The pervasive integration of digital technologies in higher education has introduced significant psychological challenges for students. This study proposes the digital stress triad model, conceptualizing technostress, misinformation exposure, and information overload as key stressors affecting student well-being. Using structural equation modeling (SEM) on data from 407 students, results show strong independent effects: Technostress reduces mental well-being (beta = -0.50, p = .001), while misinformation exposure (beta = 0.61, p = .001) and information overload (beta = 0.56, p = .001) increase psychological strain. Psychological strain shows a marginal negative effect on well-being (beta = -0.29, p = .096). No significant interaction or moderation effects were found, supporting an additive model of digital stress. The findings provide an empirical foundation for the model and inform practical interventions, such as digital wellness tools and misinformation resilience strategies, to improve student well-being in digital learning environments.
This study examines university lecturers' attitudes toward digitization in higher education and how they influence their actual practices in the teachers' training. Sixty-two lecturers participated in the study. A methodology involving interviews and classroom observations was used to identify similarities and differences in university lecturers' strategies for integrating digital technologies in teaching. The study provides a reliable picture of lecturers' attitudes toward digital technologies in the training of future teachers, as well as their approaches to their integration into real practice. A correlation was found between lecturers' attitudes and the range and diversity of digital practices. Lecturers who exhibited positive and critical attitudes incorporated more interactive and creative teaching activities, whereas those with neutral or pragmatic attitudes tended to adopt more limited use of digital tools. The study highlights the need to improve digital practices in teacher training programs in Bulgaria by encouraging university lecturers to participate in lifelong learning activities focused on the field of digital pedagogical competence.
This study investigates the long-standing employability gap among Tunisian civil engineering graduates, where mismatching between university education and construction industry demands irks labor market readiness. Through a mixed-methods approach, entailing semi-structured interviews with 25 industry leaders and action research within a leading Tunisian construction firm, this article reveals deficiencies in three domains: applied technical competencies, digital skills, and essential transversal skills. Findings show that employers refer to graduates' lack of proficiency in fundamental digital tools artificial intelligence (AI)-driven project management tools, and Computer-Aided Design (CAD)/ Computer-Aided Manufacturing (CAM) technologies. The novelty of this research is grounded in analyzing both current and future competence needs of the sector, particularly in response to ongoing technological transformation through continuous organizational feedback.
Organisational success increasingly depends on data-driven decision-making, which is making data literate talent essential. However, building a data-literate workforce is challenging, as data literacy is complex, context-dependent, and varies across sectors. This study explores the challenges middle managers face in using data for decision-making within the Queensland energy sector, which relies heavily on data to improve data resources and operations. The results from interviews with 15 middle managers showed significant disparities in data literacy levels, ranging from minimal awareness to advanced competencies. Those with higher levels of data literacy recognize its importance in deriving actionable insights and making informed business decisions, relying on tools such as spreadsheets, Tableau, and Python to analyse and interpret data. Conversely, individuals with a limited understanding of data literacy often face challenges in leveraging data effectively, leading to inefficiencies and missed opportunities.
Organisational success increasingly depends on data-driven decision-making, which is making data literate talent essential. However, building a data-literate workforce is challenging, as data literacy is complex, context-dependent, and varies across sectors. This study explores the challenges middle managers face in using data for decision-making within the Queensland energy sector, which relies heavily on data to improve data resources and operations. The results from interviews with 15 middle managers showed significant disparities in data literacy levels, ranging from minimal awareness to advanced competencies. Those with higher levels of data literacy recognize its importance in deriving actionable insights and making informed business decisions, relying on tools such as spreadsheets, Tableau, and Python to analyse and interpret data. Conversely, individuals with a limited understanding of data literacy often face challenges in leveraging data effectively, leading to inefficiencies and missed opportunities.
This study investigates the long-standing employability gap among Tunisian civil engineering graduates, where mismatching between university education and construction industry demands irks labor market readiness. Through a mixed-methods approach, entailing semi-structured interviews with 25 industry leaders and action research within a leading Tunisian construction firm, this article reveals deficiencies in three domains: applied technical competencies, digital skills, and essential transversal skills. Findings show that employers refer to graduates' lack of proficiency in fundamental digital tools artificial intelligence (AI)-driven project management tools, and Computer-Aided Design (CAD)/ Computer-Aided Manufacturing (CAM) technologies. The novelty of this research is grounded in analyzing both current and future competence needs of the sector, particularly in response to ongoing technological transformation through continuous organizational feedback.
In response to the global emergence of artificial intelligence (AI), the Government of Punjab, Pakistan, conducted a pilot project in 2024, introducing AI-powered digital textbooks for Grade 12 English learners. The project included 80 teachers and 400 learners from Lahore, Pakistan. The present study explores the perspectives of the learners and teachers who participated in this pilot initiative. A concurrent mixed-methods research design was employed, with a sample of 100 students and 40 teachers selected through simple random sampling. Structured questionnaires were used to collect quantitative data from students, while interviews were conducted with teachers. Quantitative data were analyzed using SPSS 27, and thematic analysis of qualitative data was carried out using Claude. ai. The findings revealed that students viewed AI-powered digital textbooks as a novel, dynamic, engaging, and impactful method for learning English. Similarly, teachers regarded AI-powered digital textbooks as highly beneficial for enhancing students' English language proficiency.
This study aims to determine the factors affecting the mathematical achievement of gifted students studying at science and art centers in Bursa province and to predict this achievement using various machine learning models. In the study, variables, such as demographic information, family structure, study habits, motivation level, technology use, and social activities were analyzed in line with the data collected from 151 students. Methods, such as decision trees, support vector machines, and artificial neural networks, were used by utilizing the fields of educational data mining and learning analytics. The results obtained showed that some variables significantly affected the mathematical achievement of students. The study provides important findings in terms of developing educational policies and individualized teaching strategies.
This study examined the impact of a blended teaching approach versus traditional instruction on listening comprehension and strategy use among EFL students in a Taiwanese university. Using a quasi-experimental design, 103 low-intermediate students were divided into experimental (n=52) and control (n=51) groups over 18 weeks. The experimental group engaged in pre-class activities (audio, quizzes, videos) and collaborative in-class tasks, while the control group received traditional instruction. Results showed the experimental group had significantly greater listening improvement (mean increase: 10.26 vs. 5.00 points) and higher metacognitive and social/affective strategy use. Additionally, 84% reported increased listening confidence. Findings highlight the effectiveness of blended learning in enhancing EFL listening skills.
This study investigates students' perceptions of rehearsal (test preparation) and testing after the pandemic forced increased online teaching use and experimentation. Data was gathered from information and decision sciences (IDS) students in an underrepresented minority (URM) serving university. Responses from 136 participants were analyzed and revealed four major findings. The single most interesting finding was that students, on average, preferred graded rehearsal activities over optional activities. Second, rehearsal activities were more important in online than face-to-face settings. Third, students overwhelmingly prefer online exams, on which they feel they perform better and which they find less anxiety-producing. Finally, despite research showing the importance of online proctoring for major defined-answer testing, instructor use of proctoring and monitoring is split between those who do and do not use concrete methods, with lockdown browser being common and live webcam less common. These interconnected findings are discussed.
This study examined the impact of a blended teaching approach versus traditional instruction on listening comprehension and strategy use among EFL students in a Taiwanese university. Using a quasi-experimental design, 103 low-intermediate students were divided into experimental (n=52) and control (n=51) groups over 18 weeks. The experimental group engaged in pre-class activities (audio, quizzes, videos) and collaborative in-class tasks, while the control group received traditional instruction. Results showed the experimental group had significantly greater listening improvement (mean increase: 10.26 vs. 5.00 points) and higher metacognitive and social/affective strategy use. Additionally, 84% reported increased listening confidence. Findings highlight the effectiveness of blended learning in enhancing EFL listening skills.
In response to the global emergence of artificial intelligence (AI), the Government of Punjab, Pakistan, conducted a pilot project in 2024, introducing AI-powered digital textbooks for Grade 12 English learners. The project included 80 teachers and 400 learners from Lahore, Pakistan. The present study explores the perspectives of the learners and teachers who participated in this pilot initiative. A concurrent mixed-methods research design was employed, with a sample of 100 students and 40 teachers selected through simple random sampling. Structured questionnaires were used to collect quantitative data from students, while interviews were conducted with teachers. Quantitative data were analyzed using SPSS 27, and thematic analysis of qualitative data was carried out using Claude.ai. The findings revealed that students viewed AI-powered digital textbooks as a novel, dynamic, engaging, and impactful method for learning English. Similarly, teachers regarded AI-powered digital textbooks as highly beneficial for enhancing students' English language proficiency.
It could be argued that the current adult education paradigm aligns with a liberal knowledge economy. A more critical perspective is Paulo Freire's banking education concept that removes criticality from a learner's repertoire and facilitates alignment with the prevalent liberal education and its hegemonic objectives. Drawing from Paulo Freire's (1990) Pedagogy of the Oppressed, Flores (2017) suggested that banking education teaches the oppressed to accept the oppressor's social framework. In this paper, and through the analysis of news media articles and policy documents, the author examines the phenomenon of terrorism and how a Western worldview constructs and engages in meaning-making for the reader. As a result, the author proposes a more critical cognizant adult learning model. Drawing from Habermasian theory, the need to cultivate humanity, and criticality as practiced by Critical Discourse Analysis, the author proposes a learning model construct of evolving criticality, emancipatory in intent, complex in its components and their relationships, with the intent of giving back agency to citizens.
Educational technology facilitates convenient access to online programs for adult students but also presents challenges. Using a conceptual framework of Knowles' andragogy process of program development and learner interaction theory, this study examined ed tech in an online degree program designed to serve adult students. Participants included adult educators and students from an online degree program at a large, public, Hispanic-Serving Institution in the Southwest region of the United States. Using qualitative methods, data collection comprised observations and documents, and data analysis used Creswell and Creswell's five-step process. Findings illuminate three major online facilitations: Ed tech facilitates an andragogical process of development for programs, traditional and new learner interactions, and the research process of adult students. The findings offer implications to develop the theory, practice, and policy of ed tech in online learning for adult students and educators.
The emergence of generative AI technologies has provoked considerable debate among educators regarding their role in education. This study is an investigation of the benefits, disadvantages, and potential strategies for integrating generative AI in educational settings by analyzing societal impacts based on a literature review. We have surveyed the influence of generative AI in education through sources from peer-reviewed journals. The main findings show that generative AI can enhance accessibility and customization in learning for individual learners' needs and pacing. But there are problems with algorithmic biases, discrimination, and data privacy issues, too. This study advocates for mitigating bias, data transparency, and promotion and evaluation of AI policy and research. Generative AI in education hinges on how it is responsibly integrated and observes ethical guidelines, by way of the constant assessment that will guarantee its potential in revolutionizing learning.
We examined the impact of secondary Career and Technical Education (CTE) credit-taking on students attaining full-time employment following graduation from high school in the United States, and whether such credit-taking impacted students entering employment in a related field. We focused on occupational programs, and we used four levels of CTE credit-taking (Aliaga, 2023). Similarly, we examined the impact of job-related school strategies on full-time employment and working in a related field. This study was conducted using data from the United States High School Longitudinal Study of 2009. We found that different levels of CTE credit-taking do predict working full-time after school, depending on the occupational program, and they also predict working in a related field.
Educational technology facilitates convenient access to online programs for adult students but also presents challenges. Using a conceptual framework of Knowles' andragogy process of program development and learner interaction theory, this study examined ed tech in an online degree program designed to serve adult students. Participants included adult educators and students from an online degree program at a large, public, Hispanic-Serving Institution in the Southwest region of the United States. Using qualitative methods, data collection comprised observations and documents, and data analysis used Creswell and Creswell's five-step process. Findings illuminate three major online facilitations: Ed tech facilitates an andragogical process of development for programs, traditional and new learner interactions, and the research process of adult students. The findings offer implications to develop the theory, practice, and policy of ed tech in online learning for adult students and educators.
Power distance (PD), a cultural value denoting acceptance of asymmetrical power relationships, influences the force of rhetoric used by a writer to address their reader. However, AI technologies such as ChatGPT lack an explicit awareness of PD, which could affect the quality of AI-generated persuasive texts used for language learning. To investigate this issue, 200 persuasive essays written by ChatGPT were compared to 200 essays written by L1-English university learners. Three elements of formulaic language related to PD were examined: stances, modals, and pronoun deixis. Differences in stances (z = -3.411; p = .001) and modals (z = -2.100; p = .036) were both significant according to the Wilcoxon signed ranks formula, whereas differences in pronoun deixis were nearly significant (z = -1.917; p = .055). Overall, language of ChatGPT appears generic and incomplete, suggesting that consistent and uniform expressions are being borrowed from an LLM training corpus to mimic aspects of PD. Limitations of AI highlight a need for pedagogical emphasis of culturally imbued discourse.
Power distance (PD), a cultural value denoting acceptance of asymmetrical power relationships, influences the force of rhetoric used by a writer to address their reader. However, AI technologies such as ChatGPT lack an explicit awareness of PD, which could affect the quality of AI-generated persuasive texts used for language learning. To investigate this issue, 200 persuasive essays written by ChatGPT were compared to 200 essays written by L1-English university learners. Three elements of formulaic language related to PD were examined: stances, modals, and pronoun deixis. Differences in stances (z = -3.411; p = .001) and modals (z = -2.100; p = .036) were both significant according to the Wilcoxon signed ranks formula, whereas differences in pronoun deixis were nearly significant (z = -1.917; p = .055). Overall, language of ChatGPT appears generic and incomplete, suggesting that consistent and uniform expressions are being borrowed from an LLM training corpus to mimic aspects of PD. Limitations of AI highlight a need for pedagogical emphasis of culturally imbued discourse.
This conceptual article provides a comprehensive overview of the current status of Artificial Intelligence (AI) integration and its influence on adult education. It discusses generative AI technologies and their potential applications in adult education settings, examines the opportunities and ethical challenges associated with integrating AI, and provides insights into emerging trends. The article consists of five sections. The introduction provides a rationale as to why AI should be integrated into adult education. Second, it describes evolving AI technologies such as Large Language Models (LLM) for personalized learning, Machine Learning Algorithms for adaptive learning systems, Virtual Reality (VR) and Augmented Reality (AR) for immersive learning experiences, Chatbots and virtual assistants for learner support and guidance, and Data Learning Analytics (DLA) for tracking learner progress and performance into adult education. Section three explores the ethical implications of AI in adult education, including academic honesty and integrity, data privacy, and algorithmic bias. In section four, emerging trends and future directions are discussed. The final section considers policy implications and makes recommendations for adult educators working to develop AI-enriched adult education.
