Improving learning outcomes in advanced mathematics for underprepared university students through AI-driven educational tools

This study investigates the impact of artificial intelligence (AI) tools on the academic performance of university students with insufficient mathematical preparation enrolled in higher mathematics courses. Utilizing a quasi-experimental design with pre- and post-testing, the research explores the effectiveness of AI-based platforms such as SOWISO, ChatGPT, and WolframAlpha in supporting underprepared learners. The study incorporates both quantitative and qualitative analyses and evaluates the mediating roles of academic motivation and attitudes toward AI, as well as the moderating effect of digital literacy and instructional support. Results indicate that AI interventions significantly improve learning outcomes, especially when integrated with structured pedagogical guidance and platforms that offer step-by-step feedback. The findings highlight the value of interactive AI environments in reducing academic anxiety, promoting learner autonomy, and fostering equitable access to advanced mathematical instruction. Implications for inclusive pedagogy and the role of AI in transforming higher education are discussed, along with recommendations for future research and practice.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-23
DOI
https://doi.org/10.5281/zenodo.15519390
Primary Topic
Physiological and biochemical adaptations
Type
article
Field-Weighted Citation Impact
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article

Improving learning outcomes in advanced mathematics for underprepared university students through AI-driven educational tools

Zenodo (CERN European Organization for Nuclear Research)
Physiological and biochemical adaptations
article

Improving learning outcomes in advanced mathematics for underprepared university students through AI-driven educational tools

article en

Abstract

This study investigates the impact of artificial intelligence (AI) tools on the academic performance of university students with insufficient mathematical preparation enrolled in higher mathematics courses. Utilizing a quasi-experimental design with pre- and post-testing, the research explores the effectiveness of AI-based platforms such as SOWISO, ChatGPT, and WolframAlpha in supporting underprepared learners. The study incorporates both quantitative and qualitative analyses and evaluates the mediating roles of academic motivation and attitudes toward AI, as well as the moderating effect of digital literacy and instructional support. Results indicate that AI interventions significantly improve learning outcomes, especially when integrated with structured pedagogical guidance and platforms that offer step-by-step feedback. The findings highlight the value of interactive AI environments in reducing academic anxiety, promoting learner autonomy, and fostering equitable access to advanced mathematical instruction. Implications for inclusive pedagogy and the role of AI in transforming higher education are discussed, along with recommendations for future research and practice.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 53%
Physiological and biochemical adaptations
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