Analysis of the Influence of the Use of Artificial Intelligence (AI) on Students' Critical Thinking Abilities in Learning

This study examines how Artificial Intelligence (AI) use affects students' critical thinking skills in learning. The study uses a quantitative, explanatory research design. The study population consisted of students in the Economics Education Study Program who used AI-based applications for learning. The study collected data through a five-point Likert-scale questionnaire from 64 respondents who met the research criteria. The researchers analyzed the data using validity and reliability tests, assumption tests, a…

Analysis of the Influence of the Use of Artificial Intelligence (AI) on Students' Critical Thinking Abilities in Learning
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In brief

Researchers surveyed 64 students in an Economics Education Study Program who used AI-based applications for learning. Using a five-point Likert questionnaire and simple linear regression in SPSS, they tested whether AI use predicted critical thinking skills. The analysis found a positive, statistically significant relationship.

The finding matters because schools and universities are deciding how to integrate AI tools into teaching, and the result suggests that appropriate use may support analysis, evaluation, and problem solving. Most of the variation in critical thinking, 74%, is attributed to other factors, so AI use is only one part of the picture.

Main points

  1. The design was quantitative and explanatory, with data gathered through a five-point Likert-scale questionnaire.
  2. The sample was 64 respondents from an Economics Education Study Program who met the research criteria.
  3. The t-test gave t = 4.670 with p = 0.000, and the regression coefficient was 0.431.
  4. The R-square of 0.260 means AI use accounts for 26% of variation in critical thinking, leaving 74% to other factors.

The gain

Among 64 Economics Education students, greater use of AI-based learning applications was significantly associated with stronger critical thinking skills, explaining about 26% of the variation.

The rundown

The study population was limited to students in one program, Economics Education, who already used AI-based applications for learning. Respondents were included if they met the research criteria.

Data analysis involved validity and reliability tests, assumption tests, and simple linear regression. The regression coefficient of 0.431 and t = 4.670 (p = 0.000) indicate a statistically significant positive effect in the model.

The authors conclude that appropriate AI use can support students' ability to analyze, evaluate, and solve problems, while noting that other factors account for 74% of the variation.

Sources

  1. Peer-reviewedEducational Journal of Learning Technology2026-10-14

The debate