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Artificial Intelligence: Its Influence on Academic Performance of Grade 11 Senior High School Students

Asmalia Dida-Agun, Carlito Abarquez
Psychology and Education: A Multidisciplinary Journal · 2025-09-03 · DOI 10.70838/pemj.460408
Token #6316
✓ Verified on SciChain. The record below hashes to exactly the content hash stored on chain for token #6316.
Token#6316 of SciMatic Articles (ERC-1155), fixed supply 1,000,000
Contract0x0E596B4bb924937aA35D9b342A90347ed6F05eF8
Mint transaction0xf2059118d8716f9bf30a2af3db25bbf03cf1471ba67653bdd4cb22609ec2c946 · block 12107878
Minted2026-10-02 08:32 UTC
Hash on chain0x03f9ad6b0332992dc5ef3719492b418cb44dc0fa87e062764ea0340a25939980
SHA-256 of the record0x03f9ad6b0332992dc5ef3719492b418cb44dc0fa87e062764ea0340a25939980
Article today Matches the anchored record.

Allocation at minting

HolderWalletMintedHolds now
SciMatic (10%) 0xc35709AB…277732 100,000 100,000
Asmalia Dida-Agun 0x9060Cac6…AdC762 450,000 450,000
Carlito Abarquez 0x837a87D5…5DC510 450,000 450,000

The anchored record

Canonical JSON (keys sorted, no spaces, UTF-8). Its SHA-256 is the hash on chain.

{"abstract":"This study investigated the influence of artificial intelligence (AI) on the academic performance of students enrolled in selected External Units of Mindanao State University (MSU) during the first semester of the academic year 2024–2025. Employing a quantitative, descriptive-correlational research design, data were gathered through a structured survey questionnaire. Descriptive statistics were used to analyze demographic variables such as age, sex, academic strand, and general average grades. Pearson’s r-correlation coefficient assessed the relationship between AI use and academic performance, while linear regression analysis was conducted to identify potential predictors of academic success. Findings revealed that students actively engaged with various AI tools to support their educational endeavors and reported perceived enhancements in their learning behaviors and motivational levels. Despite these positive perceptions, statistical analysis indicated no significant correlation between AI influence and students' academic performance. Furthermore, variables such as age, sex, academic strand and the use of AI applications did not significantly predict academic outcomes. The results suggested that while AI technologies contributed to shaping learning behaviors and motivational strategies, their direct effect on measurable academic success remains inconclusive.","abstract_source":"original","authors":["Asmalia Dida-Agun","Carlito Abarquez"],"date":"2025-09-03","doi":"10.70838/pemj.460408","id":6316,"issue":4,"journal":{"issn":"2822-4353","name":"Psychology and Education: A Multidisciplinary Journal"},"pdf_sha256":"72c98ee50affe97521fce84121a8fad4710c79f29ac3089cf00ade5ba3841998","schema":"scimatic-article/1","title":"Artificial Intelligence: Its Influence on Academic Performance of Grade 11 Senior High School Students","volume":46}

Check it yourself

1. The record, from the token's own metadata:

printf '%s' "$(curl -s https://scimatic.org/nft/articles/6316.json | jq -r .canonical_record)" | sha256sum

2. The hash stored on chain (contentHash(6316)):

curl -s https://rpc.scimatic.net -H 'content-type: application/json' \
  -d '{"jsonrpc":"2.0","id":1,"method":"eth_call","params":[{"to":"0x0E596B4bb924937aA35D9b342A90347ed6F05eF8","data":"0xf3e0c29000000000000000000000000000000000000000000000000000000000000018ac"},"latest"]}'

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