This study confirmed the importance of AI education for fostering students’ AI literacy and derived the necessity of constructivist-oriented datasets that provide contextual relevance to students’ lives and real-world problem-solving experiences. By reconstructing the machine learning dataset development cycle through prior research, we developed datasets following each procedural step, then evaluated and refined them through expert panel interviews focusing on dataset quality metrics and characteristics of authentic activities. The datasets were deployed through educational programming platforms commonly used in AI education and designed for sustainable maintenance. To verify effectiveness, we analyzed usage metrics of the developed datasets and conducted comparative analysis of their impact on AI literacy through educational implementations. The research outcomes include development of four AI education datasets demonstrating potential to replace conventional materials like the Iris dataset. Implementation on major Korean AI education platforms confirmed high accessibility and utility, establishing these as crucial educational resources meeting classroom needs. Through application and effectiveness analysis, we verified that AI education datasets developed based on constructivism can: connect students’ prior knowledge with real-world experiences, deepen understanding of AI model learning processes, and provide authentic data-driven computing experiences - collectively contributing to comprehensive AI literacy enhancement.

Rapid digital transformation demands educational approaches that effectively equip students with competencies crucial for addressing real-world sustainability challenges. This study introduces and evaluates a Living Lab-based collaborative problem-solving educational model explicitly designed to enhance collaborative problem-solving (CPS), computational thinking (CT), and collaborative communication (CC) within elementary informatics education. Aligned with South Korea’s 2022 revised curriculum, this quasi-experimental research involved 196 elementary students, divided into experimental and control groups. Both groups participated in pre- and post-tests measuring CPS, CC, and CT competencies. The experimental group actively engaged in structured, community-based tasks integrating informatics concepts with authentic, real-world problems, whereas the control group experienced traditional instruction methods. Statistical analysis demonstrated significant improvements in the experimental group’s CPS and CT competencies (e.g., applying problem-solving strategies increased from 3.44 to 3.93, p < 0.001; ICT usage from 3.40 to 3.82, p = 0.002). However, advancements in CC were comparatively modest (creative communication increased from 3.31 to 3.81, p = 0.006), highlighting the necessity for explicit and structured communication interventions within collaborative frameworks. This study confirms the effectiveness of the Living Lab-based collaborative problem-solving educational model in cultivating comprehensive competencies essential for sustainable development, while underscoring the need for further integration of targeted communication strategies to maximize educational impact. Future implementations should prioritize structured communication training to fully leverage the model’s interdisciplinary potential.

Rapid digital transformation demands educational approaches that effectively equip students with competencies crucial for addressing real-world sustainability challenges. This study introduces and evaluates a Living Lab-based educational model explicitly designed to enhance collaborative problem-solving (CPS), computational thinking (CT), and collaborative communication (CC) within elementary informatics education. Aligned with South Korea’s 2022 revised curriculum, this quasi-experimental research involved 196 elementary students actively engaged in structured, community-based tasks that integrated informatics concepts with authentic, real-world problems. Findings demonstrated significant improvements in CPS and CT competencies, including problem comprehension, algorithmic reasoning, abstraction, and ICT usage. However, advancements in CC were comparatively modest, highlighting the necessity for explicit and structured communication interventions within collaborative frameworks. The study confirms the effectiveness of the Living Lab-based educational model in cultivating comprehensive competencies essential for sustainable development, while underscoring the need for further integration of targeted communication strategies to maximize educational impact. Future implementations should prioritize structured communication training to fully leverage the model's interdisciplinary potential.