Knowledge Construction and Learning Models from AI Perspectives

Dear Colleagues,

In the era of artificial intelligence (AI), the fundamental processes of knowledge construction and learning models are undergoing profound transformation. From a systems science and engineering perspective, learning and knowledge creation can be viewed as complex adaptive systems comprising interacting components—learners, content, contexts, and technologies—where emergent behaviors arise from nonlinear feedback loops and self-organization. AI technologies, particularly large language models (LLMs) and adaptive learning systems, offer unprecedented capabilities to analyze, represent, and facilitate the complex dynamics of how knowledge is built, shared and internalized within these systemic structures. This shift necessitates a deep re-examination of theoretical frameworks and the innovation of practical pedagogical strategies through a systems lens. Moving beyond mere information delivery, the core challenge and opportunity lie in leveraging AI to actively support collaborative knowledge building, foster meta-cognitive skills, and create personalized, context-aware learning pathways while considering system-level properties such as robustness, adaptability, and holistic optimization. This Special Issue will explore the synergistic integration of AI with learning sciences, focusing on how intelligent systems can scaffold and enhance the architecture of learning and knowledge creation from systems engineering and system dynamics perspectives.

We invite original research and review articles that investigate the intersection of AI learning theory and practice, paying particular attention to systems-oriented approaches. Topics of interest include but are not limited to, the following:

• Systems-theoretic models of knowledge construction in AI-enhanced learning environments;
• Design and system-level efficacy evaluation of AI-scaffolded collaborative learning platforms;
• Learning analytics and AI for modeling learner understanding and conceptual change using system dynamics;
• Adaptive and personalized language teaching and learning driven by AI with feedback control mechanisms;
• The role of AI in supporting meta-cognition and self-regulated learning within cybernetic learning loops;
• AI-enabled tools for visualizing knowledge structures and argumentation as complex system maps;
• Integration of AI with constructivist and social learning pedagogies from a systems integration perspective;
• Case studies on AI-facilitated learning communities and knowledge building discourse as complex adaptive systems;
• Ethical and epistemological considerations in AI-mediated knowledge formation through systemic governance;
• Future directions for human–AI partnership in reinventing learning models via systems engineering approaches.

We invite contributions outlining empirical evidence, theoretical insights or innovative design principles, especially those applying systems thinking, feedback control, or complex systems modeling to AI-mediated learning environments. This Special Issue will serve as a foundational resource for educators and researchers to shape the future of learning from AI perspectives.

Dr. Feng Zhang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• knowledge construction
• learning models
• education innovation
• AI
• system science