ArticleScientific reports2024
Unraveling the dynamics of ChatGPT adoption and utilization through Structural Equation Modeling.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Factors influencing the intention to use generative artificial intelligence in educational systems: a meta-analysis.BMC psychology · 2026Pooled it
- Investigating behavioral intentions toward DeepSeek adoption using a moderated-mediation analysis with PLS-SEM and fsQCA.Scientific reports · 2026Article
- Exploring key predictors of ChatGPT adoption in higher education: insights from UTAUT3 and ARCS model.BMC psychology · 2026Article
- Determinants of university students' intention to use generative AI tools for personalized English learning: mediating effect of flow experience and moderating effect of personal innovativeness.Frontiers in psychology · 2026Article
- Development and validation of the AI dependence scale for Chinese undergraduates and a preliminary exploration.Frontiers in psychology · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
ChatGPT, an advanced Artificial Intelligence tool, is getting considerable attention in higher education. ChatGPT significantly changes the student learning experience through its AI-aided support, personalized study assistance and effective educational experiences, and it has become an object of particular interest in this context. This research aimed to build a technology acceptance and usage model that encapsulates the elements influencing students' adoption and utilization of ChatGPT, drawing on constructs from the 'Unified Theory of Acceptance and Use of Technology' and 'Flow Theory'. The proposed model was found valid and prolific, with the credibility of the results relying on the self-reported surveys of 505 students from three universities in Pakistan. Structural Equation Modelling (SEM) was used to analyze data that confirmed the robustness and validity of the proposed model of the study. The study findings supported nine out of the ten proposed hypotheses. Perceived playfulness was declared the paramount predictor of behavioral intention, while perceived values and performance expectancy were the next-level predictors. Additionally, behavioral attention was a high and inspiring determinant of ChatGPT usage behavior, followed by attention focus. This analysis demonstrates a need for a thorough investigation of AI tools like ChatGPT in higher education.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.