GAIDE: A Framework for Using Generative AI to Assist in Course Content Development
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arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866913736518795264 |
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| author | Dickey, Ethan Bejarano, Andres |
| author_facet | Dickey, Ethan Bejarano, Andres |
| contents | This paper introduces "GAIDE: Generative AI for Instructional Development and Education," a novel framework for using Generative AI (GenAI) to enhance educational content creation. GAIDE stands out by offering a practical approach for educators to produce diverse, engaging, and academically rigorous materials. It integrates GenAI into curriculum design, easing the workload of instructors and elevating material quality. With GAIDE, we present a distinct, adaptable model that harnesses technological progress in education, marking a step towards more efficient instructional development. Motivated by the demand for innovative educational content and the rise of GenAI use among students, this research tackles the challenge of adapting and integrating technology into teaching. GAIDE aims to streamline content development, encourage the creation of dynamic materials, and demonstrate GenAI's utility in instructional design. The framework is grounded in constructivist learning theory and TPCK, emphasizing the importance of integrating technology in a manner that complements pedagogical goals and content knowledge. Our approach aids educators in crafting effective GenAI prompts and guides them through interactions with GenAI tools, both of which are critical for generating high-quality, contextually appropriate content. Initial evaluations indicate GAIDE reduces time and effort in content creation, without compromising on the breadth or depth of the content. Moreover, the use of GenAI has shown promise in deterring conventional cheating methods, suggesting a positive impact on academic integrity and student engagement. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2308_12276 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | GAIDE: A Framework for Using Generative AI to Assist in Course Content Development Dickey, Ethan Bejarano, Andres Computers and Society K.3.2 This paper introduces "GAIDE: Generative AI for Instructional Development and Education," a novel framework for using Generative AI (GenAI) to enhance educational content creation. GAIDE stands out by offering a practical approach for educators to produce diverse, engaging, and academically rigorous materials. It integrates GenAI into curriculum design, easing the workload of instructors and elevating material quality. With GAIDE, we present a distinct, adaptable model that harnesses technological progress in education, marking a step towards more efficient instructional development. Motivated by the demand for innovative educational content and the rise of GenAI use among students, this research tackles the challenge of adapting and integrating technology into teaching. GAIDE aims to streamline content development, encourage the creation of dynamic materials, and demonstrate GenAI's utility in instructional design. The framework is grounded in constructivist learning theory and TPCK, emphasizing the importance of integrating technology in a manner that complements pedagogical goals and content knowledge. Our approach aids educators in crafting effective GenAI prompts and guides them through interactions with GenAI tools, both of which are critical for generating high-quality, contextually appropriate content. Initial evaluations indicate GAIDE reduces time and effort in content creation, without compromising on the breadth or depth of the content. Moreover, the use of GenAI has shown promise in deterring conventional cheating methods, suggesting a positive impact on academic integrity and student engagement. |
| title | GAIDE: A Framework for Using Generative AI to Assist in Course Content Development |
| topic | Computers and Society K.3.2 |
| url | https://arxiv.org/abs/2308.12276 |