In search of artificial intelligence (AI) literacy in teacher education: A scoping review

Computers and Education Open, Год журнала: 2024, Номер 6, С. 100169 - 100169

Опубликована: Март 15, 2024

Artificial Intelligence (AI) literacy has recently emerged on the educational agenda raising expectations teachers' and teacher educators' professional knowledge. This scoping review examines how scientific literature conceptualises AI in relation to different forms of knowledge relevant for Teacher Education (TE). The search strategy included papers proceedings from 2000- 2023 related TE as well intersection teaching. Thirty-four were analysis. Aristotelian concepts episteme (theoretical-scientific knowledge), techne (practical-productive phronesis (professional judgement) used a lens capture implicit explicit dimensions Results indicate that is globally emerging research topic education but almost absent context TE. covers many topics draws methodological approaches. Computer science exploratory teaching approaches influence type epistemic, practical, ethical Currently, not broadly addressed or captured research. Questions ethics are predominantly matter understanding technical configurations data-driven technologies. Teacher's' practical tends translate into adoption digital resources about integration EdTech By identifying several gaps, particularly concerning knowledge, this paper adds more comprehensive can contribute well-informed laying ground future

Язык: Английский

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Generative AI for Customizable Learning Experiences

Sustainability, Год журнала: 2024, Номер 16(7), С. 3034 - 3034

Опубликована: Апрель 5, 2024

The introduction of accessible generative artificial intelligence opens promising opportunities for the implementation personalized learning methods in any educational environment. Personalized has been conceptualized a long time, but it only recently become realistic and truly achievable. In this paper, we propose an affordable sustainable approach toward personalizing materials as part complete process. We have created tool within pre-existing management system at software engineering college that automatically generates based on outcomes provided by professor particular class. were composed three distinct styles, initial one being traditional style other two variations adopting pop-culture influence, namely Batman Wednesday Addams. Each lesson, besides delivered different formats, contained generated multiple-choice questions students could use to check their progress. This paper contains instructions developing such with help large language models using OpenAI’s API analysis preliminary experiment its usage performed 20 studying European university. Participation study was optional voluntary basis. student’s quantified, questionnaires conducted: immediately after subject completion another 6 months later assess both immediate long-term effects, perceptions, preferences. results indicate found multiple variants really engaging. While predominantly utilizing variant materials, they inspiring, would recommend students, like see more classes. most popular feature quiz-style tests used understanding. Preliminary evidence suggests various versions leads increase students’ especially who not mastered topic otherwise. study’s small sample size restricts ability generalize findings, provide useful early insights lay groundwork future research AI-supported strategies.

Язык: Английский

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Feedback sources in essay writing: peer-generated or AI-generated feedback?

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

Опубликована: Апрель 11, 2024

Abstract Peer feedback is introduced as an effective learning strategy, especially in large-size classes where teachers face high workloads. However, for complex tasks such writing argumentative essay, without support peers may not provide high-quality since it requires a level of cognitive processing, critical thinking skills, and deep understanding the subject. With promising developments Artificial Intelligence (AI), particularly after emergence ChatGPT, there global argument that whether AI tools can be seen new source or tasks. The answer to this question completely clear yet are limited studies our remains constrained. In study, we used ChatGPT students’ essay compared quality ChatGPT-generated with peer feedback. participant pool consisted 74 graduate students from Dutch university. study unfolded two phases: firstly, data were collected they composed essays on one given topics; subsequently, through engaging process using source. Two coding schemes including analysis measure Then, MANOVA was employed determine any distinctions between generated by ChatGPT. Additionally, Spearman’s correlation utilized explore potential links results showed significant difference peers. While provided more descriptive information about how written, identification problem essay. overarching look at suggests complementary role process. Regarding relationship peers, found no overall relationship. These findings imply does impact both quality. implications valuable, shedding light prospective use source, like writing. We discussed delved into future research practical applications educational contexts.

Язык: Английский

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Factors Influencing University Students’ Behavioral Intention to Use Generative Artificial Intelligence: Integrating the Theory of Planned Behavior and AI Literacy

International Journal of Human-Computer Interaction, Год журнала: 2024, Номер unknown, С. 1 - 23

Опубликована: Июль 29, 2024

Generative artificial intelligence (GAI) advancements have ignited new expectations for (AI)-enabled educational transformations. Based on the theory of planned behavior (TPB), this study combines structural equation modeling and interviews to analyze influencing factors Chinese university students' GAI technology usage intention. Regarding AI literacy, cognitive literacy in ethics scored highest (M = 5.740), while awareness lowest 4.578). Students' attitudes toward significantly positively influenced their intention, with combined TPB framework explaining 59.3% variance. subjective norms perceived behavioral control, attitude mediated impact Further, provide insights management leadership regarding construction an ecosystem under application technology.

Язык: Английский

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When artificial intelligence substitutes humans in higher education: the cost of loneliness, student success, and retention

Studies in Higher Education, Год журнала: 2024, Номер 49(5), С. 883 - 897

Опубликована: Март 13, 2024

Artificial intelligence (AI) may be the new-new-norm in a post-pandemic learning environment. There is growing number of university students using AI like ChatGPT and Bard to support their academic experience. Much higher education research date has focused on integrity matters authorship; yet, there unintended consequences beyond these concerns for students. That is, people who reduce formal social interactions while tools. This study evaluates 387 relationship – with artificial large-language model-based Using structural equation modelling, finds evidence that chatbots designed information provision associated student performance, when support, psychological wellbeing, loneliness, sense belonging are considered it net negative effect achievement. tests an AI-specific form cost pose success, retention. Indeed, chatbot usage poorer outcomes, human-substitution activity occurring chooses seek from rather than human (e.g. librarian, professor, or advisor) interesting teaching policy implications. We explore implications this lens success belonging.

Язык: Английский

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The promise and challenges of generative AI in education

Behaviour and Information Technology, Год журнала: 2024, Номер unknown, С. 1 - 27

Опубликована: Сен. 2, 2024

Generative artificial intelligence (GenAI) tools, such as large language models (LLMs), generate natural and other types of content to perform a wide range tasks. This represents significant technological advancement that poses opportunities challenges educational research practice. commentary brings together contributions from nine experts working in the intersection learning technology presents critical reflections on opportunities, challenges, implications related GenAI technologies context education. In commentary, it is acknowledged GenAI's capabilities can enhance some teaching practices, design, regulation learning, automated content, feedback, assessment. Nevertheless, we also highlight its limitations, potential disruptions, ethical consequences, misuses. The identified avenues for further include development new insights into roles human play, strong continuous evidence, human-centric design technology, necessary policy, support competence mechanisms. Overall, concur with general skeptical optimism about use tools LLMs Moreover, danger hastily adopting education without deep consideration efficacy, ecosystem-level implications, ethics, pedagogical soundness practices.

Язык: Английский

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Generative AI in Education: Pedagogical, Theoretical, and Methodological Perspectives

International Journal of Technology in Education, Год журнала: 2024, Номер 7(3), С. 373 - 385

Опубликована: Май 30, 2024

Recently, ChatGPT, a cutting-edge large language model, has emerged as powerful Generative Artificial Intelligence (GenAI) tool with the capacity to influence education. ChatGPT provides ample opportunities for learners, researchers, educators, and practitioners achieve intended learning outcomes in various disciplines. This special issue examines diverse applications implications of GenAI tools including education, highlighting their potential enhance teaching across contexts. Key findings from seventeen studies collected this demonstrate that can significantly improve educational by providing personalized feedback, facilitating learning, supporting both qualitative quantitative research methodologies. The emphasize GenAI’s increase learner engagement motivation, yet also underscore need robust ethical guidelines human oversight due issues privacy, bias, accuracy. highlights challenges faces, such limitations contextual understanding its impact on critical thinking skills. In addition, it foundational framework exploring effective responsible integration, aiming enrich experiences. We conclude future should focus longitudinal effects outcomes, developing frameworks use, ensuring adaptability populations promote inclusive practices.

Язык: Английский

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A Systematic Review of Generative AI for Teaching and Learning Practice

Education Sciences, Год журнала: 2024, Номер 14(6), С. 636 - 636

Опубликована: Июнь 13, 2024

The use of generative artificial intelligence (GenAI) in academia is a subjective and hotly debated topic. Currently, there are no agreed guidelines towards the usage GenAI systems higher education (HE) and, thus, it still unclear how to make effective technology for teaching learning practice. This paper provides an overview current state research on HE. To this end, study conducted systematic review relevant studies indexed by Scopus, using preferred reporting items reviews meta-analyses (PRISMA) guidelines. search criteria revealed total 625 papers, which 355 met final inclusion criteria. findings from showed future trends documents, citations, document sources/authors, keywords, co-authorship. gaps identified suggest that while some authors have looked at understanding detection AI-generated text, may be beneficial understand can incorporated into supporting educational curriculum assessments, teaching, delivery. Furthermore, need additional interdisciplinary, multidimensional HE through collaboration. will strengthen awareness students, tutors, other stakeholders, instrumental formulating guidelines, frameworks, policies usage.

Язык: Английский

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Developing a holistic AI literacy assessment matrix – Bridging generic, domain-specific, and ethical competencies

Computers and Education Open, Год журнала: 2024, Номер 6, С. 100177 - 100177

Опубликована: Апрель 10, 2024

Motivated by a holistic understanding of AI literacy, this work presents an interdisciplinary effort to make literacy measurable in comprehensive way, considering generic and domain-specific as well ethics. While many assessment tools have been developed the last 2-3 years, mostly form self-assessment scales less frequently knowledge-based assessments, previous approaches only accounted for one specific area competence, namely cognitive aspects within literacy. Considering demand development different professional domains reflecting on concept competence way that goes beyond mere conceptual knowledge, there is urgent need methods capture each three dimensions cognition, behavior, attitude. In addition, competencies ethics are becoming more apparent, which further calls very matter. This paper aims provide foundation upon future instruments can be built provides insights into what framework item might look like addresses both measures than just knowledge-related based approach.

Язык: Английский

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Generative AI in education and research: A systematic mapping review

Review of Education, Год журнала: 2024, Номер 12(2)

Опубликована: Авг. 1, 2024

Abstract Given the potential applications of generative AI (GenAI) in education and its rising interest research, this systematic review mapped thematic landscape 407 publications indexed Web Science, ScienceDirect Scopus. Using EPPI Reviewer, publication type, educational level, disciplines, research areas GenAI were extracted. Eight discursive themes identified, predominantly focused on ‘application, impact potential’, ‘ethical implication risks’, ‘perspectives experiences’, ‘institutional individual adoption’, ‘performance intelligence’. was conceptualised as a tool for ‘pedagogical enhancement’, ‘specialised training practices’, ‘writing assistance productivity’, ‘professional skills development’, an ‘interdisciplinary learning tool’. Key gaps highlighted include paucity discussions K‐12 education; limited exploration GenAI's using experimental procedures; ethical concerns from lens cultural dimensions. Promising opportunities future are highlighted.

Язык: Английский

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