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A LACANIAN ETHICAL RECONSTRUCTION OF SUSTAINABLE AI EDUCATION
Full text linkWithin the global agenda of "Sustainable AI and Education," mainstream AI educational systems are predominantly built upon cognitive and behaviorist paradigms. These systems emphasize efficiency, predictability, and immediate feedback, presupposing the learner as a quantifiable and optimizable cognitive subject. However, this technological imagination of a "transparent subject" obscures the fundamental condition of subjective existence revealed by psychoanalysis as early as the beginning of the 20th century—namely, split subjectivity, the insatiability of desire, and the continuous illusion of unconscious processes from structures of meaning. Adopting a Lacanian critical perspective, this paper argues that current AI educational systems, in their attempt to algorithmically satisfy learners' "demands," systematically repress "desire," which constitutes the core dynamism of subjectivity. Lacan emphasizes that the essence of human desire is an eternal pursuit of "lack," rather than a "need" waiting to be fulfilled. When existing AI educational systems operate on learners merely through a cyclical "satisfaction-feedback" pathway, they effectively induce a narcissistic loop akin to the "Imaginary order." This process deprives learners of the opportunity to confront the traumas, unknowns, or gaps of meaning associated with the "Real," thereby obstructing the potential for "symptoms" manifest in the learning process—such as frustration, dissonance, and confusion—to be transformed into creative forces. Based on this analysis, this paper introduces the Lacanian concept of "desire" as a critical entry point for examining the numerous ethical controversies in sustainable AI education. It proposes an ethics of desire for educational practice, positing that AI should not be viewed merely as a technical tool for addressing learners' demands. Instead, it should precisely function as an "Otherness" ethical medium that reveals the structural lack within the subject and guides learners into a dialogue with their own desire. Thus, as an "irreducible heterogeneity" for the learner—that is, an ethical other in the Lacanian sense—AI education can persistently evoke the learner's awareness of the fundamental (lack) inherent in knowledge and the self. This transforms education from an object of technical optimization into a sustainable ethical practice of desire. Within this practice, AI ceases to be a technological tool for narcissistic collusion with the learner and becomes an ethical partner that facilitates the learning subject's continuous transcendence of established cognitive boundaries towards unknown possibilities through the endless dialectic of desire
A LACANIAN ETHICAL RECONSTRUCTION OF SUSTAINABLE AI EDUCATION: Received: 08th December 2025, Revised: 15th December 2025, 16th December 2025, Accepted: 18th December 2025, Date of Publication: 01st January 2026
No full textWithin the global agenda of "Sustainable AI and Education," mainstream AI educational systems are predominantly built upon cognitive and behaviorist paradigms. These systems emphasize efficiency, predictability, and immediate feedback, presupposing the learner as a quantifiable and optimizable cognitive subject. However, this technological imagination of a "transparent subject" obscures the fundamental condition of subjective existence revealed by psychoanalysis as early as the beginning of the 20th century—namely, split subjectivity, the insatiability of desire, and the continuous illusion of unconscious processes from structures of meaning. Adopting a Lacanian critical perspective, this paper argues that current AI educational systems, in their attempt to algorithmically satisfy learners' "demands," systematically repress "desire," which constitutes the core dynamism of subjectivity. Lacan emphasizes that the essence of human desire is an eternal pursuit of "lack," rather than a "need" waiting to be fulfilled. When existing AI educational systems operate on learners merely through a cyclical "satisfaction-feedback" pathway, they effectively induce a narcissistic loop akin to the "Imaginary order." This process deprives learners of the opportunity to confront the traumas, unknowns, or gaps of meaning associated with the "Real," thereby obstructing the potential for "symptoms" manifest in the learning process—such as frustration, dissonance, and confusion—to be transformed into creative forces. Based on this analysis, this paper introduces the Lacanian concept of "desire" as a critical entry point for examining the numerous ethical controversies in sustainable AI education. It proposes an ethics of desire for educational practice, positing that AI should not be viewed merely as a technical tool for addressing learners' demands. Instead, it should precisely function as an "Otherness" ethical medium that reveals the structural lack within the subject and guides learners into a dialogue with their own desire. Thus, as an "irreducible heterogeneity" for the learner—that is, an ethical other in the Lacanian sense—AI education can persistently evoke the learner's awareness of the fundamental (lack) inherent in knowledge and the self. This transforms education from an object of technical optimization into a sustainable ethical practice of desire. Within this practice, AI ceases to be a technological tool for narcissistic collusion with the learner and becomes an ethical partner that facilitates the learning subject's continuous transcendence of established cognitive boundaries towards unknown possibilities through the endless dialectic of desire
CAUSAL FACTORS AFFECTING BUSINESS MODEL INNOVATION AND SUSTAINABLE PERFORMANCE OF MONTHLY RENTAL APARTMENTS IN THAILAND
Full text linkThis dissertation investigates the causal factors influencing business innovation models and sustainable performance in Thai apartments. The research aims to explore the impact of key factors, including green leadership, digital service transformation, and internal capabilities, on business innovation and sustainability. A comprehensive theoretical framework integrates these components using a systemic analysis that highlights the interconnections between each variable. Findings reveal that green leadership significantly enhances environmentally friendly practices and green innovation, while digital transformation improves operational efficiency and competitive advantage. Internal capabilities foster ongoing innovation and sustainability, contributing to a business model responsive to market and environmental demands, leading to long-term sustainability. This study provides valuable insights for apartment entrepreneurs, academics, and researchers, supporting sustainable business practices in Thailand's real estate sector
THE QUALITY OF WORK LIFE AND ITS IMPACT ON IMPROVING THE PERFORMANCE OF HUMAN RESOURCES (THE GENERAL ADMINISTRATION OF HUMAN RESOURCES AT IMAM UNIVERSITY)
Full text linkThe study aimed to identify the impact of quality of work life in improving the performance of human resources in the General Administration of Human Resources at Imam Muhammad bin Saud Islamic University in the year 2024, from the point of view of the human resources employees of the university, which numbered (214) individuals, of whom (133) responded, the descriptive survey method was chosen, and the questionnaire was chosen as a tool for the study, and the tool consisted of five sections: The variables of the study, and the impact of quality of work life in improving the performance of human resources for the dimensions of: Fair and adequate compensation, safe and healthy working conditions, career growth opportunities, and clarity of rules and regulations in the organization of work:- The study found that the respondents agreed to a "great" extent on the impact of quality of work life in improving the performance of human resources in fair and appropriate compensation, and agreed to a "very great" extent on the axis of safe and healthy working conditions, career growth opportunities, and clarity of rules in the organization of work. The study showed that there are no statistically significant differences in the responses of the study members in all axes of the questionnaire due to the study variables, and based on the findings of the study, the researcher wrote a number of recommendations
THE MEDIATING EFFECT OF CUSTOMER EXPERIENCE IN THE RELATIONSHIP BETWEEN EMOTIONAL LABOR AND WORD-OF-MOUTH
Full text linkEmotional labor plays a crucial role in creating customer perceptions and behaviors in the service industry. This study examines the mediating effect of customer experience on the relationship between emotional labor and word-of-mouth (WOM). Drawing on theoretical frameworks related to emotional labor and customer experience, we propose that frontline employees' emotional efforts influence customer perceptions, which in turn affect their willingness to engage in WOM. This study used PLS (a partial least squares technique), questionnaires were distributed online, and a total of 250 valid questionnaires were collected using convenient sampling, targeting people who have been to retail, catering, or hotel industries within three months. Our findings reveal that customer experience mediates the relationship between deep acting on WOM, highlighting the importance of managing customer interactions effectively. These insights provide valuable implications for service management and marketing strategies aimed at enhancing customer satisfaction and positive WOM
A COMPARATIVE ANALYSIS OF THE INTERNATIONAL STANDARDS FOR THE PROFESSIONAL PRACTICE OF INTERNAL AUDITING AND THE GLOBAL INTERNAL AUDIT STANDARDS (GIAS)
Full text linkIn January 2024, the Institute of Internal Auditors (IIA) issued the Global Internal Audit Standards (the Standards) with implementation required by January 9, 2025. These standards represent a significant update from the 2017 version (the International Standards for the Professional Practice of Internal Auditing ), introducing several key changes to enhance the internal audit profession (IIA, 2025). This paper focuses on explaining the critical updates on the new global internal audit standards (GIAS).These standards are related to many areas such as, standards structure, internal audit functions, emerging risks, strategic objectives, artificial intelligence, and cybersecurity
ENHANCING JAPANESE VOCABULARY ACQUISITION WITH AI-GENERATED MUSIC: A NOVEL APPROACH
Full text linkThe potential of music to activate the brain and enhance learning has been widely recognized (Mogi, 2008), yet its application in Japanese education remains underexplored. Grammatical errors in popular songs can mislead students, and the need for specialized knowledge to create educational songs poses a challenge for teachers (Liu, 2023). AI music generation technology offers a convenient solution by creating songs tailored for educational purposes. While its benefits in English education have been demonstrated (Takano, 2024; Liu, 2024), its effectiveness in Japanese education still requires further research. This study conducted a two-week empirical investigation with 16 first-year Japanese major students from a university in Weifang City, Shandong Province, China, divided into an experimental group and a control group, each with 8 students. The experimental group was taught using AI-generated Japanese songs, while the control group continued with traditional methods. Results indicated significant improvements in vocabulary retention and comprehension in the experimental group, with more stable and lasting learning outcomes. There was a significant difference in scores between the experimental and control groups (p < 0.05). The study confirms the substantial potential of AI-generated songs to enhance Japanese vocabulary learning, particularly by increasing student engagement and motivation. These findings suggest that AI-generated music could be a valuable addition to traditional language learning methods, leading to more effective and enjoyable educational experiences. We recommend further research with larger sample sizes and more diverse educational contexts to fully realize the benefits of AI in language education and to explore its application across different learning environments
IDENTIFICATION AND QUANTIFICATION OF CRITICAL FACTORS SHAPING THE LEARNING EXPERIENCE OF STUDENTS IN A HIGHER EDUCATION INSTITUTION IN OMAN
Full text linkAim: This research aims to identify and quantify the factors shaping the learning experiences of students at the College of Engineering, National University of Science and Technology, Oman, particularly in the context of the rise of AI chatbots. Method: A total of 22 students from levels 3 and 4 were selected for focus group interviews conducted in a regular classroom setting. A set of 34 questions was designed based on Urie Bronfenbrenner's updated ecological systems theory. The responses were digitized for both quantitative and qualitative analysis. Main Findings: The results indicate a high awareness among students regarding the importance of achieving a place on the dean's list and the role of AI and machine learning in future education. However, there was low awareness of online library services, MOOCs, and job prospects. Mixed responses were recorded concerning peer tutoring, group assignments, and participation in student clubs. Notably, students expressed a positive attitude toward using social media for study purposes. Implications: These findings are crucial for understanding the pain points and challenges contributing to poor learning experiences and low awareness among students. The insights gained can assist college management in addressing these issues and enhancing the overall learning experience. Novelty: This study offers a novel exploration of the factors affecting students' learning experiences in a post-COVID-19 context, providing valuable information that can lead to improved educational strategies at the college level
A PERSONAL ENCOUNTER WITH RESEARCH: POETIC TRANSCRIPTION: Received: 16th September 2024, Revised: 24th October 2024, 6th November 2024, Accepted: 10th December 2024, Date of Publication: 29th April 2025
Full text linkPoetic inquiry is a qualitative method that accounts for both the participants’ first-person perspectives and the researcher’s personal interpretation in a unique and invitational presentation of data. This paper will discuss, first, the use of poetic transcription to transform the Research Conversation interview scripts of Indigenous community members involved in a partnership with university educators. The research project examined the concepts of learning and education from those in the Indigenous community that were directly involved in the culturally appropriate programs offered at a Friendship Centre in Ontario (Canada). The key themes identified in the data will be shared. They include: 1. Education as a “lived reality” 2. Sense of Well-Being, and 3. Resolving Tensions. Second, the paper will present the respective poems that emerged from the poetic transcription that represent the researcher’s critical encounter with participants’ delicately complex stories. The manuscript addresses how readers’ emotions are implicated in poetic inquiry since the qualitative approach serves to appeal to the broader complexity of participants’ experiences. The poems, therefore, underscore the intensely personal encounter and individual impressions the researcher experienced and, in turn, offer readers an opportunity to share in the moments of the critical encounter. 
ARTIFICIAL INTELLIGENCE IN EDUCATION: CHALLENGES AND OPPORTUNITIES
Full text linkArtificial Intelligence (AI) has become the most talked-about term of the year. However, in education—as in any knowledge-intensive field—its application is far from straightforward. While large language models, now widely used across industries, often produce “hallucinations” or inaccurate responses, such shortcomings are unacceptable in educational settings. So, how can we develop AI tools that genuinely address the challenges of modern education, ease the workload of teachers and students, enhance learning effectiveness, and, most importantly, make education more personalized? What AI approaches can be truly helpful for educators in their daily practice? In this talk, we will explore these questions and also examine successful case studies of AI implementation in higher education across Eastern Europe