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An Assessment of Student-Researcher Satisfaction with the Use of Artificial Intelligence in Thesis Writing

Jena Mae Fatagani-Valerio, Jay Renee Valerio, Jonalyn Balancio, Jonald Pimentel
Psychology and Education: A Multidisciplinary Journal · 2025-09-09 · DOI 10.70838/pemj.460706
Token #6355
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Token#6355 of SciMatic Articles (ERC-1155), fixed supply 1,000,000
Contract0x0E596B4bb924937aA35D9b342A90347ed6F05eF8
Mint transaction0x7721bfb7fb53d1947a8d6b1e04c29d14012593ca4bb31d5af2e0338189b3c5fb · block 12107918
Minted2026-10-02 08:35 UTC
Hash on chain0xbe808fe4caf17fc5fd58c36358d73d2c03f46b58266af239995a0404348f9b21
SHA-256 of the record0xbe808fe4caf17fc5fd58c36358d73d2c03f46b58266af239995a0404348f9b21
Article today Matches the anchored record.

Allocation at minting

HolderWalletMintedHolds now
SciMatic (10%) 0xc35709AB…277732 100,000 100,000
Jena Mae Fatagani-Valerio 0x29dBc041…e1279F 225,000 225,000
Jay Renee Valerio 0x82bd1753…7eB63E 225,000 225,000
Jonalyn Balancio 0x436557Bf…767dad 225,000 225,000
Jonald Pimentel 0x2fec89B2…9c0ac7 225,000 225,000

The anchored record

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{"abstract":"The rapid advancement of artificial intelligence (AI) and its increasing integration into academic workflows necessitate a deeper understanding of its impact on student learning and experience. This research explores the use of AI tools in undergraduate thesis writing, focusing on student satisfaction and the factors influencing student perceptions. By examining the experiences of 121 students (83 BSIT, 38 BTVTEd) at Sultan Kudarat State University, this research contributes to the growing body of knowledge on the role of AI in higher education. Overall satisfaction with AI tools was generally high. However, a more nuanced analysis revealed no significant differences between BSIT and BTVTEd students across various satisfaction measures (overall satisfaction, ease of use, enjoyable experience), as indicated by Mann-Whitney U tests. Lower ratings for reliability, interface, and validity/plagiarism, however, suggest areas for tool improvement, despite high ratings for usability, functionality, features, and performance. A linear regression analysis, exploring the correlation between satisfaction and thesis outcomes, yielded a low R-squared (0.0512), indicating limited explanatory power. Surprisingly, a significant negative correlation emerged between thesis organization and overall satisfaction, warranting further investigation. Other thesis outcome measures showed no significant relationship with satisfaction. These findings highlight the need for further research to identify additional factors influencing satisfaction and to explore the unexpected negative correlation, potentially through qualitative methods. This research contributes valuable insights into student experiences with AI in thesis writing, informing future tool development and pedagogical approaches.","abstract_source":"original","authors":["Jena Mae Fatagani-Valerio","Jay Renee Valerio","Jonalyn Balancio","Jonald Pimentel"],"date":"2025-09-09","doi":"10.70838/pemj.460706","id":6355,"issue":7,"journal":{"issn":"2822-4353","name":"Psychology and Education: A Multidisciplinary Journal"},"pdf_sha256":"524afd5f1f8fe09d0263608d59b8e1044f45176028c46ddd4e39c68a9e2e0bee","schema":"scimatic-article/1","title":"An Assessment of Student-Researcher Satisfaction with the Use of Artificial Intelligence in Thesis Writing","volume":46}

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  -d '{"jsonrpc":"2.0","id":1,"method":"eth_call","params":[{"to":"0x0E596B4bb924937aA35D9b342A90347ed6F05eF8","data":"0xf3e0c29000000000000000000000000000000000000000000000000000000000000018d3"},"latest"]}'

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