Aug 2026· Edelweiss Applied Science and Technology· Vol 10, pp. 77-89· 0 citations· 44 references
TL;DR
Students' perceptions of AI-based personalised learning tools in Malaysian higher education institutions are examined to provide insights for developers, academic institutions, and policymakers regarding AI personalised learning tool selection, syllabus development, and integration strategies.
Abstract
Artificial Intelligence (AI) is a transformative technology reshaping teaching and learning practices. By enabling personalized, cost-effective, and adaptive learning experiences, AI has become increasingly integrated into educational environments. However, its adoption also raises concerns related to credibility, trustworthiness, accuracy, privacy, and security. As part of a larger research project, this paper examines students' perceptions of AI-based personalised learning tools in Malaysian higher education institutions. Student perceptions were investigated using three variables derived from the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2): Performance Expectancy (PE), Effort Expectancy (EE), and Social Influence (SI), with an additional variable, Reliability and Trust (RT). A qualitative study involving in-depth interviews with thirteen participants was conducted to explore their experiences with an AI-based personalised learning tool, Brainly. Using thematic analysis, five themes were identified: support and customization, learning efficiency, accessibility and interactivity, peer encouragement and social comparison, and credibility and dependability. Learning efficiency emerged as the most prominent theme, with 92% of participants reporting enhanced understanding of complex topics, improved learning effectiveness through accessibility, immediate feedback, and interactive learning, and better efficiency in revision and practice. The findings provide insights for developers, academic institutions, and policymakers regarding AI personalised learning tool selection, syllabus development, and integration strategies.
Artificial intelligence (AI) has emerged as a transformative force in education, offering new opportunities to enhance teaching and learning through adaptive instruction, personalized feedback, and flexible learning experiences. In English as a Foreign Language (EFL) education, AI-powered applications are increasingly used to support language instruction; however, empirical evidence on Iranian university instructors’ perceptions remains limited. This study investigates Iranian EFL instructors’ perceptions of integrating AI into English language teaching and learning, including perceived benefits, implementation challenges, and the influence of teaching experience. Using a quantitative research design, data were collected from 100 instructors at public and private universities across Iran through a structured questionnaire. The findings indicated that instructors generally held positive attitudes toward AI integration (M = 3.94, SD = 0.40). Personalized feedback, adaptive learning, enhanced learner engagement, and improved instructional efficiency were identified as the most valuable benefits. AI applications, particularly ELSA Speak and Duolingo, were viewed as effective supplementary tools for improving learners’ pronunciation, grammar, vocabulary, and autonomous learning. Participants identified several barriers, including inadequate technological infrastructure, financial constraints, and the absence of culturally relevant AI-generated learning materials. Statistical analyses revealed significant differences across teaching experience groups in perceptions of AI-related benefits, whereas perceptions of implementation challenges remained consistent. These findings suggest that professional experience influences instructors’ views of AI’s educational value. Institutional barriers, however, affect instructors regardless of experience. Overall, the study demonstrates AI’s potential to enrich English language education in Iran.
Fatemeh Harajpoor, Mona Alnaserian, Hossein Isaee· International Journal of Lan...· 0 citations
This study explores university EFL students’ perceptions of Artificial Intelligence (AI) in higher education learning environments, particularly within Faculty of Teacher Training and Education in Indonesia. Employing a qualitative phenomenological design, data were collected through semi-structured interviews with nine students from the Faculty of Teacher Training and Education who actively use AI-assisted tools in their academic activities. The findings reveal that EFL students demonstrate high familiarity with AI applications, especially for language learning, doing tasks, and perceive AI as a supportive learning assistant that enhances efficiency, autonomy, and confidence. AI tools are widely valued for providing immediate feedback, facilitating comprehension, and reducing learning anxiety through flexible and interactive learning experiences. However, the study also identifies critical concerns related to accuracy, ethical integrity, and dependency, as excessive reliance on AI may hinder critical thinking and academic responsibility. These findings highlight the dual role of AI as both an empowering pedagogical resource and a potential challenge when used uncritically. The study underscores the importance of developing deeper AI literacy and institutional guidance to ensure responsible, ethical, and cognitively meaningful AI integration in higher education.
Suratman Dahlan, A. Usman, Awaludin Rizal et al.· Journal of Language Teaching...· 0 citations
Artificial Intelligence (AI) has become an increasingly important component of higher education, influencing teaching, learning, academic support, and institutional practices. AI-powered tools such as adaptive learning systems, intelligent tutoring systems, virtual assistants, and learning analytics are reshaping students’ academic experiences by improving access to information, supporting self-paced learning, and enhancing engagement. At the same time, the growing use of AI in higher education has raised concerns relating to privacy, ethical use, digital fatigue, and the quality of human interaction in learning environments. Against this background, the present study examines undergraduate students’ perceptions of AI tools and their influence on student well-being and daily academic work in degree colleges of Rajouri District, Jammu and Kashmir.
The study adopted a quantitative approach using a descriptive survey design. Primary data were collected from 387 undergraduate students selected through stratified random sampling from degree colleges in Rajouri District. A structured questionnaire consisting of 25 statements measured on a five-point Likert scale was used to assess five dimensions: mental and emotional well-being, social interaction, academic engagement and performance, ethical concerns and privacy, and inclusivity and accessibility. Data were coded in Microsoft Excel and analyzed in SPSS Version 26 using descriptive statistics such as minimum, maximum, mean, and standard deviation.
The findings reveal that students generally perceive AI as beneficial for reducing academic stress, improving confidence, supporting workload management, and enhancing learning efficiency. Academic engagement and inclusivity emerged as especially strong dimensions, with students reporting that AI tools save time, support self-paced learning, and should be made equally accessible to all learners. However, the study also found that AI tools are not perceived as significantly improving peer interaction, teamwork, or collaborative learning, and many students expressed concern about privacy, ethical use, and mental fatigue associated with prolonged AI use. The paper concludes that AI has considerable potential to enrich higher education, but its educational value depends on balanced, ethical, and inclusive implementation supported by institutional transparency and human guidance.
M. Devi, Darakhshan Anjum· International Journal For Mu...· 0 citations
This paper deals with the concepts of integration, perception, and concerns of artificial intelligence (AI) applications in business education. It identifies the most commonly occurring AI tools by educators and learners, examines how convenient they are in enhancing learning, and also discusses the institutional, ethical, and behavioral concerns impacting the use of AI.
It employed a cross-sectional quantitative survey design with limited qualitative open-ended responses. Primary data collection is conducted using structured questionnaires involving 67 educators and students at Saudi Arabian institutions of higher learning. The statistical analysis conducted using STATA consisted of tests of reliability (Cronbach's Alpha), independence of chi-square tests, and ordered logistic regression to test the association of variables of AI tool use, perceived benefits, skill development, and engagement.
The empirical findings show that the most commonly used artificial intelligence application is ChatGPT, and its usage is associated with high self-reported engagement, perceived learning performance, and acquisition of abilities. The engagement of students comes out as the strongest predictor of positive perceptions with regard to the use of AI in boosting the practitioner-stakeholder associations (p < 0.01). Despite these positive relationships, concerns about accuracy, reliability, and institutional readiness are still relevant.
The formal education of AI systems, ethics, and regulatory institutions is highlighted in this manuscript as a crucial factor in addressing AI implementation. It provides new empirical data that outlines the correlation relationships between AI applications and institutional readiness and pedagogical change in the teaching of business.
This study explores the perceptions of college students toward the integration of Artificial Intelligence (AI) in education, with a focus on its general use, role in learning processes and outputs, and associated ethical concerns such as transparency, fairness, privacy, and data security. A total of 293 students from the Nueva Ecija University of Science and Technology – Gabaldon Campus participated in the study, representing various programs including Agriculture, Education, Information Technology, and Hospitality Management. A validated researcher-made questionnaire was used, comprising 25 items distributed across five constructs. Data were analyzed using descriptive statistics, mean and standard deviation, to determine levels of agreement, while Principal Components Analysis (PCA) was employed to examine communalities and ensure construct validity. The findings revealed a general agreement among students regarding the positive role of AI in enhancing learning experiences, increasing assignment efficiency, and developing skills relevant to future careers. However, lower mean scores in areas such as reliance on AI for research and collaboration suggest a need for further support and training. Notably, students expressed high confidence in the ethical management of their data, with strong agreement on institutional safeguards and transparency in data usage. Communality values ranging from 0.459 to 0.889 indicated that most items were well-represented within their respective constructs. The results highlight both the benefits and challenges of AI integration in education. The study recommends that institutions enhance AI-related communication, training, and ethical safeguards to support students in maximizing the potential of AI tools in their academic and professional development.
J. L. Galang, A. T. Capinding, Rosalie A. Pineda· TEM Journal· 0 citations
In higher education, the scope for large-scale, individualized learning catalyzed by rapidly evolving AI technology has already begun to emerge. This quantitative study was proposed to identify faculty and student knowledge of these technologies, the AI role in the context of individualized learning, and the implications of AI in Pakistani universities. 155 participants across public and private Pakistani universities completed the researcher-developed, structured, self-administered, Likert-scale questionnaire. The data were analyzed using SPSS, and following tests, such as descriptive statistics, Pearson correlation coefficients, and reliability analysis (Cronbach's alpha) were employed. AI Tool Awareness and AI-Driven Personalization were both positively and meaningfully associated with Learning Outcomes and Academic Performance. The analysis also showed a significant positive relationship among the three aspects. The participants showed a moderate to high level of AI tool awareness, high level of perception regarding AI tool utility, and positive enhancements in self-discipline, academic readiness, and overall performance. Many persisting issues were documented, including a lack of digital infrastructure, insufficient faculty training, and unaddressed issues of academic integrity and data security. For educational technologists and AI-oriented university managers, these findings require immediate formulation of responsive policies to facilitate improvement of the AI-integrated higher education learning system in Pakistan.
Mushba Ishtiaq, Ayesha Munir, Dr. Almas Shoaib· TAMSAAL· 0 citations
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