Calculated Risks: Evaluating the Internal and Systemic Drivers of Academic Dishonesty

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{"abstract":"The rapid expansion of digital learning tools and the shifting landscape of higher education have created significant challenges for maintaining academic integrity. This narrative review explores the \"judgment-action gap,\" where a weak moral identity and external systemic pressures often undermine a student’s intellectual understanding of ethical behavior. Utilizing a structured search across electronic scholarly databases, including ERIC, IEEE Xplore, and PubMed, this study synthesizes literature from 2015 to 2025 to understand the psychological \"why\" behind dishonest behavior. Key internal drivers, such as the failure to integrate academic honesty into one’s core self-identity, are examined alongside \"moral neutralization\" techniques where students frame misconduct as a \"necessary evil\" for academic survival. Furthermore, the paper evaluates how external factors, including intense competition for grades, parental expectations, and the \"bureaucratization\" of learning, alter a student's perception of risk and reward. Special attention is paid to the digital shift, where the absence of physical oversight and the emergence of Generative AI have reshaped cheating into a situational response to digital affordances. By evaluating these drivers, this paper argues that academic misconduct is not merely a logistical failure of monitoring but a complex ethical struggle with profound implications for long-term professional integrity. Ultimately, the review suggests that institutions must transition from a culture of surveillance toward \"re-humanized\" environments that utilize authentic assessments and foster internalized ethical responsibility.","abstract_source":"original","authors":["Mary Shaira Christa P. Zapanta-Ribu"],"date":"2026-04-15","doi":"10.70838/pemj.550207","id":7622,"issue":2,"journal":{"issn":"2822-4353","name":"Psychology and Education: A Multidisciplinary Journal"},"pdf_sha256":"0bc2c7e694ac3e47dd95e8bda4530cff741f57d099e597778bd54c89d981cf9c","schema":"scimatic-article/1","title":"Calculated Risks: Evaluating the Internal and Systemic Drivers of Academic Dishonesty","volume":55}

Check it yourself

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

printf '%s' "$(curl -s https://scimatic.org/nft/articles/7622.json | jq -r .canonical_record)" | sha256sum

2. The hash stored on chain (contentHash(7622)):

curl -s https://rpc.scimatic.net -H 'content-type: application/json' \
  -d '{"jsonrpc":"2.0","id":1,"method":"eth_call","params":[{"to":"0x0E596B4bb924937aA35D9b342A90347ed6F05eF8","data":"0xf3e0c2900000000000000000000000000000000000000000000000000000000000001dc6"},"latest"]}'

The two must be equal (the second with a 0x in front).