What does this research mean for the field?

Students with mastery-oriented goals integrate generative AI into their self-regulated learning processes more effectively than performance-oriented and low-goal learners. Novelty: ClaimNovelty.NOVEL_FINDING. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

The study aims to examine how students' achievement goal orientations affect their use of generative AI tools during problem-solving tasks.

March 10, 2026British Journal of Educational Technology4 citations

Students' Use Patterns of Generative AI During Problem-Solving in Intelligent Learning Systems

Students' use patterns of generative artificial intelligence during problem‐solving in an intelligent learning system: Achievement goal orientation matters

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Authors

TWTingting Wang SLShan Li SLS. Li

Discussion

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Overview

Reveals the influence of achievement goal orientation on students' GenAI use during problem-solving, indicating a need for tailored support.

Key Points

The study aims to examine how students' achievement goal orientations affect their use of generative AI tools during problem-solving tasks.
114 university students participated by completing a nutrition recommendation task.
Students' achievement goal orientations were assessed using a self-report scale before the task.
Learners' self-regulated learning activities and GenAI interactions were logged during the task.
Hierarchical clustering analysis was performed to identify distinct learner profiles.
Mastery-oriented and performance-oriented learners outperformed low-goal learners.
No significant differences in GenAI usage frequency were found across learner profiles.
Mastery-oriented learners integrated GenAI into cognitive activities such as execution and evaluation.
Performance-oriented learners mainly used GenAI for initial decision-making.
Low-goal learners showed a reliance on GenAI for metacognitive tasks like monitoring and reflection.

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Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/69af94e870916d39fea4c021 https://doi.org/10.1111/bjet.70059

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March 10, 2026British Journal of Educational Technology4 citations

Students' Use Patterns of Generative AI During Problem-Solving in Intelligent Learning Systems

Students' use patterns of generative artificial intelligence during problem‐solving in an intelligent learning system: Achievement goal orientation matters

View Full Paper

Authors

TWTingting Wang SLShan Li SLS. Li

Discussion

Member takes

Overview

Reveals the influence of achievement goal orientation on students' GenAI use during problem-solving, indicating a need for tailored support.

Key Points

The study aims to examine how students' achievement goal orientations affect their use of generative AI tools during problem-solving tasks.
114 university students participated by completing a nutrition recommendation task.
Students' achievement goal orientations were assessed using a self-report scale before the task.
Learners' self-regulated learning activities and GenAI interactions were logged during the task.
Hierarchical clustering analysis was performed to identify distinct learner profiles.
Mastery-oriented and performance-oriented learners outperformed low-goal learners.
No significant differences in GenAI usage frequency were found across learner profiles.
Mastery-oriented learners integrated GenAI into cognitive activities such as execution and evaluation.
Performance-oriented learners mainly used GenAI for initial decision-making.
Low-goal learners showed a reliance on GenAI for metacognitive tasks like monitoring and reflection.

Ask AI

Helpful

Bookmark

View Full Paper

Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/69af94e870916d39fea4c021 https://doi.org/10.1111/bjet.70059

Ask AI

Helpful

Bookmark

View Full Paper