征稿期刊

Learning and Motivation

期刊级别

IF 1.8 (JCR 2024)

SSCI

Q3 (PSYCHOLOGY, BIOLOGICAL 10/18)

Q3 (PSYCHOLOGY, EXPERIMENTAL 56/102)

征稿主题

Quantum Cognition: A Promising Approach to Understanding Learning and Motivation in Educational Setting

细分领域

Designing and evaluating strategies, using principles like superposition, to help students navigate competing academic, social, and personal goals, thereby improving engagement and well-being.

Applying quantum concepts to create practical strategies or support mechanisms that address teacher goal conflicts, enhance professional well-being, and foster resilient identities.

Developing or refining decision-support tools, informed by quantum probability, to assist students and teachers in making more effective choices under ambiguity or uncertainty.

Designing and assessing collaborative environments or pedagogical techniques inspired by quantum entanglement to foster productive interdependence and shared motivation.

Investigating and applying principles of quantum context effects (e.g., framing, sequencing) to develop practical instructional strategies that optimize conceptual change and motivational shifts.

Developing or refining AI-driven educational tools and human-AI interactions by applying quantum cognitive perspectives to better support learning processes and sustain motivation.

Translating findings on how individual variations manifest in quantum-like cognitive processes into tailored pedagogical approaches or support systems for students and teachers.

Applying quantum models to design or evaluate features within digital learning platforms that dynamically adapt to and positively influence motivational fluctuations and self-regulation.

Creating and validating novel empirical methodologies (quantitative, qualitative, mixed-methods) inspired by quantum principles, aimed at yielding actionable insights for educational improvement.

Employing quantum formalisms to develop and test models that capture the dynamic evolution of learning and motivation, enabling more effective and timely support.

重要时间

Submission Deadline: 31 January 2026