Computer-Based Diagnostics and Systematic Analysis of Knowledge Critical Reflections and Advancements

This volume explores the rapidly advancing field of technology-supported knowledge assessment. Across academia, research on learning and instruction, AI-based analysis, psychology, and education, there is a pressing need for a comprehensive collection of foundations and methodologies related to knowledge. While the market offers books on individual and locally developed methods, a holistic overview is currently lacking. It aims to fill that gap, inspiring projects globally and benefiting knowledge-intensive developments in both digital and traditional learning environments. Understanding the state and processes of knowledge often poses a bottleneck in the quality of designs and implementations. This book addresses this challenge by focusing on mostly automated, easy-to-implement strategies, supporting the crucial task of understanding knowledge.

Part 1: Conceptual Perspectives Chapter 1: On The Process, Use And Methodological Challenges Of Assessing Knowledge.- Chapter 2: Framing Knowledge As Conceptual Structure.- Chapter 3: Knowledge In The Era Of Artificial Intelligence.- Chapter 4: A Framework For Data-Driven Computer-Based Diagnostics Of Competencies And Capabilities Across Contexts.- Part 2: Applied Perspectives.- Chapter 5: T-MITOCAR. An Epistemological Approach To Assessing Artifacts Of Knowledge.- Chapter 6: Designing Effective Technologies to Support Self-Regulated Strategies Development for Writing.- Chapter 7: Sequential Pattern Mining On Cyber Ranges For A Computer-Based Diagnostic Of Cybersecurity Skills.- Chapter 8: Tracking Competency Development In Highly Interactive Digital Learning Environments.- Chapter 9: Modeling Creativity In Education. Assessing Creativity In Students Scratch Projects: A Study On Human-AI Collaboration For Creativity Assessment.- Chapter 10: The Next Level In Personalized Learning: Adaptation Of Educational Chatbots To Students’ Individual Learning.- Chapter 11: Technology-Enhanced Feedback In K-12 Schools: Utilizing T-MITOCAR For Knowledge Artifact And Feedback.- Chapter 12: Bridging The Gap Between Math Formalism And Natural Language.

Pablo Pirnay-Dummer is Professor of Educational Psychology at Martin Luther University of Halle-Wittenberg, Germany. His research interests are the processes of language in learning, computer-linguistic methods for the psychological identification of knowledge in text, modelling and comparison of knowledge domains, expertise and complex problem-solving in processes of learning and instruction.

Dirk Ifenthaler is Professor and Chair of Learning, Design and Technology at the University of Mannheim, Germany and UNESCO Co-Chair on Data Science in Higher Education Learning and Teaching at Curtin University, Australia. Dirk’s research focuses on the intersection of cognitive psychology, educational technology, data analytics, and organizational learning.