Evidence map›Paper›PMID 37279087›Full record

ArticleCBE life sciences education2023

Factors Influencing Instructors' Adoption and Continued Use of Computing Science Technologies: A Case Study in the Context of Cell Collective.

Changsoo Song, Resa Helikar, Wendy M Smith, Tomáš Helikar

Abstract read
In one paragraph

Article in CBE life sciences education, 2023. 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.

Changsoo SongDepartment of Biochemistry, University of Nebraska-Lincoln, Lincoln, NE 68503.
Resa HelikarDepartment of Biochemistry, University of Nebraska-Lincoln, Lincoln, NE 68503.
Wendy M SmithCenter for Science, Mathematics, & Computer Education, and Mathematics Department, University of Nebraska-Lincoln, Lincoln, NE 68503.
Tomáš HelikarDepartment of Biochemistry, University of Nebraska-Lincoln, Lincoln, NE 68503.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acquiring computational modeling and simulation skills has become ever more critical for students in life sciences courses at the secondary and tertiary levels. Many modeling and simulation tools have been created to help instructors nurture those skills in their classrooms. Understanding the factors that may motivate instructors to use such tools is crucial to improve students' learning, especially for having authentic modeling and simulation learning experiences. This study designed and tested a decomposed technology acceptance model in which the perceived usefulness and perceived ease of use constructs are split between the teaching and learning sides of the technology to examine their relative weight in a single model. Using data from instructors using the Cell Collective modeling and simulation software, this study found that the relationship between perceived usefulness-teaching and attitude toward behavior was insignificant. Similarly, all relationships between perceived ease of use-teaching and the other variables (i.e., perceived usefulness-teaching and attitude toward behavior) became insignificant. In contrast, we found the relationships between perceived ease of use-learning and the other variables (i.e., perceived usefulness-teaching, perceived usefulness-learning, and attitude toward behavior) significant. These results suggest that priority should be given to the development of features improving learning over features facilitating teaching.

Indexed as

LearningStudentsAttitudeComputer SimulationHumansTechnology

Identifiers

PMID37279087
PMCPMC10424226

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.