Exploring Algorithmic Storytelling: Leveraging Large Language Models for Engineered Praxis in Education

Potential Abstract:
This research article investigates the potential of algorithmic storytelling in education through the utilization of large language models. With recent advancements in artificial intelligence and natural language processing, large language models such as OpenAI’s GPT-3 have sparked considerable interest and raised important questions about their application in educational contexts. This study aims to explore the possibilities and challenges of using these models to engineer praxis in education, particularly in the realm of storytelling.

Abstract: Algorithmic storytelling refers to the process of creating narratives generated by algorithms, with the aim of enhancing educational experiences and outcomes. This article presents a conceptual framework for understanding and implementing algorithmic storytelling in educational settings, drawing on theories of narrative, technology-enhanced learning, and pedagogical practices. Through an analysis of current literature and case studies, this article examines the potential benefits, risks, and ethical considerations associated with algorithmic storytelling as an educational tool.

By leveraging large language models, such as GPT-3, educators can harness the power of these models to create personalized and engaging learning experiences. These models have the ability to generate stories, answer questions, and provide insightful feedback, thereby enhancing student engagement, promoting critical thinking, and fostering creativity. However, concerns arise regarding issues of bias, data privacy, and the impact on human agency. This article delves into these concerns and proposes strategies to mitigate potential risks.

Moreover, this article discusses the implications for curriculum design, teacher training, and assessment practices when integrating algorithmic storytelling into educational settings. It explores the role of teachers as facilitators and guides in algorithmic storytelling experiences, emphasizing the importance of scaffolding, reflection, and evaluation. Additionally, this article highlights the potential of algorithmic storytelling to foster interdisciplinary learning, promote cultural inclusivity, and support students with diverse learning needs.

In conclusion, this research article provides a comprehensive exploration of algorithmic storytelling in education, highlighting its potential benefits, challenges, and ethical considerations. By examining the integration of large language models into educational praxis, this study contributes to the ongoing discussion surrounding the use of artificial intelligence in education. The findings and insights presented in this article aim to inform educators, policymakers, and researchers interested in leveraging algorithmic storytelling for transformative educational experiences.

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