Extended TAM based acceptance of AI-Powered ChatGPT for supporting metacognitive self-regulated learning in education: A mixed-methods study.

This mixed-method study explores the acceptance of ChatGPT as a tool for Metacognitive Self-Regulated Learning (MSRL) among academics. Despite the growing attention towards ChatGPT as a metacognitive learning tool, there is a need for a comprehensive understanding of the factors influencing its acceptance in academic settings. Engaging 300 preservice teachers through a ChatGPT-based scenario learning activity and utilizing convenience sampling, this study administered a questionnaire based on the proposed Technology Acceptance Model at UTM University's School of Education. Structural equation modelling was applied to analyze participants' perspectives on ChatGPT, considering factors like MSRL's impact on usage intention. Post-reflection sessions, semi-structured interviews, and record analysis were conducted to gather results. Findings indicate a high acceptance of ChatGPT, significantly influenced by personal competency, social influence, perceived AI usefulness, enjoyment, trust, AI intelligence, positive attitude, and metacognitive self-regulated learning. Interviews and record analysis suggest that academics view ChatGPT positively as an educational tool, seeing it as a solution to challenges in teaching and learning processes. The study highlights ChatGPT's potential to enhance MSRL and holds implications for teacher education and AI integration in educational settings.

Integrated TTF and self-determination theories in higher education: The role of actual use of the massive open online courses.

The purpose of this study was to examine the relationships between users' satisfaction with actual use of massive open online courses (MOOCs) and intrinsically motivated, task-technology fit, attitudes toward using MOOCs, and behavioral intention to use MOOCs. As the primary technique for data collection, a survey questionnaire on self-determination theory (SDT) as well as task-technology fit (TTF) was distributed to a total of 228 students. The results of the users' (TTF) to attitude toward using MOOCs and their behavioral intention to use MOOCs had a positive impact on their satisfaction and actual use of MOOCs in higher education institutes. However, the users' perceived autonomy was not entirely satisfied, based on the results of their intrinsic motivation for the actual use of learning courses. Similarly, technology characteristics were insignificant with TTF for the actual use of MOOCs in academic institutions. Additionally, mediation studies showed that the correlations between independent factors on the one hand and users' satisfaction with their actual use of MOOCs on the other were significantly mediated by intrinsic motivation, TTF attitude, and behavioral intention to use. Finally, practical ramifications were examined, and recommendations were made with regards to the direction of future studies.

Integrating the Role of UTAUT and TTF Model to Evaluate Social Media Use for Teaching and Learning in Higher Education.

Investigation of task-technology fit and intention to use social media tools needs to focus specifically on higher education for teaching and learning, and its impact on students' academic performance. This article aims to develop a model that would identify essential aspects that are predicted to continue to play a large role in TTF for learning in BI, which could be used to improve academic performance in higher education. The purpose of this study was to investigate the characteristics and aspects of SM and the relationship between their use in the TTF and UTAUT theory to determine how they affect research students' satisfaction and AP in HE institutions. Data for the unified theory of acceptance and use of technology (UTAUT) and task-technology fit (TTF) theories were collected using a questionnaire survey. This research hypothesizes that behavioral intention to utilize social media and task-technology fit for learning will influence social characteristics, technology characteristics, performance expectancy, and effort expectancy, all of which will improve academic performance. As a test bed for this research, a structural equation model (SEM) was constructed examining the relationships between factors that affect students' academic performance. A stratified random sample strategy was used to disseminate the main tool of data collection, a questionnaire, to 383 students. A quantitative method was used to examine the results. The obtained outcomes showed that there was a correlation among social characteristics, technological characteristics, behavioral intention to use social media, and task-technology fit for academic performance, which aided student performance and results. The study indicates that PEX and EEX also demonstrated a strong relation to task-technology fit and behavioral intent to use social media for academic purposes, both of which positively impacted academic performance. As a result, the study found that behavioral intention to utilize and task-technology-fit social media promote students' active learning and enable them to discuss and exchange knowledge and information more efficiently. In conclusion, we encourage students to use social media for educational purposes in their studies and teaching through lectures in HE institutions.

Excessive reassurance seeking mediates relations between rumination and problematic smartphone use.

Aside from depression and anxiety, less is known about the relationship of problematic smartphone use (PSU) to other psychopathology- related variables. The authors' aim was to test previously neglected variables in relation to PSU: rumination and excessive reassurance seeking behavior (ERSB). The authors recruited 295 college students for a web-based survey of smartphone use frequency, PSU, depression and anxiety, ruminative thinking, and ERSB. The authors tested linear regression and mediation models, assessing rumination and ERSB as mediating associations between depression/anxiety severity with PSU, adjusting for age, sex, and smartphone use frequency. Results demonstrate that ERSB was significantly related to PSU severity, and ERSB mediated the association between rumination and PSU. Furthermore, the combination of rumination and ERSB mediated relations between both depression and anxiety severity with PSU. Results provide evidence for ERSB as an important variable in understanding relationships between psychopathology symptoms and PSU severity among college students.

Massive Open Online Courses (MOOCs): Data on higher education.

The data presented in this article are based on provides a systematic and organized review of 219 studies regarding using of Massive Open Online Courses (MOOCs) in higher education from 2012 to 2017. Consequently, the extant, peer-reviewed literature relating to MOOCs was methodically assessed, as a means of formulating a classification for MOOC-focused scholarly literature. The publication journal, country of origin, researchers, release data, theoretical approach, models, methodology and study participants were all factors used to assess and categorise the MOOC. These data contribute to materials required by readers who are interested in different aspects related to the literature of using Massive Open Online Courses (MOOCs) in higher education. Intention to use, interaction, engagement, motivations and satisfaction were five dynamics assessed in relation to the improvement of MOOCs. Students' academic performance can be influenced by MOOC which has the advantage of facilitating the learning process through offering materials and enabling the share of information.