Evidence map›Paper›PMID 42117781›Full record

ArticleJournal of microbiology & biology education2026

Survey of student perceptions and use of artificial intelligence when reading primary literature in the biological sciences.

Erin L Zimmer, Michael I Zimmer

Abstract read
In one paragraph

Article in Journal of microbiology & biology education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Erin L ZimmerBiology Department, Lewis University, Romeoville, Illinois, USA.ORCID 0009-0003-6084-4782
Michael I ZimmerDepartment of Biological Sciences, Purdue University Northwest, Hammond, Indiana, USA.ORCID 0009-0008-9852-182X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) tools are increasingly used by students in higher education, yet little is known about how they are applied when reading primary scientific literature. This study investigated how undergraduate biology students use AI while engaging with primary research articles and how such use influences confidence, engagement, and perceived learning. Using a mixed-methods design across two institutions, we collected pre-course surveys assessing prior AI experience and attitudes, weekly self-reported AI usage logs during a semester-long primary literature-based course, and post-course surveys evaluating changes in practices and perceptions. Students entered the course with broad familiarity with generative AI but expressed uncertainty and concern regarding accuracy, ethics, and overreliance. Throughout the semester, students primarily used AI to clarify terminology, methods, figures, and background concepts, with usage patterns evolving toward more targeted and sophisticated prompting. Students also reported increasing awareness of AI limitations and the need for critical evaluation of AI-generated responses. Post-course results indicated increased confidence in analyzing primary data and deeper engagement with the literature, while concerns about overreliance largely diminished. Overall, students viewed AI as a supportive tool that complemented, rather than replaced, their own reasoning. These findings suggest that AI can enhance students' engagement with primary literature when used thoughtfully and underscore the importance of explicit instructional guidance to promote ethical, effective, and critical use of AI in biological science education.

Indexed as

artificial intelligencebiological sciencesprimary literaturescientific literacy

Identifiers

PMID42117781
PMCPMC13520717

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.