Prompt Aloud!: Incorporating image-generative AI into STEAM class with learning analytics using prompt data

Lee, Unggi; Han, Ariel; Lee, Jeongjin; Lee, Eunseo; Kim, Jiwon; Kim, Hyeoncheol; Lim, Cheolil

doi:10.1007/s10639-023-12150-4

Cited by 8 publications

(1 citation statement)

References 54 publications

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“…Unlike AI which is tasked with automating repetitive tasks (Isusqui, Villavicencio, Inga, Gutiérrez, Díaz & Amaya, 2023), Generative Artificial Intelligence (AI-Gen) refers to AI systems that generate new datasets such as text, images, audio, video, music or software code (Fengchun & Wayne, 2023) with the objective of producing innovative and creative results based on training data (Mannuru, Shahriar, Teel, Wang, Lund, Tijani et al, 2023). These systems have garnered significant attention in society (Lee, Han, Lee, Lee, Kim, Kim et al, 2023) and have the potential to bring about the greatest evolution in education (Quy, Thanh, Chehri, Linh & Tuan, 2023). Such tools do not have any conceptual knowledge or conscious understanding, asthese only use word transitions and are based on mathematical probabilities of data and word classification (Cress & Kimmerle, 2023).…”

Section: Generative Artificial Intelligence In Educationmentioning

confidence: 99%

Generative artificial intelligence: Educational reflections from an analysis of scientific production

Dúo Terrón

2024

J. Technol. Sci. Educ.

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Generative Artificial Intelligence (AI-Gen) in education is a challenge for educational administrations due to the benefits and risks of its use. This research seeks to analyse the scientific production of AI-Gen in the educational field. The method used was a bibliometric analysis of descriptive and quantitative documents from the Web of Science database. The VOSviewer statistical programme was used to identify the keyword clusters and to create the network map. The results of this study ascertain that 2023 is the birth of AI-Gen research in education and has since produced a total of 178 papers, where Australia heads the ranking of countries with studies on this subject matter. The ChatGPT phenomenon materialises as a focus of study in the majority of cited research. The study includes seven keyword clusters, where the IA-Gen cluster which is related to terms such as challenges, risks and opportunities are highlighted. Following the discussion, the main conclusion of the study denotes that further research is required on the use of AI-Gen during the teaching-learning process in several educational stages to prevent plagiarism and to obtain a comprehensive understanding of this technology as an educational resource.

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Section: Generative Artificial Intelligence In Educationmentioning

confidence: 99%

Generative artificial intelligence: Educational reflections from an analysis of scientific production

Dúo Terrón

2024

J. Technol. Sci. Educ.

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VizChat: Enhancing Learning Analytics Dashboards with Contextualised Explanations Using Multimodal Generative AI Chatbots

Yan,

Zhao,

Echeverria

et al. 2024

Lecture Notes in Computer Science

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Poietic symbiosis or algorithmic subjugation: generative AI technology in marketing communications education

Karimova,

Kim,

Shirkhanbeik

2024

Educ Inf Technol

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This exploratory study investigates the convergence of marketing communications and AI-powered technology in higher education, adopting a perspective on student interactions with generative AI tools. Through a comprehensive content analysis of learners’ responses, we employed a blend of manual scrutiny, Python-generated Word Cloud, and Latent Dirichlet Allocation (LDA) to expose the nature of interaction between learners and AI tools. Our findings indicate that learners predominantly adhere to the perception of AI as a tool resembling a ‘brush’ in the creative process, rather than as an active co-creator – the percaption that is aligned with the conventional tool-user dynamic. Students articulated a dual narrative regarding AI: they acknowledged its utility in enhancing creativity, yet expressed concerns about overreliance potentially eroding their own creative skills. Heidegger’s exploration of different modes of ‘revealing’ and Deleuze and Guattari’s notions of desiring machines and machinic enslavement suggest an alternative perspective where technology, and by extension AI-empowered technology, can contribute to a deeper existential understanding. This study points out the possibility of moving beyond a simple tool-user model, suggesting the emergence of more complex plausible scenarios of interaction: poietic symbiosis or algorithmic subjugation.

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Prompt Aloud!: Incorporating image-generative AI into STEAM class with learning analytics using prompt data

Cited by 8 publications

References 54 publications

Generative artificial intelligence: Educational reflections from an analysis of scientific production

Generative artificial intelligence: Educational reflections from an analysis of scientific production

VizChat: Enhancing Learning Analytics Dashboards with Contextualised Explanations Using Multimodal Generative AI Chatbots

Poietic symbiosis or algorithmic subjugation: generative AI technology in marketing communications education

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