Learner Factors and Academic Performance: The Roles of Motivation, Digital Distraction, Critical Thinking, and Self-directed Learning

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{"abstract":"The increasing integration of digital technologies in higher education has reshaped students’ learning behaviors, raising concerns about academic motivation, digital distraction, higher-order thinking, and self-directed learning. Guided by Self-Determination Theory, Cognitive Load Theory, Information Processing Theory, and Self-Regulated Learning Theory, this study examined the levels of academic motivation, digital distraction, critical thinking, and self-directed learning and their relationships with academic performance among college students. Using a descriptive correlational design, data were collected from 189 higher education students through validated instruments with acceptable reliability, and academic performance was measured using students’ General Weighted Average (GWA). Descriptive statistics, Pearson’s correlation, and multiple regression analyses were conducted after verifying the relevant statistical assumptions. The results indicated high to very high levels of academic motivation, critical thinking, and self-directed learning, along with moderate digital distraction. Correlation analysis revealed no significant bivariate relationships between student-related variables and academic performance. However, regression analysis identified digital distraction as a significant predictor of academic performance when controlling for other factors, although it explained only a small proportion of variance. These findings suggest that digital engagement may exert context-dependent effects rather than uniformly negatively influencing academic outcomes. Overall, this study highlights the multifactorial nature of academic performance in technology-mediated learning environments and underscores the importance of fostering digital self-regulation, mindful technology use, and higher-order learning skills in higher education.","abstract_source":"original","authors":["Charlie Anselmo","Jason Cahigas","Julius Tolentino","Ryan Christopher Flores","Crisel Macarubbo","Abigail Cabia","Irish Narag","Grace Ann Magsino"],"date":"2026-03-23","doi":"10.70838/pemj.530704","id":7426,"issue":7,"journal":{"issn":"2822-4353","name":"Psychology and Education: A Multidisciplinary Journal"},"pdf_sha256":"9437b70956152a47d2e9a132a973c3ec430a4079271070f926ee4ebb3ebd2067","schema":"scimatic-article/1","title":"Learner Factors and Academic Performance: The Roles of Motivation, Digital Distraction, Critical Thinking, and Self-directed Learning","volume":53}

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

printf '%s' "$(curl -s https://scimatic.org/nft/articles/7426.json | jq -r .canonical_record)" | sha256sum

2. The hash stored on chain (contentHash(7426)):

curl -s https://rpc.scimatic.net -H 'content-type: application/json' \
  -d '{"jsonrpc":"2.0","id":1,"method":"eth_call","params":[{"to":"0x0E596B4bb924937aA35D9b342A90347ed6F05eF8","data":"0xf3e0c2900000000000000000000000000000000000000000000000000000000000001d02"},"latest"]}'

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