Beyond Constructionism: Learning, Agency, and Design in the Age of Artificial Intelligence

Constructionism emerged in the late 1970s as Papert recognized the personal computer's potential to transform learning from passive instruction to active knowledge construction. His vision of learners as "architects of their own microworlds" established foundational principles that have guided educational technology for decades. However, the rise of generative AI introduces qualitatively different challenges that existing constructionist frameworks cannot fully address.

Contemporary AI systems engage learners in dynamic dialogues, generate multimodal content, and adapt to individual contexts in ways that fundamentally alter the nature of human-computer interaction. These systems function not merely as tools but as cognitive partners that can surface tacit knowledge, facilitate creative exploration, and challenge traditional boundaries between knowledge creation and consumption.

The digital transformation has also reshaped human worldview components, including self-perception, social interactions, reality conception, and environmental integration. These changes demand new pedagogical approaches that recognize AI's role in mediating knowledge construction while maintaining human agency and creativity.

This special issue aims to establish new theoretical and practical foundations for education in the AI era. We seek to understand how constructionist principles can be evolved to address contemporary challenges while maintaining focus on learner agency, creativity, and meaningful knowledge construction.

Specific objectives include exploring how AI reshapes learning environments, identifying essential competencies for AI-enhanced education, developing frameworks for human-AI collaboration in learning contexts, and establishing design principles for educational technologies that preserve constructionist values while leveraging AI capabilities.

Our goal is to bridge the gap between Papert's original vision and the realities of today's AI-enhanced educational landscape, providing educators, researchers, and designers with conceptual tools and practical strategies for navigating this transformation.

We welcome diverse methodological approaches including theoretical analysis, empirical studies, design research, case studies, and critical reflections. Contributions should address topics such as meta-AI skills development, AI-human collaboration in learning environments, epistemological implications of AI in education, design principles for AI-enhanced constructionist environments, assessment and evaluation in AI-mediated learning, ethical considerations in AI-enhanced education, teacher preparation for AI integration, and cross-cultural perspectives on AI in education.

Manuscripts should demonstrate clear connections to constructionist theory while addressing contemporary challenges posed by AI technologies. We particularly encourage submissions that offer practical insights for educators and designers working to implement AI-enhanced learning environments.

Papers should be original contributions that advance understanding of learning, agency, and design in AI contexts. Empirical studies should employ rigorous methodologies appropriate to their research questions. Theoretical contributions should provide clear frameworks with practical implications. Design studies should document both process and outcomes with sufficient detail for replication and adaptation.

Authors should consider how their work contributes to the broader goal of maintaining human agency and creativity while leveraging AI's capabilities for educational enhancement. Submissions should address both opportunities and challenges, avoiding either uncritical enthusiasm or dismissive skepticism toward AI in education.

We encourage international perspectives and welcome contributions that examine cultural variations in AI adoption and educational practice. Interdisciplinary approaches that bridge education, computer science, psychology, philosophy, and design are particularly valued.

All manuscripts will undergo rigorous peer review by experts in relevant fields. We seek contributions that will shape the future of educational practice and theory in an AI-enhanced world.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Review
• Systematic Review
• Technology and Code

Keywords: Constructionism, artificial intelligence, generative AI, meta-AI skills, digital learning, educational design, agency, human-AI interaction, learning environments

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.