Evidence map›Paper›PMID 41744500›Full record

ArticleJournal of microbiology & biology education2026

Not simply "active": identifying types of active-learning tasks in introductory biology.

Benjamin D Jackson, Cristine Donham, Tessa C Andrews

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Bad AI-generated images can be good for teaching visual literacy in biology.Journal of microbiology & biology education · 2026
    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

3 authors.

Benjamin D Jackson *Department of Genetics, University of Georgia, Athens, Georgia, USA.
Cristine Donham *Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, Santa Barbara, California, USA.
Tessa C AndrewsDepartment of Genetics, University of Georgia, Athens, Georgia, USA.ORCID 0000-0002-7008-6853

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Active learning is a phrase that lacks clear definition, which has hampered researchers' efforts to investigate the nuances of effectiveness and instructors' efforts to capitalize on potential benefits for students. One way to advance our understanding of "active learning" is assessing by the type of intellectual work that in-class activities require of students. We systematically analyzed in-class work opportunities created for students in 55 introductory biology courses around the United States, each of which used active learning. We did so by adapting an observation approach grounded in the ICAP framework and analyzing classroom videos in 15-s segments. Instructors devoted about a quarter of class time to student work time, on average, but this varied widely. About half of these student work opportunities focused on recall, and half required students to generate answers beyond what had been presented to them, which can foster deeper learning and better transfer than recall alone. The ratio of these levels of intellectual work varied considerably across courses. We also tested whether course- and instructor-level factors predicted the amount and level of active-learning opportunities and found no significant relationships. This work provides a striated definition of active learning that will be useful to researchers studying active-learning outcomes and instructors aiming to harness learning benefits for their students.

Indexed as

active learningbiology educationhigher-order cognitive skillsICAPSTEM educationundergraduate

Identifiers

PMID41744500
PMCPMC13131020

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.