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Assessing Students’ Acceptance of Generative AI Tools in Education: A Technology Acceptance Model Approach

Kevin Caratiquit, Felix Arcilla
Psychology and Education: A Multidisciplinary Journal · 2026-09-15 · DOI 10.70838/pemj.620806
Token #10255
✓ Verified on SciChain. The record below hashes to exactly the content hash stored on chain for token #10255.
Token#10255 of SciMatic Articles (ERC-1155), fixed supply 1,000,000
Contract0x0E596B4bb924937aA35D9b342A90347ed6F05eF8
Mint transaction0xb71907d8f725f17e54815dbd32038a0fb95f398bba33ed16c0c4ed2204a5b8bc · block 12113138
Minted2026-10-02 15:50 UTC
Hash on chain0x54c6338a284f7600dd500854f0a6dbfea6943acd94038e36f4abda3b50c248c6
SHA-256 of the record0x54c6338a284f7600dd500854f0a6dbfea6943acd94038e36f4abda3b50c248c6
Article today Matches the anchored record.

Allocation at minting

HolderWalletMintedHolds now
SciMatic (10%) 0xc35709AB…277732 100,000 100,000
Kevin Caratiquit 0x647b4D0F…39bC8a 450,000 450,000
Felix Arcilla 0x85528c37…236299 450,000 450,000

The anchored record

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{"abstract":"The increasing use of generative artificial intelligence (AI) in education has created opportunities to enhance teaching and learning, highlighting the need to understand the factors influencing students' acceptance of these technologies. This study examined the acceptance of generative AI tools among junior and senior high school students using the Technology Acceptance Model (TAM). A cross-sectional survey was conducted among 205 students, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results supported all hypothesized relationships in the proposed model. Perceived ease of use positively influenced perceived usefulness and attitude toward using, while perceived usefulness significantly affected attitude toward using and behavioral intention. In addition, attitude toward using positively influenced both behavioral intention and actual system use, with behavioral intention emerging as the strongest predictor of actual system use. These findings support the applicability of the Technology Acceptance Model in explaining generative AI acceptance among junior and senior high school students, extending its application within the basic education context. The study provides empirical evidence that can assist educational institutions in developing policies and instructional strategies that promote the effective, ethical, and responsible integration of generative AI to enhance student engagement and learning outcomes.","abstract_source":"original","authors":["Kevin Caratiquit","Felix Arcilla"],"date":"2026-09-15","doi":"10.70838/pemj.620806","id":10255,"issue":8,"journal":{"issn":"2822-4353","name":"Psychology and Education: A Multidisciplinary Journal"},"pdf_sha256":"3b248b813b38862dd70c80712af16fee0a318f5c34bda44781b3e7b1f8b0697c","schema":"scimatic-article/1","title":"Assessing Students’ Acceptance of Generative AI Tools in Education: A Technology Acceptance Model Approach","volume":62}

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  -d '{"jsonrpc":"2.0","id":1,"method":"eth_call","params":[{"to":"0x0E596B4bb924937aA35D9b342A90347ed6F05eF8","data":"0xf3e0c290000000000000000000000000000000000000000000000000000000000000280f"},"latest"]}'

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