Lecture notes in networks and systems, Journal Year: 2025, Volume and Issue: unknown, P. 610 - 620
Published: Jan. 1, 2025
Language: Английский
Lecture notes in networks and systems, Journal Year: 2025, Volume and Issue: unknown, P. 610 - 620
Published: Jan. 1, 2025
Language: Английский
Computers & Education, Journal Year: 2025, Volume and Issue: unknown, P. 105250 - 105250
Published: Jan. 1, 2025
Language: Английский
Citations
1European Journal of Education, Journal Year: 2025, Volume and Issue: 60(1)
Published: Feb. 18, 2025
ABSTRACT The arrival of generative artificial intelligence (GAI) technologies marks a significant transformation in the educational landscape, with implications for teaching and learning performance. These can generate content, simulate interactions, adapt to learners' needs, offering opportunities interactive experiences. In China's education sector, incorporating GAI address challenges, enhance practices, improve This study scrutinises impact on performance focusing mediating roles e‐learning competence (EC), desire (DL), beliefs about future (BF), as well moderating role facilitating conditions amongst Chinese educators. Data was collected from 411 teachers across various institutions China using purposive sampling. PLS‐SEM ANN were employed assess suggested structural model. results indicate that significantly influence by EC, DL, BF roles. Furthermore, positively moderate association BF. underscores critical self‐determination theory shaping effective incorporation education, valuable insights outcomes sector.
Language: Английский
Citations
1American Journal of Economics and Sociology, Journal Year: 2024, Volume and Issue: 83(3), P. 567 - 607
Published: Feb. 24, 2024
Abstract AI advancements are poised to substantially modify human abilities in the foreseeable future. They include integration of Brain–Computer Interfaces (BCIs) augment cognitive functions, application gene editing, and utilization AI‐powered robotic exoskeletons enhance physical strength. This study employs a comprehensive analytical framework combining factor analysis, clustering, ANOVA, logistic regression investigate public attitudes toward these transformative technologies. Our findings reveal three distinct clusters opinion reflecting varying optimism concern Cluster 1 (1574 participants) held positive view with high excitement while 2 (1334 showed balanced stance. 3 (2199 expressed heightened despite some excitement. Notably, regional disparities, particularly between urban rural participants, emerge as prominent influencing (ANOVA, F = 15.2, p < 0.001). Furthermore, identifies key influencers perception, highlighting significant roles played by religion factors. The implications extend beyond understanding sentiment. underscore need for informed policies that promote education awareness about technologies, address ethical concerns, engage decision‐making processes. As society navigates this technological landscape, nuanced becomes paramount, guiding regulation, innovation, engagement strategies. provides valuable insights into intricate dynamics surrounding acceptance highlights importance adapting measures evolving perceptions among general public.
Language: Английский
Citations
8Computers and Education Artificial Intelligence, Journal Year: 2024, Volume and Issue: 7, P. 100274 - 100274
Published: Aug. 3, 2024
In an era where artificial intelligence (AI) is reshaping educational paradigms, this study explores AI-based chatbot adoption in higher education among students and educators. Employing a Structural Equation Modeling (SEM) approach, the research focuses on developing validating comprehensive model to understand multifaceted factors impacting acceptance use of these chatbots. The methodology integrates extensive literature review, construction theoretical model, administration detailed questionnaire representative sample from sector, coupled with advanced SEM techniques for data analysis interpretation. validates model's robustness highlights relationships between several key affecting users' perspectives chatbots adoption. Results reveal predominantly positive perception towards AI-chatbots both educators, underscoring potential substantially enrich their journey. However, it also uncovers critical concerns pertaining trust, privacy, response bias, information accuracy. Moreover, offers valuable insights into how moderators such as technological proficiency, user roles, gender influence relationships. This emphasizes need customizing deployment meet diverse needs users effectively. Contributing robust framework understanding perceptions patterns, actionable leaders, policymakers, technology developers. It lays groundwork future research, including longitudinal studies evaluate long-term impact technologies, investigations effect learning outcomes, explorations ethical privacy considerations involved.
Language: Английский
Citations
8British Educational Research Journal, Journal Year: 2024, Volume and Issue: unknown
Published: Oct. 19, 2024
Abstract The adoption of generative artificial intelligence (GAI) tools, such as ChatGPT, in higher education presents numerous opportunities and challenges. use GAI technologies various fields, including education, has accelerated technology develops. widely used language model developed by OpenAI, become progressively more important, especially the field education. This study employs acceptance to investigate factors influencing employment ChatGPT within sector Pakistan. employed PLS‐SEM method for probing data collected from 368 Pakistani university students. findings indicate that trust positively mediates affiliation between self‐efficacy, actual use, information interaction. Further, usefulness ease significantly moderate association self‐efficacy trust. Educators must encourage students safely preserve their critical thinking, problem‐solving abilities creativity during assessments. contributes understanding AI tools are educational settings provides insights administrators policymakers aiming implement these effectively.
Language: Английский
Citations
8Education and Information Technologies, Journal Year: 2024, Volume and Issue: unknown
Published: Nov. 22, 2024
Language: Английский
Citations
7Asia Pacific Journal of Tourism Research, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 20
Published: Sept. 24, 2024
Language: Английский
Citations
6Journal of Librarianship and Information Science, Journal Year: 2024, Volume and Issue: unknown
Published: Aug. 19, 2024
The use of artificial intelligence (AI) tools, such as chatbots, has significantly increased in academia and research. present study seeks to determine the key factors influencing chatbot adoption, well attempts validate unified theory acceptance technology (UTAUT) context AI chatbots adoption among research scholars. data for this were collected through purposive sampling using a cross-sectional survey. population comprised scholars enrolled three public sector universities Pakistan. eight-factor proposed measurement model was estimated confirmatory factor analysis (CFA) based on 30 valid items. goodness fit indices suggest favourable χ 2 = 1.710, DF 381; p 0.000; IFI .902; TLI 0.886, CFI 0.900, RMSEA 0.056. Our affirms that social influence, trust, facilitating conditions play pivotal roles primary predictors behavioural intentions suggests perceived risks associated with due their potential misuse can be minimized by effectively implementing user guidelines, developing literacy Information professionals ethical libraries an important role “building bridge” between cutting-edge capabilities information users’ needs rights. holds substantial understanding influence performance expectancy, effort risk, intention adoption. This contributes limited body investigating UTAUT additional constructs trust risk.
Language: Английский
Citations
5Journal of Applied Research in Higher Education, Journal Year: 2024, Volume and Issue: unknown
Published: March 28, 2024
Purpose This paper aims to explore students’ intention use and actual of the artificial intelligence (AI)-based chatbot such as ChatGPT or Google Bird in field higher education an emerging economic context like Bangladesh. Design/methodology/approach The present study uses convenience sampling techniques collect data from respondents. It applies partial least squares structural equation modeling (PLS-SEM) for analyzing a total 413 responses examine study’s measurement model. Findings results that perceived ease (PEOU) negatively affects adopt AI-powered chatbots (IA), whereas university usefulness (PU) influences their IA positively but insignificantly. Furthermore, time-saving feature (TSF), academic self-efficacy (ASE) electronic word-of-mouth (EWOM) have positive direct impact on IA. finding also reveals students' significantly AI-based (AU). Precisely, out five constructs, TSF has strongest intentions chatbots. Practical implications Students who are not aware usage benefits might ignore these language models. On other hand, developers may be conscious crucial drawbacks product per perceptions multiple users. However, findings transmit clear message about advantages users developers. Therefore, will enhance chatbots’ functionality usage. Originality/value alert teachers, students policymakers educational institutions understand outcomes accept OpenAI’s ChatGPT. Outcomes notify AI-product boost chatbot’s quality terms timeliness, user-friendliness, accuracy trustworthiness.
Language: Английский
Citations
4Information Development, Journal Year: 2024, Volume and Issue: unknown
Published: June 5, 2024
The aim of present study was to measure the relationship UTAUT (Unified Theory Acceptance and Use Technology) TAM (Technology Model) variables regarding AI technology AI-based applications acceptance in education sector. Research carried out by using PRISMA (Preferred reporting items for systematic review meta-analysis) guidelines. relevant studies were searched from major databases that included a) Scopus, b) Web Science. Initial search retrieved 309 titles, 30 articles conference papers selected following process. Data analysed CMA (Comprehensive Meta-analysis) Meta-Essential software. Findings exhibit between BI accept high (PE → BI), medium (EE BI, SI low (FC BI). magnitude constructs remained all paths (PU AT, PEOU PU Theoretically, this meta-analysis provided a panoramic picture two leading models acceptance/adoption This way forward researchers extend research on including ChatGPT, intelligent tutoring, robots, Chatbots, voice assistants. Practically, findings are useful IT companies, decision makers educational institutes designing implementing applications.
Language: Английский
Citations
4