About the project
Objective
The LATEL project aims to harness the potential of data generated by educational technologies to enhance the quality of education. The primary objectives are to identify and retain potential dropout students, motivate learners to achieve their educational goals, and support teachers in refining learning designs. By addressing the practical challenges of implementing learning analytics (LA) in educational institutions, the project seeks to develop a systemic and use-case-based approach to demonstrate how data and evidence can be utilized for informed decision-making. This involves showcasing the application of LA in a real KTH course, exploring its potential in a new KTH program, and examining the legal and ethical frameworks governing data use in learning analytics. Ultimately, the project aims to clarify the legal landscape and promote the value of LA in shaping the future of engineering education, providing a roadmap for data-driven insights and solutions to policy-related obstacles that impede the implementation of LA in universities.
Background
Learning Analytics (LA) is an interdisciplinary field that combines data science, psychology, education, and computer science to optimize learning experiences. By analyzing data from online learning platforms, student information systems, and other sources, LA provides insights into student behavior, learning processes, and institutional performance. Despite its potential to personalize learning and identify at-risk students, the practical application of LA faces significant challenges, particularly related to data identification, curation, and legal and ethical compliance. Many educational institutions struggle with poor student throughput and funding issues, highlighting the need for effective LA solutions.
Current research often focuses on empirical studies, lacking practical applications for implementing LA in academic settings. The LATEL project addresses these gaps by proposing a design-based, iterative approach to demonstrate how data can be used to enhance teaching and learning quality. By exploring legal, ethical, and practical issues, the project aims to provide actionable insights for educators and policymakers, ultimately transforming education through data-driven decision-making.
Cross-disciplinary collaboration
The LATEL project brings together a diverse team of experts from various fields to tackle the complexities of implementing learning analytics in educational settings.
- Dr. Mattias Wiggberg, the principal investigator, holds a PhD in Computer Science Didactics and has extensive experience in digital transformation and the involvement of AI in society. He also contributes with expertise in skills development and policy work in education.
- Dr. Joakim Lilliesköld, an Associate Professor in Systems Engineering Management, contributes his knowledge in engineering education development and digitalization, focusing on legal and system challenges.
- Dr. Olga Viberg, an Associate Professor in Media Technology, specializes in Technology Enhanced Learning and will guide the empirical case study on learning analytics at KTH.
- Dr. Thashmee Karunaratne, an Associate Professor in Digital Learning, brings her background in machine learning and computer science to explore digital transformation and data analytics.
- Dr. Stefan Hrastinski, a Professor with a focus on Digital Learning, offers his extensive research experience in digital learning and learning analytics.
This cross-disciplinary collaboration, supported by the Digital Futures Education Transformation Working Group, ensures a comprehensive approach to addressing the project’s objectives and achieving meaningful educational transformation.
