Evidence map›Paper›PMID 39594308›Full record

ArticleBehavioral sciences (Basel, Switzerland)2024

Latent Profile Analysis of AI Literacy and Trust in Mathematics Teachers and Their Relations with AI Dependency and 21st-Century Skills.

Tommy Tanu Wijaya, Qingchun Yu, Yiming Cao, Yahan He, Frederick K S Leung

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 3 pooled it
–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

19 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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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

5 authors.

Tommy Tanu WijayaSchool of mathematical Sciences, Beijing Normal University, Beijing 100088, China.ORCID 0000-0001-6840-3875
Qingchun YuSchool of mathematical Sciences, Beijing Normal University, Beijing 100088, China.ORCID 0000-0002-6619-689X
Yiming CaoSchool of mathematical Sciences, Beijing Normal University, Beijing 100088, China.
Yahan HeSchool of Mathematical Sciences, Capital Normal University, Beijing 100048, China.
Frederick K S LeungCollege of Education for the Future, Beijing Normal University, Zhuhai 519087, China.ORCID 0000-0003-1725-3883

Funding

National Research Institute for Mathematics Teaching Materials 2023GH-ZDA-JJ-Y-04
6 · The paper itself

Abstract

Artificial Intelligence (AI) technology, particularly generative AI, has positively impacted education by enhancing mathematics instruction with personalized learning experiences and improved data analysis. Nonetheless, variations in AI literacy, trust in AI, and dependency on these technologies among mathematics teachers can significantly influence their development of 21st-century skills such as self-confidence, problem-solving, critical thinking, creative thinking, and collaboration. This study aims to identify distinct profiles of AI literacy, trust, and dependency among mathematics teachers and examines how these profiles correlate with variations in the aforementioned skills. Using a cross-sectional research design, the study collected data from 489 mathematics teachers in China. A robust three-step latent profile analysis method was utilized to analyze the data. The research revealed five distinct profiles of AI literacy and trust among the teachers: (1) Basic AI Engagement; (2) Developing AI Literacy, Skeptical of AI; (3) Balanced AI Competence; (4) Advanced AI Integration; and (5) AI Expertise and Confidence. The study found that an increase in AI literacy and trust directly correlates with an increase in AI dependency and a decrease in skills such as self-confidence, problem-solving, critical thinking, creative thinking, and collaboration. The findings underscore the need for careful integration of AI technologies in educational settings. Excessive reliance on AI can lead to detrimental dependencies, which may hinder the development of essential 21st-century skills. The study contributes to the existing literature by providing empirical evidence on the impact of AI literacy and trust on the professional development of mathematics teachers. It also offers practical implications for educational policymakers and institutions to consider balanced approaches to AI integration, ensuring that AI enhances rather than replaces the critical thinking and problem-solving capacities of educators.

Indexed as

21st-century skillsAI toolsChatGPTdependencylatent profile analysis

Identifiers

PMID39594308
PMCPMC11591428

What OpenQuestion holds

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LicenceCC BY
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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.