Faculty acceptance and use of generative artificial intelligence in their practice DOI Creative Commons
Julián Nevárez Montes, Josemaría Elizondo-García

Frontiers in Education, Journal Year: 2025, Volume and Issue: 10

Published: Feb. 3, 2025

The effective integration of Generative Artificial Intelligence (GenAI) into educational practices holds promise for enhancing teaching and learning processes. Examining faculty acceptance use GenAI implementation can provide valuable insights the conditions necessary its successful application. This study consisted a survey to measure in practice 208 members at private university Mexico. instrument used integrates elements Technology Acceptance Model (TAM) Theory Reasoned Action (TRA). original questionnaire was translated Spanish validated by experts ensure reliability validity new context. Overall, dimensions obtained middle-high results. Behavioral intention highest values whereas Subjective norm lowest values. Significant differences regarding disciplines sociodemographics were not identified. Also, is positively moderate correlated with produce text. identified level among toward environments leads expect promising future practices. In addition, further research on student impact training settings are encouraged.

Language: Английский

Generative AI in Curriculum Development in Higher Education DOI
Muhammad Usman Tariq

Advances in educational technologies and instructional design book series, Journal Year: 2024, Volume and Issue: unknown, P. 231 - 262

Published: Aug. 27, 2024

This chapter explores the transformative role of Generative Artificial Intelligence (Generative AI) in reshaping development higher education curricula. AI, as exemplified by advanced models like GPT-3, employs sophisticated algorithms to generate scientifically relevant content, surpassing traditional norms teaching and learning. The overview delves into fundamental principles emphasizing significance generative such Adversarial Networks (GANs) technical intricacies involved their training. Essentially, discourse on AI curriculum underscores its disruptive potential education. By providing personalized adaptable pathways for growth, addresses diverse needs students, fostering engagement comprehension. It also overcoming limitations education, facilitating creation virtual laboratories simulations that enhance hands-on

Language: Английский

Citations

28
ChatGPT for Academic Purposes: Survey Among Undergraduate Healthcare Students in Malaysia DOI Open Access
Renjith George, Htoo Htoo Kyaw Soe, Preethy Mary Donald

et al.

Cureus, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 27, 2024

Background: The impact of generative artificial intelligence-based Chatbots on medical education, particularly in Southeast Asia, is understudied regarding healthcare students' perceptions its academic utility. Sociodemographic profiles and educational strategies influence prospective practitioners' attitudes toward AI tools. Aim objectives: This study aimed to assess university knowledge, attitude, practice ChatGPT for purposes. It explored chatbot usage frequency, purposes, satisfaction levels, associations between age, gender, variables. Methodology: Four hundred forty-three undergraduate students at a Malaysian tertiary institute participated, revealing varying awareness levels ChatGPT's Despite concerns about accuracy, ethics, dependency, participants generally held positive academics. Results: Multiple logistic regression highlighted demographics, use. MBBS were significantly more likely use academics than BDS FIS students. Final-year exhibited the highest likelihood Higher knowledge correlated with increased usage. Most users (45.8%) employed aid specific assignment sections while completing most work independently. Some did not it (41.1%), others heavily relied (9.3%). Users also various from generating questions understanding concepts. Thematic analysis responses showed data plagiarism, ethical issues, dependency tasks. Conclusion: aids creating guidelines implementing GAI chatbots emphasizing benefits, risks, informing developers educators potential academia.

Language: Английский

Citations

21
Could AI Ethical Anxiety, Perceived Ethical Risks and Ethical Awareness About AI Influence University Students’ Use of Generative AI Products? An Ethical Perspective DOI
Wenjuan Zhu, Lei Huang,

Xinni Zhou

et al.

International Journal of Human-Computer Interaction, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 23

Published: March 8, 2024

The study aims to explore the factors that influence university students' behavioral intention (BI) and use behavior (UB) of generative AI products from an ethical perspective. Referring decision-making theory, research model extends UTAUT2 with three influencing factors: awareness (EA), perceived risks (PER), anxiety (AIEA). A sample 226 students was analysed using Partial Least Squares Structural Equation Modelling technique (PLS-SEM). results further validate effectiveness UTAUT2. Furthermore, performance expectancy, hedonistic motivation, price value, social all positively BI products, except for effort expectancy. Facilitating conditions habit show no significant impact on BI, but they can determine UB. extended perspective play roles as well. AIEA PER are not key determinants BI. However, directly inhibit From mediation analysis, although do have a direct UB, it inhibits UB indirectly through AIEA. Ethical Nevertheless, also increase PER. These findings help better accept ethically products.

Language: Английский

Citations

21
Examining Faculty and Student Perceptions of Generative AI in University Courses DOI Creative Commons
Junghwan Kim, Michelle Klopfer, Jacob Grohs

et al.

Innovative Higher Education, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 24, 2025

Abstract As generative artificial intelligence (GenAI) tools such as ChatGPT become more capable and accessible, their use in educational settings is likely to grow. However, the academic community lacks a comprehensive understanding of perceptions attitudes students instructors toward these new tools. In Fall 2023 semester, we surveyed 982 76 faculty at large public university United States, focusing on topics perceived ease use, ethical concerns, impact GenAI learning, differences responses by role, gender, discipline. We found that did not differ significantly higher education, except regarding hedonic motivation, habit, interest exploring technologies. Students also used for coursework or teaching similar rates, although regular was still low across both groups. Among students, significant between males STEM majors females non-STEM majors. These findings underscore importance considering demographic disciplinary diversity when developing policies practices integrating contexts, may influence learning outcomes differently various groups students. This study contributes broader how can be leveraged education while highlighting potential areas inequality need addressed widely used.

Language: Английский

Citations

2
Impacts of Generative Artificial Intelligence in Higher Education: Research Trends and Students’ Perceptions DOI Creative Commons
Sandra Saúde, João Paulo Barros, Inês Almeida

et al.

Social Sciences, Journal Year: 2024, Volume and Issue: 13(8), P. 410 - 410

Published: Aug. 7, 2024

In this paper, the effects of rapid advancement generative artificial intelligence (Gen AI) in higher education (HE) are discussed. A mixed exploratory research approach was employed to understand these impacts, combining analysis current trends and students’ perceptions Gen AI tools academia. Through bibliometric systematic literature review, 64 publications (indexed SCOPUS Web Science databases) were examined, highlighting AI’s disruptive effect on pedagogical aspects HE. The impacts identified by compared with held computer science students two different HE institutions (HEIs) topic. An study developed based application a questionnaire group 112 students. results suggest that while can enhance academic work learning feedback, it requires appropriate support foster critical, ethical, digital literacy competencies. Students demonstrate awareness both risks benefits associated settings. concludes failing recognize effectively use impedes educational progress adequate preparation citizens workers think act an AI-mediated world.

Language: Английский

Citations

13
Unveiling Insights: A Bibliometric Analysis of Artificial Intelligence in Teaching DOI Creative Commons
Malinka Ivanova, Gabriela Grosseck, Carmen Holotescu

et al.

Informatics, Journal Year: 2024, Volume and Issue: 11(1), P. 10 - 10

Published: Feb. 25, 2024

The penetration of intelligent applications in education is rapidly increasing, posing a number questions different nature to the educational community. This paper coming analyze and outline influence artificial intelligence (AI) on teaching practice which an essential problem considering its growing utilization pervasion global scale. A bibliometric approach applied outdraw “big picture” gathered bibliographic data from scientific databases Scopus Web Science. Data relevant publications matching query “artificial teaching” over past 5 years have been researched processed through Biblioshiny R environment order establish descriptive structure production, determine impact publications, trace collaboration patterns identify key research areas emerging trends. results point out growth production lately that indicator increased interest investigated topic by researchers who mainly work collaborative teams as some them are countries institutions. identified include techniques used applications, such intelligence, machine learning, deep learning. Additionally, there focus applicable technologies like ChatGPT, learning analytics, virtual reality. also explores context application for these various settings, including teaching, higher education, active e-learning, online Based our findings, trending topics can be encapsulated terms chatbots, AI, generative emotion recognition, large language models, convolutional neural networks, decision theory. These findings offer valuable insights into current landscape interests field.

Language: Английский

Citations

10
Teacher professional development for a future with generative artificial intelligence – an integrative literature review DOI Open Access

Anabela Brandão,

Luís Pedro, Nelson Zagalo

et al.

Digital Education Review, Journal Year: 2024, Volume and Issue: 45, P. 151 - 157

Published: July 1, 2024

Artificial Intelligence (AI) has been part of every citizen's life for several years. Still, the emergence generative AI (GenAI), accessible to all, raised discussions about ethical issues they raise, particularly in education. GenAI tools generate content according user requests, but are students using these ethically and safely? Can teachers guide this use their teaching activities? This paper argues that teacher professional development (TPD) is an essential key trigger adopting emerging technologies. The will present integrative literature review discusses components TPD may empower towards safe GenAI. According review, one component should be literacy, which involves understanding AI, its capabilities limitations, potential benefits drawbacks Another hands-on activities engage teachers, peers, actively during training process. discuss advantages working with designing lesson plans implement them critically classroom.

Language: Английский

Citations

10
Academic Integrity and Artificial Intelligence in Higher Education (HE) Contexts: A Rapid Scoping Review DOI Creative Commons
Beatriz Moya Figueroa, Sarah Elaine Eaton, Helen Pethrick

et al.

Canadian Perspectives on Academic Integrity, Journal Year: 2024, Volume and Issue: 7(3)

Published: March 31, 2024

Artificial Intelligence (AI) developments challenge higher education institutions’ teaching, learning, assessment, and research practices. To contribute timely evidence-based recommendations for upholding academic integrity, we conducted a rapid scoping review focusing on what is known about integrity AI in education. We followed the Updated Reviewer Manual Scoping Reviews from Joanna Briggs Institute (JBI) Preferred Reporting Items Systematic reviews Meta-Analysis (PRISMA-ScR) reporting standards. Five databases were searched, eligibility criteria included stakeholders of any age gender engaged with context 2007 through November 2022 available English. The search retrieved 2223 records, which 14 publications mixed methods, qualitative, quantitative, randomized controlled trials, text opinion studies met inclusion criteria. results showed bounded unbounded ethical implications AI. Perspectives included: cheating; as legitimate support; an equity, diversity, lens into AI; emerging to tackle evidence sources provides guidance that can inform educational decision-making processes integration, analysis misconduct cases involving AI, exploration assistance. Likewise, this signals key questions future research, explore our discussion.

Language: Английский

Citations

8
Integrating generative artificial intelligence in K-12 education: Examining teachers’ preparedness, practices, and barriers DOI Creative Commons
Yin Hong Cheah, Jingru Lu, Juhee Kim

et al.

Computers and Education Artificial Intelligence, Journal Year: 2025, Volume and Issue: unknown, P. 100363 - 100363

Published: Jan. 1, 2025

Language: Английский

Citations

1
Mapping Tomorrow’s Teaching and Learning Spaces: A Systematic Review on GenAI in Higher Education DOI Creative Commons
Tanja Tillmanns, Alfredo Salomão Filho,

Susmita Rudra

et al.

Trends in Higher Education, Journal Year: 2025, Volume and Issue: 4(1), P. 2 - 2

Published: Jan. 8, 2025

This collective systematic literature review is part of an Erasmus+ project, “TaLAI: Teaching and Learning with AI in Higher Education”. The investigates the current state Generative Artificial Intelligence (GenAI) higher education, aiming to inform curriculum design further developments within digital education. Employing a descriptive, textual narrative synthesis approach, study analysed across four thematic areas: learning objectives, teaching activities, development, institutional support for ethical responsible GenAI use. 93 peer-reviewed articles from eight databases using keyword-based search strategy, collaborative coding process involving multiple researchers, vivo transparent documentation. findings provide overview recommendations integrating into learning, contributing development effective AI-enhanced environments reveals consensus on importance incorporating Common themes like mentorship, personalised creativity, emotional intelligence, higher-order thinking highlight persistent need align human-centred educational practices capabilities technologies.

Language: Английский

Citations

1