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Ineffective Online Learning During the COVID-19 Pandemic in Higher Education
(2026-01-01)
Sitthiworachart, Jirarat
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Hong, Jon Chao
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Yanwar, Amanda Pradhani
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Prabowo, Thoriq Tri
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Suwanno, Phimpawee
The rapid shift to online learning during COVID-19 caused challenges in higher education. Many teachers and students lacked experience with online learning platforms and techniques. The factors why online learning was not effective during the COVID-19 pandemic are examined. A total of 302 questionnaires were collected using Google Form. The quantitative data were analyzed using SPSS and AMOS for item analysis, facet reliability and validity analysis, path analysis, direct and indirect effect analysis, and difference analysis. The effect of online learning flow, online learning cognitive load, and self-efficacy of online learning on unsuccessful online learning was revealed in this study. The result showed that: (1) greater levels of Self-efficacy of Online Learning on Human-system interaction (SOLH) and Self-efficacy of Online Learning on Content (SOLC) were significantly predict higher levels of Flow in Online Learning (FOL); (2) greater levels of Self-efficacy of Online Learning on Human-system interaction (SOLH) and Self-efficacy of Online Learning on Content (SOLC) were not significantly predict higher levels of Cognitive Load of Online Learning (CLOL); and (3) greater levels of Cognitive Load of Online Learning (CLOL) were significantly predicted higher levels of Online Learning Ineffectiveness (OLI). The online learning ineffectiveness can be reduced by decreasing the levels of cognitive load instead the learning flow.
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Developing a Conceptual Framework UTAUT-TTF-TOE Model to Examine AI’s Influence on HR Performance in Higher Education
(2026-01-01)
Luomou
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Chaveesuk, Singha
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Chaiyasoonthorn, Wornchanok
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Kamales, Nayika
The swift advancement of artificial intelligence (AI) is exerting a profound influence on the operational paradigm of higher education, yet the degree of its implementation exhibits substantial disparities among institutions. Presently, there is a dearth of systematic research on the moderating mechanisms of AI adoption intensity on organizational performance. This research integrates the Unified Theory of Acceptance and Use of Technology (UTAUT), task-technology fit (TTF), and the technology-organization-environment (TOE) framework to formulate a comprehensive model for exploring the mechanisms through which AI impacts human resource performance in universities. The research centers on analyzing how technological, organizational, and environmental factors interact to affect AI adoption, specifically investigating the moderating function of adoption intensity in this relationship. This research endeavors to uncover the specific pathways and boundary conditions for AI to improve university management efficiency.
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Enhancing digital literacy in Thai higher education: A strategic imperative
(2025-01-01)
Noppakhunwong, Thaksina
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Kantathanawat, Thiyaporn
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Pimdee, Paitoon
This study aims to enhance digital literacy in Thai higher education through the development of an integrated framework—3CLPC (Cloud-based, Collaborative, and Positive Coaching). A mixed-methods approach was employed, combining surveys and interviews with students and faculty from three public universities. Quantitative data were analyzed using descriptive statistics, while qualitative input informed iterative model refinement. The results indicated improvements in students’ digital competencies, especially in collaboration, content creation, and problem-solving. Participants also reported increased confidence and engagement when using cloud-based tools and receiving supportive coaching. The 3CLPC framework effectively addresses the divide between access to technology and pedagogical effectiveness, particularly in under-resourced institutions. The model is scalable and adaptable to other Southeast Asian contexts. Practical implications include integration into teacher training programs and digital curriculum policies. The study contributes to bridging the gap between policy and practice in digital education, emphasizing equity and learner-centered design.
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Towards global citizenship–role of cross border higher education across the ASEAN region
(2024-10-01)
Khalid, Bilal
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Kurowska-Pysz, Joanna
The Association of Southeast Asian Nations (ASEAN) region has been experiencing a vibrant economy with heavy investment in higher education as an economic development driver. Being home to over 630 million people and more than 7,000 higher education institutions (HEIs) and over 12 million students, it was critical to evaluate the role of cross-border higher education in the region. This study aimed to investigate the factors and motivations contributing to the success and efficacy of cross-border higher education in the ASEAN region. Additionally, it sought to examine the impact of cross-border education on the development of global citizenship. A quantitative study was conducted using secondary data from the repositories of the World Bank and UNESCO Institute for Statistics (UIS). Data was analyzed using descriptive visualizations and regression analysis. Results indicated variations in HEIs investments, with Brunei having the least. Many students moved from the ASEAN region to seek higher education in other regions, with Vietnam having the highest number of 137,022 students. The majority of these ASEAN countries have more than 10,000 higher education students’ abroad. The United States, Australia, and Japan were the significant destinies of students from the ASEAN region. Government expenditure on tertiary education, gross domestic product (GDP), tertiary school enrolment, and GDP growth rate were found to have a significant influence on cross-border higher education mobility. Policy recommendations were the development of international collaborations, cross-border partnerships, and cross-national harmonization to enhance the partnership and mobility of higher education students in the ASEAN region.
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Influences of International Exchange Programs and Research Engagement on Faculty Development in Higher Education Institutions
(2024-01-01)
Wei, Lina
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Sumettikoon, Piyapong
The study examines the significant effects of their satisfaction with international exchange programs and their participation in international research activities on faculty members’ professional development within higher education institutions. The main objective of this study is to find out the considerable correlation between faculty members’ professional advancement and their satisfaction with international exchange programs. Results indicate that faculty development is highly influenced by satisfaction and participation in international research activities. In this research paper, survey data from various departments across multiple Chinese universities is quantitatively analyzed. Purposive sampling was utilized in this starfield to gather the intended respondents. The findings highlight the significance of exchange program quality and content and the benefits of active engagement in global research. The study also focuses on how faculty members’ global experiences enhance their innovative teaching practices, research output, and professional development.
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The outlook of ChatGPT, an AI-based tool adoption in Academia: applications, challenges, and opportunities
(2023-01-01)
Ahadi, Navidreza
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Zanjanab, Ali Ghalehban
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Sorooshian, Shahryar
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Monametsi, Gladness
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Virutamasen, Porngarm
Artificial intelligence (AI) technologies continually improve and become more pervasive in many facets of our lives. ChatGPT is a chatbot created by OpenAI with a conversational artificial intelligence interface. Academic institutions could routinely use artificial intelligence (AI) and language models like ChatGPT, with an increasing range of applications and ramifications. This study investigates the adoption of ChatGPT in academia which include applications, challenges and opportunities using the lenses of educational transformation, response service quality, usefulness privacy concerns. The article first examine diverse applications of ChatGPT, including automation, sentiment analysis and natural language processing. Second, it addresses the challenges and limitations that come with using these technologies, like regulatory compliance algorithmic prejudice, and ethical issues. Third, the study emphasize the opportunities brought about by the implementation of AI and ChatGPT, such as improved research capacities, individualized learning experiences, and new career pathways. To promote an efficient and responsible adoption and deployment of ChatGPT, the study's findings offer several research directions and implications in academia.
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Architecture students’ conceptions, experiences, perceptions, and feelings of learning technology use: Phenomenography as an assessment tool
(2022-01-01)
Ebenezer, Jazlin
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Sitthiworachart, Jirarat
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Na, Kew Si
The primary purpose of this phenomenographic qualitative study is to identify a group of second-year undergraduate architecture students’ conceptions of learning technology use. The secondary purpose is to examine students’ learning experiences, perceptions, and feelings of technology use in an education course. Data were collected over a week by individually interviewing 15 architecture students, who were becoming teachers of architecture. Each 20-min individual interview was audio-recorded, transcribed verbatim, translated into English, and analysed to identify descriptive categories of the students’ conceptions of learning technology use. The six descriptive categories were: learning online; searching for information and knowledge, defining social media connectivity, exploring a virtual place, designing a model house, and transferring knowledge and understanding. Most architecture students expressed the technology-integrated lessons were interesting. The architecture students perceived educational games as the most useful teaching tools in their future classrooms. The study implies phenomenography can be used as an assessment tool to identify students’ conceptions and characterize their structural aspects, which may be used as curriculum frameworks to design content that moves architecture students from the periphery to the core of the subject.
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Higher Education-Oriented Recommendation Algorithm for Personalized Learning Resource
(2022-01-01)
Zhang, Liang
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Zeng, Xiao
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Lv, Ping
As smart education is continuously deepened in higher education, personalized learning resource recommendation has developed into a significant research field of smart learning. Although the prediction accuracy has been improved by knowledge tracing models established on the basis of students’ historical learning data, how to design and apply personalized learning recommendation by combining classroom teaching of higher education is a great difficulty. To recommend personalized learning resources meeting the teaching requirements in higher education, the Q-LRDP-D (Learning Resource Difficulty Prediction and Dijkstra based on Q matrix) algorithm was proposed in this study. First, learning resources were modeled in accordance with Q matrix theory. Then, students’ learning difficulty was predicted through the long short-term memory (LSTM) algorithm of a learning resource difficulty prediction module, followed by cyclic prediction through combining the to-be-learned knowledge points as required by teaching units to form a directed path diagram of learning resources. Next, the least learning resources conforming to students’ learning levels were recommended using the shortest path algorithm to complete learning tasks. Lastly, the accuracy and effectiveness of the established model were verified through undergraduate teaching experiments. Results demonstrate that the modeling of learning resources in higher education on the basis of Q matrix theory is applicable to the LSTM algorithm. In comparison with the benchmark algorithm, its precision is obviously improved. With the recommendation algorithm, the average return on learning resources in the experimental class is 6.31, which is considerably higher than that in the control group. This study provides a certain reference for improving students’ learning efficiency through recommendation algorithms in higher education and teaching
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Pre-service teachers' concerns about diversity
(2021-10-12)
Sunthonkanokpong, Wisuit
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Murphy, Elizabeth
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Development of an Assessment Tool for Prioritizing Influencing Factors of Sustainability in Higher Education
(2020-01-01)
Jungthawan, Siripong
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Tiyarattanachai, Ronnachai
The United Nations set 17 Sustainable Development Goals (SDGs) in August 2015 as a blueprint to achieve sustainable future for all nations at all levels. Higher education institutions are expected to significantly contribute to the goal, as they must produce the human resources and research necessary for achieving sustainability. In October 2019, Times Higher Education (THE) launched the THE University Impact Rankings, which encouraged universities to focus efforts that pose positive impacts on SDGs in the areas related to the university's operation. Since SDGs and their targets may have different priorities in different countries, we examined the perspectives of stakeholders in 16 Thai universities ranked in the THE World University Rankings to prioritize the SDG areas on which the universities should focus. We expect that this study will be used by Thai university executives to optimize resources spent on achieving better sustainability performance.

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