Evidence map›Paper›PMID 39605574›Full record

ArticlebioRxiv : the preprint server for biology2024

A ChatGPT Assisted Reading Protocol for Undergraduate Research Students.

Marcus Sambar, Gonzalo R Vázquez, Anne V Vázquez, Frank X Vázquez

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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

4 authors.

Marcus SambarDepartment of Chemistry, St. John's University, Queens, NY 11439, USA.
Gonzalo R VázquezDepartment of Chemistry, St. John's University, Queens, NY 11439, USA.
Anne V VázquezDepartment of Chemistry, St. John's University, Queens, NY 11439, USA.ORCID 0009-0001-3446-9291
Frank X VázquezDepartment of Chemistry, St. John's University, Queens, NY 11439, USA.ORCID 0000-0002-2157-3823

Funding

Multiscale Modeling of Dynamin Induced Membrane FissionSC2GM131992 · NIGMS · ST. JOHN'S UNIVERSITY · PI VAZQUEZ, FRANCISCO X. · 2019 to 2021
$492k
NIGMS NIH HHS SC2 GM131992
6 · The paper itself

Abstract

A major challenge for undergraduate students is reading scientific literature. This is especially true in biophysics, where many of the concepts may not have been covered in undergraduate courses. Students can become overwhelmed, which may lead to less overall engagement with the scientific literature. In response, we have developed a guided reading protocol that combines pre-reading strategies, structured notetaking, and ChatGPT to help students clarify unfamiliar concepts in an interactive way. To test the protocol, participants in this study were given an initial survey to determine their experience with reading scientific literature. After this they were given an abridged biophysics paper and the protocol. The ChatGPT transcripts were analyzed using open coding and the students were given a post-study survey. We found most students did not appear to regularly engage with the literature, possibly due to content barriers they encountered. Analyzing their transcripts, we observed that students asked for definitions, explanations, summaries, and simplifications. Overall, students reported that using ChatGPT was a positive experience and they expected to use ChatGPT in the future. From this work, we expect this new protocol may be a way to keep novice students from becoming discouraged when reading scientific papers and keep them engaged with the current literature.

Indexed as

AIChatGPTreadingscientific literatureundergraduate research

Identifiers

PMID39605574
PMCPMC11601371

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.