Modelling ChatGPT Utilization and Acceptance Among Undergraduate Students in Philippine Higher Education Institution

The hypotheses of the research were established based on the UTAUT2 model with the following factors included: Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Hedonic Motivation, Price Value, Habit, Age, Gender, Experience, Behavioural Intention, Use Behavior. To examine the direct, indirect, and moderating relationships between various predictors and outcomes, a statistical model was developed. It was discovered that performance expectation (PE), social influence (SI), price value (PV), and habit (HAB) have significant direct effects on behavioral intention (BI). The influence of HAB was the most significant ( = 0.388), followed by PV ( = 0.252), SI ( = 0.190), and PE ( = 0.079). With a beta coefficient of 0.388, the results of the model indicated that, of the four predictors, habit had the greatest influence on behavioral intention. Price value came in second with a beta coefficient of 0.252, while social influence and performance expectations had beta coefficients of 0.190 and 0.079, respectively. In contrast, effort expectancy (EE) had no significant effect on BI. These relationship effect sizes were categorized as minor (f2 0.02) for PE, medium (f2 0.15 for SI and PV, and large (f2 0.35 for HAB). BI was also discovered to have a significant impact on use behavior (UB).In terms of indirect connections, there was a significant connection between HAB and BI via UB. This indicates that a person's HAB has a substantial impact on their BI, which in turn has a substantial impact on their UB. Therefore, a person's HAB can serve as a reliable indicator of their UB. Thus, as previously demonstrated, a habit may influence both the direct and indirect use of substances. In this indirect path, the magnitude of the effect was modest.Multiple interactions were also investigated for potential moderating effects. The age of a student did not substantially influence the correlations between PV and BI, HAB and BI, or HAB and UB. In contrast, gender substantially moderated the effects of PV and HAB on BI, albeit to a small extent. In addition, experience (EXP) substantially moderated the effects of BI and HAB on UB, both of which had modest effect sizes. Insignificant was the effect of EXP on the relationship between HAB and BI.

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Identifier
DOI https://doi.org/10.17632/5hw62cdb75.2
PID https://nbn-resolving.org/urn:nbn:nl:ui:13-w3-rswj
Metadata Access https://easy.dans.knaw.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:easy.dans.knaw.nl:easy-dataset:298103
Provenance
Creator HIMANG, C
Publisher Data Archiving and Networked Services (DANS)
Contributor CELBERT HIMANG
Publication Year 2023
Rights info:eu-repo/semantics/openAccess; License: http://creativecommons.org/licenses/by/4.0; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Representation
Resource Type Dataset
Discipline Other