ChatGPT: Bullshit spewer or the end of traditional assessments in higher education?

Journal of Applied Learning & Teaching, Journal Year: 2023, Volume and Issue: 6(1)

Published: Jan. 25, 2023

ChatGPT is the world’s most advanced chatbot thus far. Unlike other chatbots, it can create impressive prose within seconds, and has created much hype doomsday predictions when comes to student assessment in higher education a host of matters. state-of-the-art language model (a variant OpenAI’s Generative Pretrained Transformer (GPT) model) designed generate text that be indistinguishable from written by humans. It engage conversation with users seemingly natural intuitive way. In this article, we briefly tell story OpenAI, organisation behind ChatGPT. We highlight fundamental change not-for-profit commercial business model. terms our methods, conducted an extensive literature review experimented artificial intelligence (AI) software. Our shows amongst first peer-reviewed academic journal articles explore its relevance for (especially assessment, learning teaching). After description ChatGPT’s functionality summary strengths limitations, focus on technology’s implications discuss what future learning, teaching context AI chatbots such as position current Artificial Intelligence Education (AIEd) research, student-facing, teacher-facing system-facing applications, analyse opportunities threats. conclude article recommendations students, teachers institutions. Many them assessment.

Language: Английский

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A Review of Artificial Intelligence (AI) in Education from 2010 to 2020

Complexity, Journal Year: 2021, Volume and Issue: 2021(1)

Published: Jan. 1, 2021

This study provided a content analysis of studies aiming to disclose how artificial intelligence (AI) has been applied the education sector and explore potential research trends challenges AI in education. A total 100 papers including 63 empirical (74 studies) 37 analytic were selected from educational category Social Sciences Citation Index database 2010 2020. The showed that questions could be classified into development layer (classification, matching, recommendation, deep learning), application (feedback, reasoning, adaptive integration (affection computing, role‐playing, immersive learning, gamification). Moreover, four trends, Internet Things, swarm intelligence, neuroscience, as well an assessment education, suggested for further investigation. However, we also proposed may caused by with regard inappropriate use techniques, changing roles teachers students, social ethical issues. results provide insights overview used domain, which helps strengthen theoretical foundation provides promising channel educators engineers carry out collaborative research.

Language: Английский

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State of the art and practice in AI in education

European Journal of Education, Journal Year: 2022, Volume and Issue: 57(4), P. 542 - 570

Published: Oct. 30, 2022

Abstract Recent developments in Artificial Intelligence (AI) have generated great expectations for the future impact of AI education and learning (AIED). Often these been based on misunderstanding current technical possibilities, lack knowledge about state‐of‐the‐art education, exceedingly narrow views functions society. In this article, we provide a review existing systems their pedagogic educational assumptions. We develop typology AIED describe different ways using learning, show how are grounded interpretations what is or could be, discuss some potential roadblocks highway.

Language: Английский

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AI literacy in K-12: a systematic literature review

International Journal of STEM Education, Journal Year: 2023, Volume and Issue: 10(1)

Published: April 19, 2023

Abstract The successful irruption of AI-based technology in our daily lives has led to a growing educational, social, and political interest training citizens AI. Education systems now need train students at the K-12 level live society where they must interact with Thus, AI literacy is pedagogical cognitive challenge level. This study aimed understand how being integrated into education worldwide. We conducted search process following systematic literature review method using Scopus. 179 documents were reviewed, two broad groups approaches identified, namely learning experience theoretical perspective. first group covered experiences technical, conceptual applied skills particular domain interest. second revealed that significant efforts are made design models frame proposals. There hardly any assessed whether understood concepts after experience. Little attention been paid undesirable consequences an indiscriminate insufficiently thought-out application A competency framework required guide didactic proposals designed by educational institutions define curriculum reflecting sequence academic continuity, which should be modular, personalized adjusted conditions schools. Finally, can leveraged enhance disciplinary core subjects integrating teaching those subjects, provided co-designed teachers.

Language: Английский

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Power to the Teachers: An Exploratory Review on Artificial Intelligence in Education

Information, Journal Year: 2021, Volume and Issue: 13(1), P. 14 - 14

Published: Dec. 29, 2021

This exploratory review attempted to gather evidence from the literature by shedding light on emerging phenomenon of conceptualising impact artificial intelligence in education. The utilised PRISMA framework analysis and synthesis process encompassing search, screening, coding, data strategy 141 items included corpus. Key findings extracted incorporate a taxonomy applications with associated teaching learning practice for helping teachers develop self-reflect skills capabilities envisioned employing Implications ethical use set propositions enacting using are demarcated. this contribute developing better understanding how may enhance teachers’ roles as catalysts designing, visualising, orchestrating AI-enabled learning, will, turn, help proliferate AI-systems that render computational representations based meaningful data-driven inferences pedagogy, domain, learner models.

Language: Английский

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Empowering educators to be AI-ready

Computers and Education Artificial Intelligence, Journal Year: 2022, Volume and Issue: 3, P. 100076 - 100076

Published: Jan. 1, 2022

In this paper, we present the concept of AI Readiness, along with a framework for developing Readiness training. 'AI Readiness' can be framed as contextualised way helping people to understand AI, in particular, data-driven AI. The nature training is not same merely learning about Rather, recognises diversity professions, workplaces and sectors whom has potential impact. For example, lawyers may based on principles Educators. However, details will differently. that such contextualisation an option: it essential due multiple intricacies, sensitivities variations between different their settings, which all impact application To embrace contextualisation, needs active, participatory process aims empower more able leverage meet needs. text follows focuses within Education Training sector starts discussion current state education training, need Readiness. We then problematize why needed, what means. expand upon through difference human Artificial Intelligence, before presenting 7-step become Ready. Finally, use example action Higher exemplify

Language: Английский

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Advantages and Constraints of a Hybrid Model K-12 E-Learning Assistant Chatbot

IEEE Access, Journal Year: 2020, Volume and Issue: 8, P. 77788 - 77801

Published: Jan. 1, 2020

E-Learning has become more and popular in recent years with the advance of new technologies. Using their mobile devices, people can expand knowledge anytime anywhere. also makes it possible for to manage learning progression freely follow own style. However, studies show that cause user experience feelings isolation detachment due lack human-like interactions most platforms. These could reduce user's motivation learn. In this paper, we explore evaluate how well current chatbot technologies assist users' on platforms these possibly problems such as detachment. For evaluation, specifically designed a be an assistant. The NLP core our is based two different models: retrieval-based model QANet model. We two-model hybrid used alongside platform. response context not only course materials mind but everyday conversation chitchat, which make feel like human companion. Experiment questionnaire evaluation results chatbots helpful potentially Our performed better than teacher counselling service platform based.

Language: Английский

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Artificial intelligence in education

Published: Jan. 1, 2023

The article is an excerpt from Wayne Holmes/ Maya Bialik/ Charles Fadel, Artificial Intelligence in Education : Promises and Implications for Teaching Learning, Center Curriculum Redesign, Boston, 2019, 151-180 (ISBN-13: 978-1-794-29370-0). With permission of the publisher. Abstract available from: https://discovery.ucl.ac.uk/id/eprint/10139722/).

Language: Английский

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Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions

Information Fusion, Journal Year: 2024, Volume and Issue: 106, P. 102301 - 102301

Published: Feb. 15, 2024

Understanding black box models has become paramount as systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications. In response, Explainable AI (XAI) emerged a field of research with practical and ethical benefits across various domains. This paper highlights the advancements XAI its application scenarios addresses ongoing challenges within XAI, emphasizing need for broader perspectives collaborative efforts. We bring together experts from fields identify open problems, striving synchronize agendas accelerate By fostering discussion interdisciplinary cooperation, we aim propel forward, contributing continued success. develop comprehensive proposal advancing XAI. To achieve this goal, present manifesto 28 problems categorized into nine categories. These encapsulate complexities nuances offer road map future research. For each problem, provide promising directions hope harnessing collective intelligence interested stakeholders.

Language: Английский

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Influence of Pedagogical Beliefs and Perceived Trust on Teachers’ Acceptance of Educational Artificial Intelligence Tools

International Journal of Human-Computer Interaction, Journal Year: 2022, Volume and Issue: 39(4), P. 910 - 922

Published: April 19, 2022

Advancements in artificial intelligence (AI) have stimulated the development of educational AI tools (EAIT). EAITs intelligently assist teachers formulating better pedagogical decisions or actions for their students. However, are hardly integrating EAITs, and little is known about perceptions EAITs. This study seeks to identify human factors that encourage restrict teachers' acceptance We propose a revised technology model incorporating beliefs perceived trust Survey data were collected from 215 South Korea analyzed using structural equation modeling. The results indicate with constructivist more likely integrate than transmissive orientations. Furthermore, usefulness, ease use, determinants be considered when explaining Among them, most influential determinant predicting was found how easily EAIT constructed. Significant implications researchers stakeholders regarding integration discussed.

Language: Английский

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