Artificial Intelligence (AI) to Support Curriculum Development for English Language Teaching in South Sulawesi's Secondary Schools

Background and Aim: Grounded in the Technology Acceptance Model (TAM) and Technological Pedagogical Content Knowledge (TPACK) framework, this study investigates the relationship between artificial intelligence (AI) competency and AI awareness among graduate-level instructors in Thailand’s private higher education sector. The objectives were to: (1) examine overall levels of AI competency; (2) compare competency and awareness across academic disciplines, positions, and faculties; and (3) analyze the relationship between AI competency and awareness in the context of teaching management. The study addresses the growing need for educators to integrate AI tools ethically and effectively in instruction, research, and academic administration. Materials and Methods: A total of 400 graduate-level instructors from five private universities, Shinawatra University, Rangsit University, Sripatum University, Bangkok University, and Mahanakorn University of Technology, were selected through purposive sampling. Data were collected between January and March 2025 using a validated questionnaire (Cronbach’s α = .902) measuring AI competency and awareness of AI utilization. Descriptive statistics (frequency, percentage, mean, and standard deviation) were used to assess general trends, while inferential analyses (ANOVA, Pearson’s correlation, and t-tests) tested group differences and relationships. Results: Findings indicated a moderate overall level of AI competency and awareness, with higher proficiency among instructors in STEM disciplines and technology-oriented faculties compared to those in the humanities and social sciences. Significant differences were observed by academic position, with lecturers demonstrating higher engagement in AI-integrated practices than senior professors. A strong positive correlation was found between AI competency and AI awareness (r = .928, p < .001), confirming that instructors with stronger technical, instructional design, and ethical AI skills also exhibited greater awareness of AI’s pedagogical and societal implications. Conclusion: The study underscores the need for targeted faculty development programs, AI-integrated professional learning, and institutional strategies to enhance instructors’ digital and ethical readiness. Strengthening AI competency not only fosters responsible AI awareness but also supports teaching innovation, faculty performance, and digital transformation within Thailand’s private higher education sector.

Several revolutions are currently taking place in the healthcare industry to provide accurate, reliable, and valid healthcare to patients. Among these is artificial intelligence (AI). This study aimed to assess the CP's awareness, perceptions, and opinions of AI in health care among community pharmacists. This cross-sectional survey-based study was conducted over 3 months in 2023 using structured prevalidated 34 items questionnaires. In this study, 94.5% (n= 258) of the CPs were aware of AI, yet 25.6% (n= 70) believed that AI would eventually replace healthcare professionals. However, 63.4% (n= 173) of the CPs concurred that AI is a technology that supports healthcare workers. 12.8% of the CPs believed that there is a risk of losing their jobs if AI is widely used in Saudi Arabia, but 68.9% (n= 188) of them considered that healthcare professionals will benefit from the extensive use of AI. Eighty-four percent of CPs (n= 232) agreed or strongly agreed that AI decreases drug mistakes in clinical practice. Similarly, 86% of the CPs (n= 235) concurred that AI makes it easier for patients to access the service. In contrast, almost 58% of the CPs (n= 232) agreed that AI makes it easier for healthcare professionals to acquire information, and 87.9% of the CPs (n= 240) said that AI helps them make better decisions. This study concluded that most of the CPs were aware of AI and agreed that AI is a tool that helps healthcare professionals. In addition, the majority of the CPs thought that AI adoption in healthcare practice will benefit healthcare practitioners.

ObjectiveDrawing on the conservation of resources theory (COR), the research aims to reveal the influence of artificial intelligence (AI) awareness on employees’ mental health and behaviors, particularly examining whether and how employees’ AI awareness impacts their counterproductive work behaviors (CWB) in human-intelligence collaborations.MethodsData was collected from 327 Chinese employees who collaborated with AI in sales, manufacturing, logistics, and other industries. The measurement instruments included scales for AI awareness, psychological contract (PC), emotional exhaustion (EE), and counterproductive work behavior (CWB). We used Hayes’s PROCESS macro to analyze the data.FindingsAI awareness had a significant positive impact on CWB (β = 0.448, p < 0.01). PC and EE play a role as partial mediators in the relationship between AI awareness and CWB. The mediating pathways consist of three sequences: “AI awareness → PC → CWB,” “AI awareness → EE → CWB” and “AI awareness → PC → EE → CWB,” with the respective contributions to the overall effect amounting to 8.04, 18.53, and 4.91%.DiscussionOur research contributes to the study of AI in the management field by elucidating the relationship between AI awareness and CWB, as well as the mediating mechanisms of this relationship, which enriches the literature on CWB and expands the understanding of the associations between AI and CWB.

Purpose The prevalence of artificial intelligence (AI) has considerably affected management and society. This paper aims to explore its potential impact on hospitality industry employees, bringing enlightenment to both employees and managers. Design/methodology/approach Data were collected from a survey of 432 employees who worked in full-service hotels in China. Structural equation modeling (SEM) was used to analyze the data. Findings Results presented a positive relationship between AI awareness and job burnout. No significant direct relationship was found between AI awareness and career competencies. Organizational commitment mediated the relationship between AI awareness and career competencies, as well as the relationship between AI awareness and job burnout. Research limitations/implications This study contributes to human resource management in the hospitality industry to theoretical and practical aspects. Theoretically, it enriched both career theory and fit theory. Practically, this study reminds managers to pay attention to the adverse effect of AI on human capital. It also enlightens the manager to think of the positive effects that AI may bring. Managers should provide proper support to overcome AI’s threat to human resources. Practical implications Practically, this study reminds managers to pay attention to the adverse effect of AI on human capital. It also enlightens the manager to think of the positive effects that AI may bring. Managers should provide proper support to overcome AI’s threat to human resources. Originality/value The study aims to analyze the impact of AI from a career perspective. It provided theoretical support and evidence for hotel managers for the effects of AI awareness on hotel employees. The study conveys a potential topic of concern that the hospitality industry may face in the future.

The design industry in the AI era: How AI awareness and AI literacy influence the innovative work behavior of Chinese Generation Y designers.

Purpose This study aims to explore the relationship between artificial intelligence (AI) awareness and physical and psychological withdrawal behaviors of enterprises employees through the mediating roles of job security and emotional exhaustion as well as the moderating role of emotional intelligence. Design/methodology/approach Data were collected through a self-administered questionnaire from six fields with the highest level of AI application with a sample of 1,129 Vietnamese enterprises employees. Data were analyzed using SmartPLS, a bootstrapping technique was used to analyze the data. The mediating effect of job security and emotional exhaustion and the moderating effect of emotional intelligence were performed. Findings The research showed that the proposed moderated mediation model was accepted because the relationships between the constructs were statistically significant. The results of the data analysis supported a positive relationship between AI awareness and physical and psychological withdrawal behaviors, as well as a mediating effect of job security and emotional exhaustion. The findings also confirmed that there is a moderating effect of emotional intelligence between AI awareness and job security, emotional exhaustion, physical and psychological withdrawal behaviors. Research limitations/implications Sample data was only collected at a few Vietnamese enterprises in six fields with the highest level of AI application which are e-commerce, transportation and logistics, education, real estate, finance and agriculture, which may be limiting generalizability of research results. Practical implications This study offers several practical and useful management implications, such as anticipating negative attitudes, feelings and behaviors of employees to prepare a response plan; conducting interviews, investigate employees’ AI awareness and do their best to minimize its negative effects on employees’ psychological states and behaviors; and paying attention to recruiting and selecting employees with good emotional intelligence. Originality/value This study contributes to the growing literature on AI by elucidating the mediating roles of job insecurity and emotional exhaustion in the relationship between AI awareness and physical and psychological withdrawal behavior. This study also makes a significant step forward in examining the moderating mechanisms of emotional intelligence in attenuating the effects of AI awareness on job insecurity, emotional exhaustion, physical and psychological withdrawal behavior.

Purpose This paper aims to provide the integrated model with artificial intelligence (AI) awareness for the betterment of the higher education system in crisis i.e. fear of contagious viruses (different kinds of flu, monkeypox, chickenpox, COVID-19, etc.) corollaries in developing nations where the quality of education depends on teachers’ commitment, stress and the turnover intention. Design/methodology/approach This empirical investigation employs a self-administered survey distributed among the faculty members within higher education institutions (HEIs) of the Punjab province and the Federal Capital Territory (FCT) Islamabad, Pakistan. The final sample of 622 faculty members was collected through convenience sampling, and structural equation modeling was performed with SmartPLS to assess the proposed model. Findings The study reveals that remote work significantly enhances organizational commitment while concurrently lowering the turnover intention. Conversely, perceived work stress negatively impacts organizational commitment but positively influences turnover intention. Organizational commitment partially mediates between perceived work stress and turnover intention but exhibited no mediation between remote work and turnover intention. Notably, fear of contagious viruses and AI awareness positively moderate and amplify both the perceived work stress with turnover intention and remote working with organizational commitment, respectively. Research limitations/implications The current study extends the AI-mediated social exchange theory (MET) by observing faculty members of HEIs in the context of remote working, perceived work stress, commitment, turnover intention, fear of contagious viruses and AI awareness. Moreover, the successful application of AI-MET extended the researcher’s understanding of quality education in crisis. Practical implications The study offers several contributions including applications of technical skills with AI awareness among faculty members to provide quality education for society’s welfare. Moreover, HEIs should arrange training programs for performance enhancement. Originality/value This research provided a quality-based model for HEIs for developing nations to deal with forthcoming calamities of contagious viruses and deliver quality education through remote working during lockdown. Nowadays, off-campus education during calamity situations has been an alternative to on-campus education. Therefore, HEIs must introduce AI awareness to increase the dedication of faculty members toward society’s welfare with the utilization of full effort.

Artificial intelligence has become a trending topic in the last decade and has permeated all spheres of life and profession and Architecture is no exception. The use of artificial intelligence in architecture is still in its infancy as more research is still being carried out in the application of artificial intelligence in architecture to solve problems ranging from intelligent material design to architectural plan solutions. This study aimed to examine students’ levels of awareness, access, and use of artificial intelligence in architectural design at selected tertiary institutions in Southeast Nigeria. The three tertiary institutions selected are; The Department of Architectural Technology, Akanu Ibiam Federal Polytechnic Unwana, The Department of Architectural Technology Abia State Polytechnic, Aba and The Department of Architecture, Abia State University, Uturu. The main objective is to carry out a survey to investigate the awareness, access, and utilization of artificial intelligence (AI) in architectural design among students in selected tertiary institutions in Southeast Nigeria. This study adopted a descriptive research design of the survey method and employed a three-sectioned questionnaire to elicit information from the respondents. The sample size included a multistage sample of 300 undergraduates across three tertiary institutions in Ebonyi State and Abia State. The findings of the study were that the majority of the students are not aware of artificial intelligence and will use AI if they are aware of it and have access to it for their architectural design. Therefore, there is a need for integrating AI-related courses and workshops into the Architectural curriculum which can lead to better-prepared graduates who are proficient in using advanced design tools, potentially increasing their employability and innovation in the field. This study concluded that students' ability to explore digital resources such as AI for Architectural design is dependent on their awareness and access to digital technologies. A lack of these will result in a lack of use and lack of skill to use them.

PurposeThis study aims to investigate whether and how artificial intelligence (AI) awareness affects work withdrawal.Design/methodology/approachThis survey garners participation from a total of 305 hotel employees in China. The proposed hypotheses are examined using Hayes’s PROCESS macro.FindingsThe results indicate that AI awareness could positively affect work withdrawal. Negative work-related rumination and emotional exhaustion respectively mediate this relationship. Furthermore, negative work-related rumination and emotional exhaustion act as chain mediators between AI awareness and work withdrawal.Practical implicationsGiven the growing adoption of AI technology in the hospitality industry, it is imperative that managers intensify their scrutiny of the psychological changes experienced by frontline service employees and allocate more resources to mitigating the impact of AI on their work withdrawal.Originality/valueThis study contributes to the burgeoning literature on AI by elucidating the chain mediating roles of negative work-related rumination and emotional exhaustion. It also makes a significant forward in examining mediating mechanisms, notably the chain-mediated mechanism, through which AI awareness impacts employee outcomes.

This study investigates the patterns of artificial intelligence (AI) awareness among pre-service teachers at Mersin University, using both descriptive and inferential analyses to examine the levels of knowledge and attitudes towards AI. Understanding educators' AI awareness is essential as AI is increasingly integrated into education. A sample of 117 pre-service teachers completed the Artificial Intelligence Awareness Scale for Teachers, measuring Practical Knowledge, Beliefs and Attitudes, Attitude to Association, and Theoretical Knowledge. Statistical analysis were conducted to assess differences in AI awareness across demographic variables, including gender, academic department, and technology use. In addition, cluster analysis was performed, revealing three distinct clusters: (1) a moderate-awareness cluster, characterized by average levels of AI knowledge and attitudes across all dimensions; (2) a low-awareness cluster, characterized by limited AI knowledge and neutral-to-negative attitudes; and (3) a high-awareness cluster, characterized by strong AI knowledge and positive attitudes toward artificial intelligence. The findings that technology usage significantly influences pre-service teachers' AI awareness levels, whereas demographic factors such as gender and academic department do not. The results emphasize the need for differentiated AI training within teacher preparation programs, suggesting foundational AI literacy training for lower-awareness groups and more advanced content for those already possessing higher awareness.

This study aimed to determine teachers' level of artificial intelligence (AI) awareness and computational thinking (CT) skills. We also examined whether AI awareness and CT skills were related and how these variables differed across various sociodemographic and professional variables. This study, conducted in Turkey during the 2024-2025 academic year using a descriptive correlational survey design, involved 981 teachers (female = 514, male = 467) who volunteered to participate. Data were analysed using descriptive statistics, independent samples t-test, one-way analysis of variance (ANOVA), and Pearson correlation. The analysis indicated that teachers' AI awareness and CT skills were above average. Furthermore, significant differences in teachers' AI awareness and CT skills were revealed based on sociodemographic and professional variables. A positive statistically significant correlation was found between AI awareness and CT skills. Based on the results, we made recommendations for researchers and practitioners.

This study examines how higher education students’ awareness, literacy, attitudes and perceptions of artificial intelligence (AI) have been investigated in the scholarly literature. The objective is to map the development, main actors and thematic structure of this emerging field and to identify gaps for future research and practice. A bibliometric review was conducted using publications indexed in the Web of Science Core Collection and Scopus. The search string “artificial intelligence” AND “awareness” AND (“university student*” OR “higher education student*” OR “undergraduate student*”) was applied to titles, abstracts and keywords. After merging databases, removing duplicates and limiting the timespan to 2014–2025, the final corpus comprised 235 documents. Performance indicators (annual production, document types, sources, authors, institutions, countries) and science-mapping techniques (collaboration networks, keyword co-occurrence, thematic map and trend topics) were applied in R with the bibliometrix/Biblioshiny environment. The results show very limited activity until 2019, followed by exponential growth from 2023 onwards, with most publications produced in a small set of countries and STEM-oriented disciplines. A few journals and universities account for a substantial share of the output, while international co-authorship remains modest. Thematic analyses reveal motor themes around AI awareness and human-centred concerns, and around students in engineering and computing education, whereas critical and non-STEM perspectives are less developed. The study positions student AI awareness research in the exponential-growth stage of disciplinary development and provides the first field-level map focused specifically on higher education students, offering an evidence base for future empirical work, curriculum design and policy discussions.

Purpose This study aimed to develop a moderated mediation model to explain the relationship between artificial intelligence (AI) awareness and counterproductive work behavior, turnover intention. In this model, the authors assumed that interpersonal conflict mediates and that perceived organizational support and competitive psychological climate moderates the relationship between AI awareness and counterproductive work behavior, turnover intention. Design/methodology/approach An empirical study based on a sample of 1,129 Vietnamese employees at some enterprises of 6 fields with the highest level of AI application. Structural equation modelling analysis was used for hypothesis testing. Findings Analysis of the data demonstrates that AI awareness has a relationship with counterproductive behavior, interpersonal conflict and turnover intention. At the same time, the research results also confirm that interpersonal conflict affects counterproductive behavior and turnover intention. Moreover, interpersonal conflict mediates the effect of AI awareness on counterproductive behavior and turnover intention, and the moderating roles of perceived organizational support and competitive psychological climate has been confirmed. Research limitations/implications Sample data was only collected at a few Vietnamese enterprises in 6 fields with the highest level of application which are e-commerce, transportation and logistics, education, real estate, finance and agriculture, which may be limiting generalizability of research results. Future studies could include data from enterprises in different sectors or focus on a specific sector. Practical implications The authors offer several significant implications to reduce counterproductive work behavior and turnover intention in enterprises, such as by paying attention that the penetration and spread of AI or other smart technologies is inevitable in the future, ensuring make sure support from organization is available for the employees and creating a working environment of integrity and honesty in all situations based on trust, respect and fairness. Originality/value The study developed and verified a moderated mediated model on the relationship between AI awareness and counterproductive work behavior, turnover intention. The authors confirmed the mediating role of interpersonal conflict and the moderating role of perceived organizational support and competitive psychological climate in the relationship among AI awareness and counterproductive work behavior, turnover intention.

This article presents a comprehensive study conducted during the spring semester of 2024, aimed at exploring undergraduate computer science students’ perceptions, awareness, and understanding of generative artificial intelligence (GAI) tools within the context of their Artificial Intelligence (AI) courses. The research methodology employed qualitative techniques, including human-subject research and focus groups, to delve into students’ insights on the evolution of AI as delineated in the seminal textbook by Russell and Norvig. The study-initiated discussions on the historical development of AI, prompting students to reflect on the aspects that intrigued them the most, and to identify which historical concepts and methodologies, perhaps even those not directly covered in their curriculum, piqued their interest. Furthermore, the dialogue encompassed the learning methodologies highlighted in the textbook, seeking students’ feedback on the strategies that have been most effective for mastering complex AI theories and their practical applications. Interdisciplinary applications of AI were also discussed, encouraging students to contemplate AI’s role beyond the realm of computer science and its potential to foster innovative solutions across various fields. Finally, the conversation shifted towards students’ personal goals and aspirations in AI, urging them to consider how their perspectives have evolved in light of technological advancements, societal needs, and ethical considerations. The findings underscore a notable gap in students’ awareness of AI’s history and its current capabilities, indicating a need for educational strategies that not only deepen understanding but also foster a broader appreciation of AI’s potential. This study contributes valuable insights into enhancing AI education and encouraging interdisciplinary innovation among the next generation of computer scientists.

This study explores the mechanism and boundary conditions of employees using job crafting to cope with the impact of Artificial intelligence(AI) awareness based on the cognitive evaluation theory of stress and resource conservation theory.With 282 employees as the research subjects, the study found that AI awareness was positively related to the challenging appraisal, and organizational support strengthened this positive relationship, thereby affecting employees' job crafting.AI awareness was positively correlated with the threatening appraisal, and organizational support weakened this positive relationship.This study reveals the reasons and conditions for employees choosing job crafting to cope with AI awareness and expands the antecedent mechanism research of job crafting.It also provides suggestions for organizations to guide employees' job crafting from an evaluation perspective.