Frontiers of digital education., Год журнала: 2025, Номер 2(1)
Опубликована: Март 1, 2025
Язык: Английский
Frontiers in Education, Год журнала: 2024, Номер 8
Опубликована: Янв. 8, 2024
Incorporating artificial intelligence (AI) into education, specifically through generative chatbots, can transform teaching and learning for education professionals in both administrative pedagogical ways. However, the ethical implications of using chatbots must be carefully considered. Ethical concerns about advanced have yet to explored sector. This short article introduces associated with introducing platforms such as ChatGPT education. The outlines how handling sensitive student data by presents significant privacy challenges, thus requiring adherence protection regulations, which may not always possible. It highlights risk algorithmic bias could perpetuate societal biases, problematic. also examines balance between fostering autonomy potential impact on academic self-efficacy, noting over-reliance AI educational purposes. Plagiarism continues emerge a critical concern, AI-generated content threatening integrity. advocates comprehensive measures address these issues, including clear policies, plagiarism detection techniques, innovative assessment methods. By addressing argues that educators, developers, policymakers, students fully harness creating more inclusive, empowering, ethically sound future.
Язык: Английский
Процитировано
33
Education and Information Technologies, Год журнала: 2024, Номер unknown
Опубликована: Авг. 24, 2024
Язык: Английский
Процитировано
17
Journal of Organizational Behavior, Год журнала: 2025, Номер unknown
Опубликована: Янв. 1, 2025
ABSTRACT As artificial intelligence (AI) becomes increasingly integrated in teams, understanding the factors that drive trust formation between human and AI teammates crucial. Yet, emergent literature has overlooked impact of third parties on human‐AI teaming. Drawing from social cognitive theory teams research, we suggest how much a teammate perceives an as trustworthy, engages behaviors toward AI, determines focal employee's perceptions behavior this teammate. Additionally, propose these effects hinge trustworthiness . We test predictions across two studies: (1) online experiment comprising individuals with work experience examines disembodied trustworthiness, (2) incentivized observational study investigates embodied AI. Both studies reveal teammate's perceived of, in, strongly predict behavioral Furthermore, relationship vanishes when employees perceive their less trustworthy. These results advance our third‐party formation, providing organizations insights for managing influences teams.
Язык: Английский
Процитировано
2
Journal of International Education in Business, Год журнала: 2025, Номер unknown
Опубликована: Март 3, 2025
Purpose This study explores the factors influencing artificial intelligence (AI)-driven decision-making proficiency (AIDP) among management students, focusing on foundational AI knowledge, data literacy, problem-solving, ethical considerations and collaboration skills. The research examines how these competencies enhance self-efficacy engagement, with curriculum design, industry exposure faculty support as moderating factors. aims to provide actionable insights for educational strategies that prepare students AI-driven business environments. Design/methodology/approach adopts a hybrid methodology, integrating partial least squares structural equation modeling (PLS-SEM) neural networks (ANNs), using quantitative collected from 526 across five Indian universities. PLS-SEM model validates linear relationships, while ANN captures nonlinear complexities, complemented by sensitivity analyses deeper insights. Findings results highlight pivotal roles of literacy problem-solving in fostering self-efficacy. Behavioral, cognitive, emotional social engagement significantly influence AIDP. Moderation analysis underscores importance design enhancing efficacy constructs. identifies most critical predictors AIDP, respectively. Research limitations/implications is limited central universities may require contextual adaptation global applications. Future could explore longitudinal impacts AIDP development diverse cultural settings. Practical implications findings designers, policymakers educators integrate into education. Emphasis experiential learning, frameworks interdisciplinary preparing AI-centric landscapes. Social By equipping future leaders proficiency, this contributes societal readiness technological disruptions, promoting sustainable contexts. Originality/value To author’s best uniquely integrates analyze interplay shaping It advances theoretical models linking learning theories practical education strategies, offering comprehensive framework developing students.
Язык: Английский
Процитировано
2
International Journal of Human-Computer Interaction, Год журнала: 2024, Номер unknown, С. 1 - 22
Опубликована: Июль 12, 2024
Язык: Английский
Процитировано
9
Acta Psychologica, Год журнала: 2024, Номер 249, С. 104442 - 104442
Опубликована: Авг. 6, 2024
Prior research highlights the critical role of AI in enhancing second language (L2) learning. However, factors that practically affect L2 learners to engage with resources are still underexplored. Given widespread availability digital devices among college students, they particularly poised benefit from AI-assisted As such, this study, grounded an extended Technology Acceptance Model (TAM), investigates predictors learners' actual use tools, focusing on self-efficacy, AI-related anxiety, and their overall attitude toward AI. Data was gathered 429 at Chinese universities via online questionnaire, utilizing four established scales. Through structural equation modeling (SEM) AMOS 24, results indicate self-efficacy could negatively positively influence both tools. Besides, anxiety predicted Moreover, a positive predictor through reducing AI, or combination both. This study also discusses theoretical pedagogical implications suggests directions for future research.
Язык: Английский
Процитировано
8
European Journal of Education, Год журнала: 2025, Номер 60(1)
Опубликована: Янв. 7, 2025
ABSTRACT As artificial intelligence (AI) technology continues to advance, its influences across various industries have grown, leading increasing levels of anxiety, including that in education. Nonetheless, terms current knowledge, the literature lacks a valid scale measure AI anxiety among EFL teachers, particularly university teachers. Moreover, underlying dimensions this construct yet be clarified. Against these gaps, study aims develop and validate assess teachers China. We used qualitative interviews quantitative surveys combined identify key In so doing, 251 Chinese completed newly designed scale. The result exploratory factor analyses indicated five 21 items questionnaire. Five were identified: technical proficiency, job displacement, technological support, student experience research development. Next, another 415 participated validating confirmatory analysis demonstrated strong reliability, validity an acceptable model fit. This new provides useful tool for assessing highlights unique challenges they face adapting AI, offering basis future targeted support.
Язык: Английский
Процитировано
1
Education and Information Technologies, Год журнала: 2025, Номер unknown
Опубликована: Янв. 22, 2025
Язык: Английский
Процитировано
1
Information Development, Год журнала: 2025, Номер unknown
Опубликована: Янв. 31, 2025
In recent years, the adoption of AI technologies in academia has increased, prompting a need to explain factors driving scholars adopt or plan research routines. This study integrates three models into one integrated model: TAM, UTAUT, and SCT. These are combined understand how GenAI self-efficacy, perceived ethics, academic integrity, social influence, facilitating conditions, risks, ease use, usefulness influenced participants’ intention research. Following this, data were collected from Egyptian academics linked universities. There 742 responses this question. Data analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The paper's results showed that ethics significantly related perceptions usefulness, use GenAI. Facilitating conditions have negative effect on risk does not affect significantly. Notably, result found integrity GenAI's usage utility. guide illustrates universities must take proactive steps influence will be used reinforces importance these tools within an ethical lens. paper emphasizes balance generative practices. It examines role attitudes toward AI. They represent step forward our understanding induce adoption–in case, context, specifically Egypt. Additionally, it places sound emphasis technology can beneficial whilst advocating for sensible approach application, which includes principles.
Язык: Английский
Процитировано
1
Acta Psychologica, Год журнала: 2024, Номер 248, С. 104376 - 104376
Опубликована: Июль 1, 2024
The positive impact of Artificial Intelligence (AI) on second language (L2) learning is well-documented. An individual's attitude toward AI significantly influences its adoption. Despite this, no specific scale has been designed to measure this attitude, particularly in the Chinese context. To address gap, our study aims construct AI-Assisted L2 Learning Attitude Scale for College Students (AL2AS-CCS) and evaluate reliability, validity, relationship with proficiency. Our research comprises two phases, each involving separate samples. In Phase One (Sample 1: n = 379), we conducted exploratory factor analysis (EFA) determine structure AL2AS-CCS. resulting two-factor consists 12 items, categorized into cognitive behavioral components. Two 2: 429), performed confirmatory (CFA) validate assess model fit. CFA Sample 2 confirmed demonstrated a good Additionally, AL2AS-CCS exhibited high criterion internal consistency, cross-gender invariance. findings suggest that valid measurement tool assessing college students' AI-assisted learning. Moreover, students were discovered maintain moderately correlation was identified between their
Язык: Английский
Процитировано
6