference lists with full citations, research gap analysis, and search query optimization. Perfect for graduate students, researchers, and academics building systematic literature reviews. Includes APA citations, methodological matching, and database recommendations.
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