Innovative Tangible Interactive Games for Enhancing Artificial Intelligence Knowledge and Literacy in Elementary Education: A Pedagogical Framework

• URL: http://arxiv.org/abs/2506.00651v1
• Date: Sat, 31 May 2025 17:40:30 GMT
• Title: Innovative Tangible Interactive Games for Enhancing Artificial Intelligence Knowledge and Literacy in Elementary Education: A Pedagogical Framework
• Authors: Nikolaos Sampanis,
• Abstract summary: This paper presents an innovative framework employing tangible interactive games to enhance artificial intelligence (AI) knowledge and literacy.<n> Recognizing the growing importance of AI competencies in the 21st century, this study addresses the critical need for age-appropriate, experiential learning tools.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper presents an innovative pedagogical framework employing tangible interactive games to enhance artificial intelligence (AI) knowledge and literacy among elementary education students. Recognizing the growing importance of AI competencies in the 21st century, this study addresses the critical need for age-appropriate, experiential learning tools that demystify core AI concepts for young learners. The proposed approach integrates physical role-playing activities that embody fundamental AI principles, including neural networks, decision-making, machine learning, and pattern recognition. Through carefully designed game mechanics, students actively engage in collaborative problem solving, fostering deeper conceptual understanding and critical thinking skills. The framework further supports educators by providing detailed guidance on implementation and pedagogical objectives, thus facilitating effective AI education in early childhood settings. Empirical insights and theoretical grounding demonstrate the potential of tangible interactive games to bridge the gap between abstract AI theories and practical comprehension, ultimately promoting AI literacy at foundational educational levels. The study contributes to the growing discourse on AI education by offering scalable and adaptable strategies that align with contemporary curricular demands and prepare young learners for a technologically driven future.

Related papers

• A Structured Unplugged Approach for Foundational AI Literacy in Primary Education [7.495145157323768]
  We propose a structured teaching approach that fosters foundational AI literacy in primary students.<n>Our results indicate improvements in terminology understanding and usage, features description, logical reasoning, and evaluative skills.<n>The approach proved engaging, with students particularly enjoying activities that linked AI concepts to real-world reasoning.
  arXiv  Detail & Related papers  (2025-05-27T16:23:57Z)
• Form-Substance Discrimination: Concept, Cognition, and Pedagogy [55.2480439325792]
  This paper examines form-substance discrimination as an essential learning outcome for curriculum development in higher education.<n>We propose practical strategies for fostering this ability through curriculum design, assessment practices, and explicit instruction.
  arXiv  Detail & Related papers  (2025-04-01T04:15:56Z)
• AI in Education: Rationale, Principles, and Instructional Implications [0.0]
  Generative AI, like ChatGPT, can create human-like content, prompting questions about its educational role.<n>The study emphasizes deliberate strategies to ensure AI complements, not replaces, genuine cognitive effort.
  arXiv  Detail & Related papers  (2024-12-02T14:08:07Z)
• Generative AI Literacy: Twelve Defining Competencies [48.90506360377104]
  This paper introduces a competency-based model for generative artificial intelligence (AI) literacy covering essential skills and knowledge areas necessary to interact with generative AI.<n>The competencies range from foundational AI literacy to prompt engineering and programming skills, including ethical and legal considerations.<n>These twelve competencies offer a framework for individuals, policymakers, government officials, and educators looking to navigate and take advantage of the potential of generative AI responsibly.
  arXiv  Detail & Related papers  (2024-11-29T14:55:15Z)
• From MOOC to MAIC: Reshaping Online Teaching and Learning through LLM-driven Agents [78.15899922698631]
  MAIC (Massive AI-empowered Course) is a new form of online education that leverages LLM-driven multi-agent systems to construct an AI-augmented classroom. We conduct preliminary experiments at Tsinghua University, one of China's leading universities.
  arXiv  Detail & Related papers  (2024-09-05T13:22:51Z)
• Collaborative Design of AI-Enhanced Learning Activities [0.0]
  We develop a formative intervention that enables preservice teachers, in-service teachers, and EdTech specialists to effectively incorporate AI into their teaching practices. Participants reflect on AI's potential in teaching and learning by exploring different activities that can integrate AI literacy in education, including its ethical considerations and potential for innovative pedagogy.
  arXiv  Detail & Related papers  (2024-07-09T08:34:08Z)
• From Algorithm Worship to the Art of Human Learning: Insights from 50-year journey of AI in Education [0.0]
  Current discourse surrounding Artificial Intelligence (AI) oscillates between hope and apprehension. This paper delves into the complexities of AI's role in Education, addressing the mixed messages that have both enthused and alarmed educators. It explores the promises that AI holds for enhancing learning through personalisation at scale, against the backdrop of concerns about ethical implications.
  arXiv  Detail & Related papers  (2024-02-05T16:12:14Z)
• Bringing Generative AI to Adaptive Learning in Education [58.690250000579496]
  We shed light on the intersectional studies of generative AI and adaptive learning. We argue that this union will contribute significantly to the development of the next-stage learning format in education.
  arXiv  Detail & Related papers  (2024-02-02T23:54:51Z)
• Exploring Parent's Needs for Children-Centered AI to Support Preschoolers' Interactive Storytelling and Reading Activities [52.828843153565984]
  AI-based storytelling and reading technologies are becoming increasingly ubiquitous in preschoolers' lives. This paper investigates how they function in practical storytelling and reading scenarios and, how parents, the most critical stakeholders, experience and perceive them. Our findings suggest that even though AI-based storytelling and reading technologies provide more immersive and engaging interaction, they still cannot meet parents' expectations due to a series of interactive and algorithmic challenges.
  arXiv  Detail & Related papers  (2024-01-24T20:55:40Z)
• Multimodality of AI for Education: Towards Artificial General Intelligence [14.121655991753483]
  multimodal artificial intelligence (AI) approaches are paving the way towards the realization of Artificial General Intelligence (AGI) in educational contexts. This research delves deeply into the key facets of AGI, including cognitive frameworks, advanced knowledge representation, adaptive learning mechanisms, and the integration of diverse multimodal data sources. The paper also discusses the implications of multimodal AI's role in education, offering insights into future directions and challenges in AGI development.
  arXiv  Detail & Related papers  (2023-12-10T23:32:55Z)
• An interdisciplinary conceptual study of Artificial Intelligence (AI) for helping benefit-risk assessment practices: Towards a comprehensive qualification matrix of AI programs and devices (pre-print 2020) [55.41644538483948]
  This paper proposes a comprehensive analysis of existing concepts coming from different disciplines tackling the notion of intelligence. The aim is to identify shared notions or discrepancies to consider for qualifying AI systems.
  arXiv  Detail & Related papers  (2021-05-07T12:01:31Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.