Assessing Dependency and Impact of Artificial Intelligence on Learning Among Students

  • Swati Bansal
  • Dr. Gaurav Kumar
  • Mr. Sumit Singh
  • et al.
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Abstract

The rapid integration of generative artificial intelligence (GenAI) tools such as ChatGPT has transformed highereducation, prompting concerns about student dependency and its effects on learning. This study aimed to assessundergraduate students’ dependency on artificial intelligence and its perceived impact on learning at S.G.T.University, India.A quantitative descriptive cross-sectional survey design was employed. Data were collected via a self-structuredGoogle Form questionnaire from 99 respondents using non-probability convenience sampling. After removing oneduplicate record, the final analytic sample comprised 98 valid consenting participants (n=98). The instrumentincluded demographic details, AI usage patterns, five 5-point Likert-scale items measuring dependency andlearning impact, and an overall opinion statement. Descriptive statistics, Cronbach’s alpha, and Spearman rank-order correlations were computed using Microsoft Excel and JAMOVI.Results showed that 94.9% of students used AI tools for academics, with ChatGPT being the most preferred(73.5%). The primary purpose was understanding difficult concepts (56.3%). Highest agreement was recorded for“AI saves time” (M=3.67 ± 1.24) and “AI helps understand difficult topics” (M=3.62 ± 1.26). While 55.1%endorsed AI as a supportive learning tool, moderate concern existed regarding reduced independent thinking(M=3.48 ± 1.22). The Likert scale demonstrated good internal consistency (Cronbach’s α=0.821). Significantpositive correlations emerged between dependency and positive learning impact (ρ=0.492, p<0.001), frequency ofuse and impact (ρ=0.401, p<0.001), and frequency of use and dependency (ρ=0.249, p=0.013).The findingshighlight exceptionally high GenAI adoption among first-year students alongside predominantly positiveperceptions tempered by dependency risks.Institutions should implement AI literacy training and evidence-based guidelines to maximise benefits whilesafeguarding critical thinking and academic integrity. This study offers timely insights for responsible GenAIintegration in undergraduate education.

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APA

Swati Bansal, Dr. Gaurav Kumar, Mr. Sumit Singh, Renu Parkash, Piyush Kant, & Santosh Kumar. (2026). Assessing Dependency and Impact of Artificial Intelligence on Learning Among Students. The Bioscan, 21(2), 1748–1757. https://doi.org/10.63001/tbs.2026.v21.i02.s.i(2).pp1748-1757

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