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- PaperEdArXiv (OSF Preprints)21 Jul 2026
Changes in Motivational Beliefs and Science Identity During an AI-Assisted Reading of Primary Scientific Literature
Sebastian Alvarado, Bradley Bergey, Leif Philips, Maral Tajerian
A mixed-methods study of 27 undergraduate biology students using the AI tool Scite for reading primary scientific literature found medium-sized increases in intrinsic, utility, and attainment values and science identity, alongside an unexpected rise in perceived costs. Students rated Scite highly useful for identifying and synthesizing research, but concerns about reliability and ease of use emerged.
Original abstract
Reading primary scientific literature is essential yet challenging for undergraduate science students, who often report low confidence and difficulty navigating complex texts. Guided by Expectancy-Value Theory, this mixed-methods study examined changes in students' motivational beliefs across a biology literature review assignment in which students used Scite, an AI-powered citation analysis tool, including science identity; self-efficacy; and intrinsic, utility, and attainment values and perceived costs of reading primary scientific literature. Students enrolled in a 200-level Foundations of Research in Biology course were assigned a structured literature review on pharmacological interventions for a disease of their choice, using Scite.ai to locate, evaluate, and synthesize primary research. A racially diverse sample of 27 undergraduate biology students (48% women, 42% first-generation college students) completed a posttest questionnaire, including a subsample (n = 21) with matched pretest questionnaire responses. Paired-sample t tests revealed statistically significant, medium-sized increases in intrinsic, utility, and attainment values and science identity, alongside an unexpected rise in perceived costs (d = .51-.65); results revealed a small nonsignificant increase in self-efficacy. Students rated Scite as highly useful for identifying, summarizing, and synthesizing research. Thematic analysis of open-ended responses revealed the salience of perceived utility, enjoyment, cognitive support, and credibility, alongside concerns about reliability, ease of use, and occasional identity-related conflicts. Findings suggest that AI-assisted engagement with PSL carries complex motivational implications, warranting controlled investigation.