Factors influencing the adoption of artificial intelligence in libraries: A systematic literature review DOI
Khurram Shahzad,

Shakeel Ahmad Khan,

Abid Iqbal

и другие.

Information Development, Год журнала: 2025, Номер unknown

Опубликована: Янв. 21, 2025

The study aimed to identify the factors influencing adoption of artificial intelligence applications in libraries, find out associated challenges with AI apps, and develop a framework effectively implement tools libraries. A systematic literature review (SLR) was applied address study's objectives. 30 most relevant research papers published impact factor journals were selected conduct study. Findings showed that four major influenced These included transformation library services, provision innovative librarians users’ satisfaction, technological revolution. manifested challenges, skills knowledge barriers, financial organizational cultural barriers caused for adopt apps has added valuable existing body knowledge. It developed on evidence based datasets libraries efficiently.

Язык: Английский

Investigating factors of students' behavioral intentions to adopt chatbot technologies in higher education: Perspective from expanded diffusion theory of innovation DOI Creative Commons
Musa Adekunle Ayanwale, Mdutshekelwa Ndlovu

Computers in Human Behavior Reports, Год журнала: 2024, Номер 14, С. 100396 - 100396

Опубликована: Март 3, 2024

With the emergence of emerging 4IR technologies, AI application tools (chatbots) are becoming more and popular widespread in various fields, including education. This study investigates factors that influence undergraduate students' inclination to utilize tools, specifically chatbots, for educational purposes. We applied an expanded diffusion theory innovation framework examine relationships between relative advantages, compatibility, trialability, trust, perceived usefulness, ease use, behavioral intention. Data from 842 students were collected through a questionnaire using 7-point scale, findings analyzed SmartPLS 4.0.9.2 software with covariance-based structural equation model. The results confirm hypotheses regarding trust chatbots. Students who perceive benefits chatbots express strong intention use them academic perception compatibility positively influences their adoption intention, those have opportunity try out likely them, indicating importance trialability. Surprisingly, did not find direct suggesting presence other influencing or dynamics offer practical insights contribute theoretical understanding innovation. Future research can further explore these gain deeper into complexities chatbot enhance settings.

Язык: Английский

Процитировано

44
The Role of Perceived Trust in Embracing Artificial Intelligence Technologies: Insights from SMEs DOI
Mowafaq Salem Alzboon,

Hussam Mohd Al-Shorman,

Sabha Maria” Nawaf Alka’awneh

и другие.

Studies in computational intelligence, Год журнала: 2025, Номер unknown, С. 1 - 15

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

27
Exploring intention of undergraduate students to embrace chatbots: from the vantage point of Lesotho DOI Creative Commons
Musa Adekunle Ayanwale, Rethabile Rosemary Molefi

International Journal of Educational Technology in Higher Education, Год журнала: 2024, Номер 21(1)

Опубликована: Март 22, 2024

Abstract The increasing prevalence of Fourth Industrial Revolution (4IR) technologies has led to a surge in the popularity AI application tools, particularly chatbots, various fields, including education. This research explores factors influencing undergraduate students' inclination embrace specifically for educational purposes. Using an expanded diffusion theory innovation framework, study investigates relationship between relative advantages, compatibility, trialability, perceived trust, usefulness, ease use, and behavioral intention. 7-point scale, questionnaire was given 842 students collect data. analysis, conducted using SmartPLS 4.0.9.2 software with covariance-based structural equation model, produced significant findings. confirms hypotheses related trust associated chatbots. Notably, who perceive benefits chatbots show strong intention use them academic perception compatibility positively influences adoption intention, highlighting importance compatibility. Additionally, have opportunity trial are more likely them, emphasizing significance trialability. Interestingly, did not establish direct relationships suggests presence other influential or dynamics These findings offer practical insights contribute theoretical understanding innovation. Future can further explore these unravel complexities chatbot facilitate broader tools settings.

Язык: Английский

Процитировано

20
Artificial intelligence in Indian higher education institutions: a quantitative study on adoption and perceptions DOI
Silky Sharma, Gurinder Singh, Chandra Shekhar Sharma

и другие.

International Journal of Systems Assurance Engineering and Management, Год журнала: 2024, Номер unknown

Опубликована: Янв. 30, 2024

Язык: Английский

Процитировано

17
Gen-AI integration in higher education: Predicting intentions using SEM-ANN approach DOI

K. Keerthi Jain,

J. Naga Venkata Raghuram

Education and Information Technologies, Год журнала: 2024, Номер 29(13), С. 17169 - 17209

Опубликована: Фев. 21, 2024

Язык: Английский

Процитировано

17
AI and Digital Transformation in Higher Education: Vision and Approach of a Specific University in Vietnam DOI Open Access
Vũ Khánh Quý, Bùi Trung Thành, Abdellah Chehri

и другие.

Sustainability, Год журнала: 2023, Номер 15(14), С. 11093 - 11093

Опубликована: Июль 16, 2023

The Fourth Industrial Revolution is opening up new opportunities and challenges for all industries, professions, fields, aiming to bring humanity more optimal tools services. During the Revolution, digital transformation has been one of most critical problems. Artificial Intelligence (AI) Internet Things (IoT) are two technologies that have potential cause biggest breakout evolve in educational domain. In recent years, seen implementation across sectors, including education, healthcare, agriculture, transportation, other smart ecosystems. Among those areas, especially higher among challenging due diversity training programs, duration, subjects. makes it possible create ubiquitous learning environments, while artificial intelligence can completely transform way we learn teach. this paper, present process education Vietnam internationally analyze some characteristics Vietnamese process. Moreover, vision, approach, at universities low- middle-income countries from perspective Hung Yen University Technology Education Vietnam.

Язык: Английский

Процитировано

38
Understanding the Factors Influencing Higher Education Students’ Intention to Adopt Artificial Intelligence-Based Robots DOI Creative Commons
Mohammed A. M. AlGerafi, Yueliang Zhou, Hind Alfadda

и другие.

IEEE Access, Год журнала: 2023, Номер 11, С. 99752 - 99764

Опубликована: Янв. 1, 2023

Although there has been some progress, the integration of artificial intelligence into higher education remains far from sufficient. The demand for teachers will persist time; however, with introduction AI-based robots classrooms, role reduced to a minimum. purpose current study was evaluate Chinese students' intentions adopt educational purposes. Based on TAM3 model, proposes 14 hypotheses intention in education. data were collected and analyzed using PLS-SEM. findings revealed that 12 accepted two rejected. results indicate students are willing accept their However, an insignificant influence job relevance robot anxiety perceived usefulness ease use, respectively. this provide insight university administrations regarding significance Moreover, help developers, policy makers, administrators design implement fulfill contemporary needs.

Язык: Английский

Процитировано

31
Development of a Framework for Metaverse in Education: A Systematic Literature Review Approach DOI Creative Commons
Rita Roy,

Mohammad Dawood Babakerkhell,

Subhodeep Mukherjee

и другие.

IEEE Access, Год журнала: 2023, Номер 11, С. 57717 - 57734

Опубликована: Янв. 1, 2023

A more interactive learning environment is made possible by the metaverse, a made-up world with vastly expanding digital spaces. The metaverse development in synchronous communication that enables many users to share different experiences. This study proposes research framework for adopting education. systematic literature review using PRISMA methodology identified seventy-three papers on and Also, this provided various applications, challenges, dominant themes of research, future perspectives proposed discusses multiple drivers There are few education, so tries fill gap. also twenty-seven questions which can addressed researchers. will benefit students teachers across universities/ colleges schools.

Язык: Английский

Процитировано

28
Exploring Factors That Support Pre-service Teachers’ Engagement in Learning Artificial Intelligence DOI Creative Commons
Musa Adekunle Ayanwale,

Emmanuel Kwabena Frimpong,

Oluwaseyi Aina Gbolade Opesemowo

и другие.

Journal for STEM Education Research, Год журнала: 2024, Номер unknown

Опубликована: Апрель 12, 2024

Abstract Artificial intelligence (AI) is becoming increasingly relevant, and students need to understand the concept. To design an effective AI program for schools, we find ways expose knowledge, provide learning opportunities, create engaging experiences. However, there a lack of trained teachers who can facilitate students’ learning, so focus on developing capacity pre-service teach AI. Since engagement known enhance it necessary explore how engage in This study aimed investigate teachers’ with after 4-week at university. Thirty-five participants took part reported their perception 7-factor scale. The factors assessed survey included (cognitive—critical thinking creativity, behavioral, social), attitude towards AI, anxiety readiness, self-transcendent goals, confidence We used structural equation modeling approach test relationships our hypothesized model using SmartPLS 4.0. results supported all hypotheses, attitude, anxiety, being found influence engagement. discuss findings consider implications practice policy.

Язык: Английский

Процитировано

13
An explanatory study of factors influencing engagement in AI education at the K-12 Level: an extension of the classic TAM model DOI Creative Commons
Wei Li, Xiaolin Zhang, Jing Li

и другие.

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Июнь 17, 2024

Abstract Artificial intelligence (AI) holds immense promise for K-12 education, yet understanding the factors influencing students’ engagement with AI courses remains a challenge. This study addresses this gap by extending technology acceptance model (TAM) to incorporate cognitive such as intrinsic motivation (AIIM), readiness (AIRD), confidence (AICF), and anxiety (AIAX), alongside human–computer interaction (HCI) elements like user interface (UI), content (C), learner-interface interactivity (LINT) in context of using generative (GenAI) tools. By including these factors, an expanded is presented capture complexity student education. To validate model, 210 Chinese students spanning grades K7 K9 participated 1 month artificial course. Survey data structural equation modeling reveal significant relationships between HCI perceived usefulness (PU) ease use (PEOU). Specifically, AIIM, AIRD, AICF, UI, C, LINT positively influence PU PEOU, while AIAX negatively affects both. Furthermore, PEOU significantly predict attitudes toward curriculum learning. These findings underscore importance considering design implementation education initiatives. providing theoretical foundation practical insights, informs development aids educational institutions businesses evaluating optimizing AI4K12 strategies.

Язык: Английский

Процитировано

8