Embracing the future of Artificial Intelligence in the classroom: the relevance of AI literacy, prompt engineering, and critical thinking in modern education

International Journal of Educational Technology in Higher Education, Journal Year: 2024, Volume and Issue: 21(1)

Published: Feb. 26, 2024

Abstract The present discussion examines the transformative impact of Artificial Intelligence (AI) in educational settings, focusing on necessity for AI literacy, prompt engineering proficiency, and enhanced critical thinking skills. introduction into education marks a significant departure from conventional teaching methods, offering personalized learning support diverse requirements, including students with special needs. However, this integration presents challenges, need comprehensive educator training curriculum adaptation to align societal structures. literacy is identified as crucial, encompassing an understanding technologies their broader impacts. Prompt highlighted key skill eliciting specific responses systems, thereby enriching experiences promoting thinking. There detailed analysis strategies embedding these skills within curricula pedagogical practices. This discussed through case-study based Swiss university narrative literature review, followed by practical suggestions how implement classroom.

Language: Английский

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Drivers of generative AI adoption in higher education through the lens of the Theory of Planned Behaviour

Technology in Society, Journal Year: 2024, Volume and Issue: 77, P. 102521 - 102521

Published: March 25, 2024

Drawing on the Theory of Planned Behaviour (TPB), this study investigates relationship between perceived benefits, strengths, weaknesses, and risks generative AI (GenAI) tools fundamental factors TPB model (i.e., attitude, subjective norms, behavioural control). The also structural association variables intention to use GenAI tools, how latter might affect actual usage in higher education. paper adopts a quantitative approach, relying an anonymous self-administered online questionnaire gather primary data from 130 lecturers 168 students education institutions (HEIs) several countries, PLS-SEM for analysis. results indicate that although lecturers' students' perceptions weaknesses differ, strengths advantages technologies have significant positive impact their attitudes, control. core positively significantly intentions which turn adoption such tools. This advances theory by outlining shaping HEIs. It provides stakeholders with variety managerial policy implications formulate suitable rules regulations utilise these while mitigating impacts disadvantages. Limitations future research opportunities are outlined.

Language: Английский

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Will artificial intelligence drive the advancements in higher education? A tri-phased exploration

Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 201, P. 123258 - 123258

Published: Feb. 9, 2024

Language: 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, Journal Year: 2024, Volume and Issue: 49(5), P. 883 - 897

Published: March 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.

Language: Английский

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Artificial Intelligence and the Transformation of Higher Education Institutions: A Systems Approach

Sustainability, Journal Year: 2024, Volume and Issue: 16(14), P. 6118 - 6118

Published: July 17, 2024

Artificial intelligence (AI) advances and the rapid adoption of generative AI tools, like ChatGPT, present new opportunities challenges for higher education. While substantial literature discusses in education, there is a lack systems approach that captures holistic view structure dynamics transformation education institutions (HEIs). To fill this gap, article develops causal loop diagram (CLD) to map feedback mechanisms typical HEI. We identify important variables their relationships multiple reinforcing balancing loops accounting forces drive its impact on value creation The model shows how, motivated by technology advances, HEI can invest improve student learning, research, administration while dealing with academic integrity problems adapting job market changes emphasizing AI-complementary skills. explore insights, scenarios, policy interventions recommend leaders become thinkers manage complexity benefit from avoiding traps may lead decline. also discuss notion HEIs influencing direction directions future research sustainability HEIs.

Language: Английский

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Artificial Intelligence in Higher Education: The Impact of Need Satisfaction on Artificial Intelligence Literacy Mediated by Self-Regulated Learning Strategies

Behavioral Sciences, Journal Year: 2025, Volume and Issue: 15(2), P. 165 - 165

Published: Feb. 2, 2025

Artificial intelligence (AI) technologies have profoundly influenced both professional environments and personal lives. In the rapidly developing sector of AI education, fostering essential literacy among university students has become vital. Nevertheless, factors that determine remain insufficiently defined. This research, grounded in self-determination theory (SDT), seeks to investigate relationships three components: fulfillment students’ psychological needs, self-regulated learning strategies (SRLSs), literacy. The aim is enhance human capital efficiency prepare tackle future workplace challenges effectively. To examine these connections, a cross-sectional survey was administered 1056 students. findings reveal satisfying needs—perceived autonomy, competence, relatedness—plays pivotal role advancing Additionally, four SRLSs—cognitive engagement, metacognitive knowledge, resource management, motivational beliefs—acted as mediators between needs Consequently, this study not only enhances our understanding behavioral development during their engagement with education but also provides theoretical support practical guidance for

Language: Английский

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AI and ethics: Investigating the first policy responses of higher education institutions to the challenge of generative AI

Humanities and Social Sciences Communications, Journal Year: 2024, Volume and Issue: 11(1)

Published: Aug. 6, 2024

Abstract This article addresses the ethical challenges posed by generative artificial intelligence (AI) tools in higher education and explores first responses of universities to these globally. Drawing on five key international documents from UN, EU, OECD, study used content analysis identify dimensions related use AI academia, such as accountability, human oversight, transparency, or inclusiveness. Empirical evidence was compiled 30 leading ranked among top 500 Shanghai Ranking list May July 2023, covering those institutions that already had publicly available form policy guidelines. The paper identifies central imperative student assignments must reflect individual knowledge acquired during their education, with individuals retaining moral legal responsibility for AI-related wrongdoings. top-down requirement aligns a bottom-up approach, allowing instructors flexibility determining how they utilize especially large language models own courses. Regarding typical response identified involves blend preventive measures (e.g., course assessment modifications) soft, dialogue-based sanctioning procedures. challenge transparency induced good practice clear communication syllabi university examined this study.

Language: Английский

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Mapping Tomorrow’s Teaching and Learning Spaces: A Systematic Review on GenAI in Higher Education

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

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Cultivating independent thinkers: The triad of artificial intelligence, Bloom’s taxonomy and critical thinking in assessment pedagogy

Education and Information Technologies, Journal Year: 2025, Volume and Issue: unknown

Published: March 12, 2025

Language: Английский

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Generative AI and the future of connectivist learning in higher education

Journal of Asian Public Policy, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 23

Published: Aug. 27, 2024

The burgeoning field of Generative Artificial Intelligence (GenAI) presents a new avenue for enhancing teaching and learning practices within higher education. While existing research has predominantly focused on GenAI's capabilities to perform specific educational tasks, its potential as an interactive agent engaging in human-like conversations forming connections remains underexplored. Drawing upon connectivist lens that recognizes occurs networks interactions, we investigate how GenAI tools can contribute social entrepreneurship Through qualitative interviews with multiple key stakeholder groups, this study reveals three dimensions dialogic spaces be enabled by GenAI: collaborative learning, knowledge connectivity, theory-practice integration. This makes several contributions. First, it expands current discussions AI education, moving beyond tool-based acceptance actively exploring active agent. Second, contributes the literature demonstrating not only interaction facilitators but also agents create interactions across different levels. Finally, offers practical insights bridging voices perspectives stakeholders envision future where coexists traditional agents.

Language: Английский

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