Evidence map›Paper›PMID 40372075›Full record

ArticleBiochemistry and molecular biology education : a bimonthly publication of the International Union of Biochemistry and Molecular Biology

Learning Tools Using ChatGPT in the Biochemistry Class: Creating Notes and Performance on Exams.

Ana Roman, Maria Simaitis, Kate Sheely, Yotam M Roth, John T Tansey, John Cogan

Abstract read
In one paragraph

Article in Biochemistry and molecular biology education : a bimonthly publication of the International Union of Biochemistry and Molecular Biology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Learning Tools Using ChatGPT in the Biochemistry Class: Creating Notes and Performance on Exams.Biochemistry and molecular biology education : a bimonthly publication of the International Union of Biochemistry and Molecular Biology
    Article
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

6 authors.

Ana RomanThe Ohio State University, Columbus, Ohio, USA.ORCID 0009-0005-2959-3916
Maria SimaitisThe Ohio State University, Columbus, Ohio, USA.
Kate SheelyThe Ohio State University, Columbus, Ohio, USA.
Yotam M RothThe Ohio State University, Columbus, Ohio, USA.
John T TanseyDepartment of Chemistry, Program in Biochemistry and Molecular Biology, Otterbein University, Westerville, Ohio, USA.
John CoganDepartment of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ChatGPT has emerged as a popular choice in education that has transformed the experience for both teachers and students. This study investigates the performance of ChatGPT in aiding learning in the biochemistry classroom in two ways. We sought to determine how effective ChatGPT 3.5 was in generating study materials for an introductory biochemistry course. A lecture was delivered in class and transcribed. The resulting transcript was curated, then submitted to ChatGPT 3.5 to generate a summary, a set of notes, and an outline. Each artifact was verified and given to students to help prepare for a quiz. Students were asked about the use of AI-generated materials compared to other study materials. Results were bimodal for the AI-generated materials, with some students indicating that the materials were useful while others preferred traditional study materials such as the text or class notes. We also compared the performance of ChatGPT on open-note biochemistry exams that students had taken. The exams were completed by ChatGPT in two modes: with and without access to external tools. Performance metrics were used to evaluate ChatGPT performance and student responses. The results showed that ChatGPT was unable to pass the exams. This research provides valuable insights into the potential of ChatGPT in educational settings, highlighting strengths and limitations. The implications of these findings may inform the design of future AI-assisted tools and contribute to the ongoing discussions surrounding the integration of AI in education.

Indexed as

BiochemistryEducational MeasurementLearningGenerative Artificial IntelligenceHumansStudentsAIbiochemistryChatGPTlearning toolsundergraduate STEM education

Identifiers

PMID40372075
PMCPMC12290240

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.