A perspective on the synergistic potential of artificial intelligence and product-based learning strategies in biobased materials education

Márquez, Ronald; Barrios, Nelson; Vera, Ramon E.; Mendez, Maria E.; Tolosa, Laura; Zambrano, Franklin; Li, Yali

doi:10.1016/j.ece.2023.05.005

Cited by 16 publications

(8 citation statements)

References 120 publications

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“…Regarding the learning theories theme, a similar tendency to discuss or investigate the implications of ChatGPT for the existing theories of learning, and elaborate on the need to design newer, AI-friendly or AI-supported techniques of instruction. One such study was conducted by Marquez et al (2023) to enable the effective use of ChatGPT in chemistry laboratory classes. These researchers proposed new learning theories to achieve the transition of a traditional lab class into an AI-enhanced one, particularly predicating on cognitivism and constructivism.…”

Section: Discussionmentioning

confidence: 99%

Assessing the Intellectual Structure of the Evolving Knowledge Base on ChatGPT in the Field of Education and Health

Demirkol,

Malkoç

2023

EDUPIJ

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Background/purpose -The unprecedented developments in AI-based technologies and large language models such as ChatGPT have exhibited a brand-new territory to be explored. Since its first release in November 2022, the potential utility of ChatGPT has garnered incremental attention in the scientific world, and has already accumulated a great number of studies from diverse fields. The current study was conducted with the purpose of exploring the scientific landscape of the evolving knowledge base related to the use of ChatGPT in the field of education and health through science mapping analysis of published research. Materials/methods -Data were retrieved from Web of Science and Scopus, and a comparative, period-based science mapping analysis was conducted using the SciMAT software. Results -The results showed that the studies published during the first period mostly focused on machine learning, reproductive medicine, education and first-year undergraduate themes. During the second period, though, the studies featured themes that are closely related to the design and performance of ChatGPT such as large language models (LLMs), natural language processing (NLP) and chatbot while abandoning a focus on artificial intelligence. These results imply that discussions and investigations over ChatGPT were being departed from those in the field of artificial intelligence, and the focus was becoming more central to the features of ChatGPT as a language model that can process huge amounts of information to generate human-like texts. Plagiarism and research ethics were also emerging themes during the last period. Conclusion -The results of the science mapping showed a growing interest into the opportunities and risks of ChatGPT, particularly for fields of education and medicine, and indicated that much research is warranted to discover the potential of GPT technology as an uncharted territory.

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Section: Discussionmentioning

confidence: 99%

Assessing the Intellectual Structure of the Evolving Knowledge Base on ChatGPT in the Field of Education and Health

Demirkol,

Malkoç

2023

EDUPIJ

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“…A perspective on the synergistic potential of artificial intelligence and product-based learning strategies in biobased materials education [27] 111…”

Section: Title Codementioning

confidence: 99%

Large Language Models (LLMs) in Engineering Education: A Systematic Review and Suggestions for Practical Adoption

Filippi,

Motyl

2024

Information

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The use of large language models (LLMs) is now spreading in several areas of research and development. This work is concerned with systematically reviewing LLMs’ involvement in engineering education. Starting from a general research question, two queries were used to select 370 papers from the literature. Filtering them through several inclusion/exclusion criteria led to the selection of 20 papers. These were investigated based on eight dimensions to identify areas of engineering disciplines that involve LLMs, where they are most present, how this involvement takes place, and which LLM-based tools are used, if any. Addressing these key issues allowed three more specific research questions to be answered, offering a clear overview of the current involvement of LLMs in engineering education. The research outcomes provide insights into the potential and challenges of LLMs in transforming engineering education, contributing to its responsible and effective future implementation. This review’s outcomes could help address the best ways to involve LLMs in engineering education activities and measure their effectiveness as time progresses. For this reason, this study addresses suggestions on how to improve activities in engineering education. The systematic review on which this research is based conforms to the rules of the current literature regarding inclusion/exclusion criteria and quality assessments in order to make the results as objective as possible and easily replicable.

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“…Transformative role of AI in education and learning Marquez et al (2023) [27] Emphasizes the potential of integrating product-based learning strategies and AI text generation models in biobased materials education, showcasing how this approach promotes active participation, problem-solving skills, and the generation of sustainable solutions.…”

Section: Themes Authors Focusmentioning

confidence: 99%

Transforming Education: A Comprehensive Review of Generative Artificial Intelligence in Educational Settings through Bibliometric and Content Analysis

Bahroun,

Anane,

Ahmed

et al. 2023

Sustainability

177

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In the ever-evolving era of technological advancements, generative artificial intelligence (GAI) emerges as a transformative force, revolutionizing education. This review paper, guided by the PRISMA framework, presents a comprehensive analysis of GAI in education, synthesizing key insights from a selection of 207 research papers to identify research gaps and future directions in the field. This study begins with a content analysis that explores GAI’s transformative impact in specific educational domains, including medical education and engineering education. The versatile applications of GAI encompass assessment, personalized learning support, and intelligent tutoring systems. Ethical considerations, interdisciplinary collaboration, and responsible technology use are highlighted, emphasizing the need for transparent GAI models and addressing biases. Subsequently, a bibliometric analysis of GAI in education is conducted, examining prominent AI tools, research focus, geographic distribution, and interdisciplinary collaboration. ChatGPT emerges as a dominant GAI tool, and the analysis reveals significant and exponential growth in GAI research in 2023. Moreover, this paper identifies promising future research directions, such as GAI-enhanced curriculum design and longitudinal studies tracking its long-term impact on learning outcomes. These findings provide a comprehensive understanding of GAI’s potential in reshaping education and offer valuable insights to researchers, educators, and policymakers interested in the intersection of GAI and education.

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A perspective on the synergistic potential of artificial intelligence and product-based learning strategies in biobased materials education

Cited by 16 publications

References 120 publications

Assessing the Intellectual Structure of the Evolving Knowledge Base on ChatGPT in the Field of Education and Health

Assessing the Intellectual Structure of the Evolving Knowledge Base on ChatGPT in the Field of Education and Health

Large Language Models (LLMs) in Engineering Education: A Systematic Review and Suggestions for Practical Adoption

Transforming Education: A Comprehensive Review of Generative Artificial Intelligence in Educational Settings through Bibliometric and Content Analysis

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