Potential Abstract: This study examines the cognitive biases that underlie decision-making processes in educational settings, particularly in the context of implementing artificial intelligence solutions. Drawing on principles from activity theory and the analysis of eigenvectors, we investigate how these biases impact the design and implementation of educational technologies. By applying an activity theoretic framework, we aim to uncover the complex interplay between individual and collective cognitive processes, technological artifacts, and institutional structures in shaping educational practices. Through a series of case studies and simulations, we analyze how various cognitive biases, such as confirmation bias and anchoring, influence the development and adoption of artificial intelligence solutions in education. Our findings suggest that a deeper understanding of these biases is crucial for creating more effective and equitable educational interventions. We propose a set of guidelines for educators and technology developers to mitigate the impact of cognitive biases and enhance the design of educational solutions that promote learning and engagement.
Potential References:
- Cognitive biases in Design Thinking processes: the Active Learning Lab case study
- Errors in creative thought? Cognitive biases in a complex processing activity
- Activity theory as a framework for building adaptive e-learning systems: A case to provide empirical evidence
- An analysis of students’ cognitive bias in experimental activities following a lab manual
- Improving knowledge acquisition and dissemination through technological interventions on cognitive biases
