Aims & Scope

In the pursuit of regaining digital sovereignty, a critical political and societal goal in our contemporary landscape marked by pandemics, geopolitical tensions, and virtual security risks, the nexus of computing education and digital literacy emerges as central. This integrated call for workshops addresses the transformative power of computational methods, including AI, not only in education, but also in society and labor markets. Expanding on skills and qualifications for the design of digitalized futures, this call seeks interdisciplinary insights into computer science, computational studies in the social sciences, economics, and humanities, and the profound impact of computational methods on digital sovereignty, societal structures, and the evolving demands of labor markets.

Call for Papers

This workshop aims to comprehensively explore the intersection of computer science, computational methods, education research, sociological research, their respective methods and societal implications, with a special focus on digitalization and AI for and in education and educational research. It delves into interdisciplinary perspectives on the design of digitalized futures, examining aspects such as general education, labor markets, qualifications, vocational education and training, and adult education. In addition, the workshop encourages submissions that critically reflect on the application of digital methods in these research areas. The overarching goal is to understand how computational methods, especially AI, can be sensible applied in the development of digital and sustainable societies and economies. Emphasis is placed on both quantitative and qualitative research, including data science methods and AI approaches applicable to recommender systems, digitized learning, and effective linking of digital resources. Topics of interest include, but are not limited to:

• Quantitative and qualitative research

• Data science methods to analyse (vocational) education and labour market data

• Digital methods and systems in education (e-learning, adult education, general, VET and academic education, etc.)

• AI approaches for recommender systems and digitalized learning

• Linking of digital resources, a discussion of data sets, their quality and reliability, combining quantitative and qualitative data, anonymization and data protection.

• We also welcome submissions focusing on a critical reflection of digital methods in labour market research, education and other research areas.