Evidence map›Paper›PMID 40521144›Full record

ArticleData in brief2025

Data on behavioural intention to use AI copilot through TAM and AI ecological education policy lens.

Emelie C Villaceran, Celbert M Himang

Abstract read
In one paragraph

Article in Data in brief, 2025. 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. 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

2 authors.

Emelie C VillaceranCollege of Computer, Information and Communications Technology, Cebu Technological University, M.J. Cuenco Ave cor. R. Palma St., Cebu City, Philippines.
Celbert M HimangGraduate School, Cebu Technological University, M.J. Cuenco Ave., cor R. Palma St., Cebu City, Philippines.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This research presents a dataset concerning the behavioral intention to utilize AI Copilot among faculty and students at Cebu Technological University, analyzed through the lenses of the Technology Acceptance Model (TAM) and the AI Ecological Education Policy Framework. Data collection was conducted via a quantitative survey distributed electronically, targeting a broad participant that included various students and instructors from multiple academic departments and year levels. A non-probability convenience sampling method was employed, targeting students and instructors within CTU. The survey was meticulously designed to evaluate constructs aligned with the Technology Acceptance Model and the pedagogical components of the AI Ecological Policy Framework, emphasizing aspects such as perceived usefulness and ease of use. Informed consent was obtained from participants, ensuring an understanding of the study's objectives and their rights regarding confidentiality. Ultimately, 414 responses were collected, with 18 responses excluded due to a lack of variability. The dataset, predominantly featuring student responses (94 %) and a smaller faculty representation (6 %), offers insights pertinent to AI Copilot's acceptance in this academic context. This dataset boasts considerable potential for future research endeavours, including studies on technology adoption in educational institutions, comparative analyses between different settings, and the enhancement of AI tools aligned with educational practices. Researchers and policymakers can utilize these insights to inform strategies for effective AI integration in education.

Indexed as

AI copilotAI ecological policy frameworkAI in educationStructural equation modelingTechnology acceptance model

Identifiers

PMID40521144
PMCPMC12163176

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.