TY - JOUR
T1 - Chat-GPT; validating Technology Acceptance Model (TAM) in education sector via ubiquitous learning mechanism
AU - Saif, Naveed
AU - Khan, Sajid Ullah
AU - Shaheen, Imrab
AU - Alotaibi, Abdullah
AU - Alnfiai, Marim M.
AU - Arif, Mohammad
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2024/5
Y1 - 2024/5
N2 - The current study aims to establish a connection between students' behavioral concerns, namely stress and anxiety, related to the completion of academic tasks, and their integration of technology using the Technology Acceptance Model (TAM) through the utilization of Chat-GPT via ubiquitous learning (UL) procedure. To achieve this objective, data was collected from 156 students studying management science who were engaged in their final year research projects or internship reports from selected universities in Pakistan. The gathered data underwent analysis through Structural Equation Modeling (SEM) using Smart PLS software. The findings reveal a significant relationship: students' stress contributes to the emergence of anxiety, which in turn motivates the adoption of technology-assisted solutions, specifically Chat-GPT, to efficiently complete assigned tasks within deadlines working through any device from anywhere. Consequently, the perceived ease of use and usefulness associated with Chat-GPT's AI-generated text contribute to shaping students' favorable attitudes toward utilizing Chat-GPT and also play a role in reducing their stress levels. Furthermore, the study confirms that the development of a positive attitude in students acts as a driving force, compelling them to engage with Chat-GPT through ubiquitous learning (UL) procedure, ultimately resulting in increased actual usage of Chat-GPT. This pattern, in turn, contributes to stress and anxiety reduction among management science students. The study's outcomes corroborate the TAM model, which aligns with the social exchange process, demonstrating its applicability within the context of the educational setup in management sciences and its potential to enhance the learning experiences of researchers.
AB - The current study aims to establish a connection between students' behavioral concerns, namely stress and anxiety, related to the completion of academic tasks, and their integration of technology using the Technology Acceptance Model (TAM) through the utilization of Chat-GPT via ubiquitous learning (UL) procedure. To achieve this objective, data was collected from 156 students studying management science who were engaged in their final year research projects or internship reports from selected universities in Pakistan. The gathered data underwent analysis through Structural Equation Modeling (SEM) using Smart PLS software. The findings reveal a significant relationship: students' stress contributes to the emergence of anxiety, which in turn motivates the adoption of technology-assisted solutions, specifically Chat-GPT, to efficiently complete assigned tasks within deadlines working through any device from anywhere. Consequently, the perceived ease of use and usefulness associated with Chat-GPT's AI-generated text contribute to shaping students' favorable attitudes toward utilizing Chat-GPT and also play a role in reducing their stress levels. Furthermore, the study confirms that the development of a positive attitude in students acts as a driving force, compelling them to engage with Chat-GPT through ubiquitous learning (UL) procedure, ultimately resulting in increased actual usage of Chat-GPT. This pattern, in turn, contributes to stress and anxiety reduction among management science students. The study's outcomes corroborate the TAM model, which aligns with the social exchange process, demonstrating its applicability within the context of the educational setup in management sciences and its potential to enhance the learning experiences of researchers.
KW - Chat-GPT
KW - Higher education
KW - Management sciences students
KW - TAM
KW - Ubiquitous learning (UL) procedure
UR - http://www.scopus.com/inward/record.url?scp=85182271397&partnerID=8YFLogxK
U2 - 10.1016/j.chb.2023.108097
DO - 10.1016/j.chb.2023.108097
M3 - Article
AN - SCOPUS:85182271397
SN - 0747-5632
VL - 154
JO - Computers in Human Behavior
JF - Computers in Human Behavior
M1 - 108097
ER -