Where is the reflexive ‘I’ in the Elements of AI? DOI Creative Commons
Hany Hachem, Fredrik Heintz

International Journal of Lifelong Education, Год журнала: 2024, Номер 43(6), С. 664 - 681

Опубликована: Авг. 11, 2024

AI's opportunities and potential high-risk consequences for individuals societies render mass AI literacy imperative. MOOCs are one effective conduit its provision. However, remain epistemologically one-sided when lifelong learning steadily shifts towards a reflexive epistemology whereby subjectivities expert knowledge intersect, problematising the latter's relevance to agents disregarding first. Addressing underexplored epistemologies of kindled by transformative in late modernity, this paper examines how design MOOC Elements prompts reflexivity over AI. A Bloom's taxonomy-based qualitative content analysis categorised 16 objectives 25 assessments according cognitive processes dimensions they serve. Results showed adequate but delayed instruction benign constructive misalignment, with assessment hitting higher wider than objectives. Following fleshing out results, their discussion leads EAI-specific general enhancements identity-based catering scale individuality.

Язык: Английский

Integrating Artificial Intelligence (AI) Into Adult Education DOI Creative Commons
Valerie A. Storey,

Amiee Wagner

International Journal of Adult Education and Technology, Год журнала: 2024, Номер 15(1), С. 1 - 15

Опубликована: Май 7, 2024

This conceptual article provides a comprehensive overview of the current status Artificial Intelligence (AI) integration and its influence on adult education. It discusses generative AI technologies their potential applications in education settings, examines opportunities ethical challenges associated with integrating AI, insights into emerging trends. The consists five sections. introduction rationale as to why should be integrated Second, it describes evolving such Large Language Models (LLM) for personalized learning, Machine Learning Algorithms adaptive learning systems, Virtual Reality (VR) Augmented (AR) immersive experiences, Chatbots virtual assistants learner support guidance, Data Analytics (DLA) tracking progress performance Section three explores implications education, including academic honesty integrity, data privacy, algorithmic bias. In section four, trends future directions are discussed. final considers policy makes recommendations educators working develop AI-enriched

Язык: Английский

Процитировано

7

The effectiveness of ChatGPT in assisting high school students in programming learning: evidence from a quasi-experimental research DOI Creative Commons
Tzu‐Chi Yang, Yung‐Chin Hsu, Jiun‐Yu Wu

и другие.

Interactive Learning Environments, Год журнала: 2025, Номер unknown, С. 1 - 18

Опубликована: Янв. 16, 2025

Programming education gains importance in high schools as the digital age progresses. However, openness and adaptability of programming languages present unique challenges for instructional practices compared to other subjects. While traditional tools offer limited support, ChatGPT, a groundbreaking Generative Artificial Intelligence, has shown impressive capabilities natural language processing knowledge generation. This study explored whether ChatGPT can transcend existing limitations improve through quasi-experimental approach with post-hoc interviews school classrooms. A total 153 students participated, results from MANCOVA ANCOVA analyses revealed that using reported lower levels flow experience, self-efficacy, learning achievement those utilizing conventional methods. Post-hoc further felt ChatGPT's effectiveness facilitating their fell short initial expectations. These findings highlight need carefully consider complexity tasks students' cognitive, affective, interactive dimensions when integrating AI technologies into education. We discuss implications provide thorough pedagogical strategies, specifically guidance–practice–transformation (G–P–T) mode, maximize potential support education, emphasizing balance technological innovation best practices.

Язык: Английский

Процитировано

0

Andragogy as a Theoretical Framework for AI Integration in Higher Education DOI
Ashley L. Dockens, Kaye Shelton

Advances in educational technologies and instructional design book series, Год журнала: 2025, Номер unknown, С. 71 - 108

Опубликована: Янв. 17, 2025

This chapter examines the integration of artificial intelligence (AI) and andragogy in higher education, focusing on how adult learning principles can guide ethical use AI technologies. It provides an overview andragogical principles, discusses AI's impact learning, presents strategies for aligning with approaches. Key areas include enhancing self-directed supporting experiential problem-centered fostering critical thinking AI. The explores practical implementation strategies, educator training, considerations such as data privacy algorithmic bias. also emerging technologies their potential andragogy, identifies further research, preparing education AI-enhanced future. Throughout, importance balancing technological innovation sound practices is emphasized, providing insights educators, administrators, policymakers education.

Язык: Английский

Процитировано

0

Technological Frontiers in Education: Exploring the Impact of AI and Immersive Learning DOI

Petra Mueller-Csernetzky,

Elena Malakhatka, Liane Thuvander

и другие.

Springer series in adaptive environments, Год журнала: 2025, Номер unknown, С. 291 - 328

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

The Impact of Generative AI on Education DOI

Nisserine El Bahri,

Zakaria Itahriouan, Anouar Abtoy

и другие.

Advances in educational technologies and instructional design book series, Год журнала: 2025, Номер unknown, С. 29 - 64

Опубликована: Фев. 14, 2025

Education is utilizing generative artificial intelligence more and more, especially with models like GPT, BERT, other neural networks. Through the automatic generation of information, individualized learning resources, responses to student inquiries, these technologies are transforming traditional teaching methods, course design, interactions learners. Despite fact that tools have potential drastically change nature education, it crucial comprehend their existing uses, advantages, drawbacks. The purpose this chapter present a thorough analysis current scholarly research on application AI in education across all academic levels.

Язык: Английский

Процитировано

0

Generative AI Capability Maturity Model for Online and Adult Learning: Introducing the EMERALD-GenAI-CMM-OAL Framework DOI
Valeri Chukhlomin

SSRN Electronic Journal, Год журнала: 2024, Номер unknown

Опубликована: Янв. 1, 2024

Download This Paper Open PDF in Browser Add to My Library Share: Permalink Using these links will ensure access this page indefinitely Copy URL DOI

Язык: Английский

Процитировано

3

Intelligent Tutors for Adult Learning at Scale: A Narrative Review DOI

Utkarsh Nattamai Subramanian Rajkumar,

Sibley F. Lyndgaard, Ruth Kanfer

и другие.

Опубликована: Июль 9, 2024

Intelligent tutors and tutoring systems (ITS) are increasingly common in educational contexts. These tools have considerable potential for scaling highly effective 1:1 learner-instructor interactions. To date, most studies investigating ITS implementation engaged non-adult (i.e., child, adolescent, or traditional college student) populations, however, their adult learning is recognized. We performed a selected, narrative review of ITS, asked two guiding questions: (1) What the primary domains which has been deployed to promote lifespan learning? (2) How specifically within each domain? Fifteen papers were three themes emerged: Adult literacy, post-secondary/professional education, (3) lifelong career-related development. Exemplar from theme selected presented/discussed more detail. The results discussed terms current state literature on learning, how such can improve access personalized support at scale. Limitations future directions discussed.

Язык: Английский

Процитировано

0

Determinants of cognitive skills in adulthood: Age cohort patterns DOI Creative Commons
Débora B. Maehler,

Silke Martin,

Julia Gorges

и другие.

International Journal of Lifelong Education, Год журнала: 2024, Номер unknown, С. 1 - 22

Опубликована: Авг. 16, 2024

The current study examines change and stability of cognitive skills across life stages delves into the factors contributing to changes in skills. Specifically, we examine associations between individual characteristics contextual a large sample German adults aged 16–65 years (N = 2,430; PIAAC-L data). Across all age cohorts, were predicted mainly by person's educational background, but they also associated with related socialisation, lifestyle personality. findings indicate that specific influence at different stages. For example, personality was solely two younger whereas impacts most pronounced middle cohort.

Язык: Английский

Процитировано

0

Linear regression model to predict the use of artificial intelligence in experimental science students DOI
Elizeth Mayrene Flores Hinostroza, Derling José Mendoza Velazco, Mercedes Navarro Cejas

и другие.

International Electronic Journal of Mathematics Education, Год журнала: 2024, Номер 20(1), С. em0807 - em0807

Опубликована: Дек. 20, 2024

This study builds on the increasing relevance of technology integration in higher education, specifically artificial intelligence (AI) usage educational contexts. Background research highlights limited exploration AI training programs, particularly within Latin America. has become increasingly pivotal practices, influencing development competencies various disciplines, including experimental sciences. aimed to describe correlation between professional AI, usage, and digital resources among students sciences education program at National University Chimborazo. Methodologically, a quantitative approach was employed, involving structured survey distributed 459 students. Data analysis conducted using multiple regression models establish predictive insights into usage. A linear model developed predict these The revealed significant correlations competencies, resources. highlighted that both are predictors These findings underscore importance developing providing access enhance effective use practices. Limitations future directions discussed.

Язык: Английский

Процитировано

0

Where is the reflexive ‘I’ in the Elements of AI? DOI Creative Commons
Hany Hachem, Fredrik Heintz

International Journal of Lifelong Education, Год журнала: 2024, Номер 43(6), С. 664 - 681

Опубликована: Авг. 11, 2024

AI's opportunities and potential high-risk consequences for individuals societies render mass AI literacy imperative. MOOCs are one effective conduit its provision. However, remain epistemologically one-sided when lifelong learning steadily shifts towards a reflexive epistemology whereby subjectivities expert knowledge intersect, problematising the latter's relevance to agents disregarding first. Addressing underexplored epistemologies of kindled by transformative in late modernity, this paper examines how design MOOC Elements prompts reflexivity over AI. A Bloom's taxonomy-based qualitative content analysis categorised 16 objectives 25 assessments according cognitive processes dimensions they serve. Results showed adequate but delayed instruction benign constructive misalignment, with assessment hitting higher wider than objectives. Following fleshing out results, their discussion leads EAI-specific general enhancements identity-based catering scale individuality.

Язык: Английский

Процитировано

0