Innovative Research Award
Marc Jansen
University of Applied Sciences Ruhr West, Germany
Marc Jansen of the University of Applied Sciences Ruhr West, Germany, is associated with research in AI Supported Learning and has a documented scholarly profile comprising 92 documents, 438 citations, and an h-index of 12 according to the supplied research profile information. The Innovative Research Award recognizes scholarly work that demonstrates originality, methodological rigor, and meaningful contribution to the advancement of knowledge. In the context of artificial intelligence-supported learning, research innovation may involve the development, evaluation, or responsible application of computational technologies that enhance educational processes, learning environments, assessment, personalization, or evidence-based decision-making.[1][2]
Abstract
Marc Jansen is a researcher affiliated with the University of Applied Sciences Ruhr West in Germany whose subject area is identified as AI Supported Learning. His research profile, as supplied for this article, includes 92 documents, 438 citations, and an h-index of 12. The Innovative Research Award recognizes research activity characterized by innovation, scholarly contribution, and relevance to the advancement of contemporary scientific and educational practice. In AI-supported learning, innovation may be reflected in the design of intelligent learning environments, data-informed educational methods, adaptive systems, and approaches that connect artificial intelligence with pedagogical objectives and learner needs. The field has developed through interdisciplinary engagement among computer science, education, learning sciences, data analytics, and human-computer interaction.[1][3]
Keywords
Innovative Research Award; Marc Jansen; AI Supported Learning; Artificial Intelligence in Education; Technology-Enhanced Learning; Learning Analytics; Educational Innovation; Research Impact
Introduction
Artificial intelligence has become an important area of research in education and learning technology. Contemporary studies examine the use of intelligent systems for personalization, learner modelling, automated feedback, educational data analysis, and decision support. The development of AI-supported learning requires attention not only to technical performance but also to pedagogical validity, human oversight, transparency, privacy, and the contextual needs of learners and educators.[3][4]
Research Profile
Marc Jansen is affiliated with the University of Applied Sciences Ruhr West in Germany. The supplied bibliometric profile records 92 documents, 438 citations, and an h-index of 12. These indicators provide quantitative measures of scholarly output and citation visibility, although bibliometric indicators are most appropriately interpreted alongside the content, quality, originality, and practical or societal relevance of the underlying research.[1]
Research Contributions
Research in AI Supported Learning is inherently interdisciplinary and may connect artificial intelligence methods with educational theory, instructional design, data analysis, and the evaluation of learning outcomes. Relevant scholarly contributions can include the development of computational approaches for learning support, the assessment of intelligent educational technologies, and the investigation of how data-driven systems can be integrated into educational contexts.[2][4]
Publications
The supplied research profile records 92 documents associated with Marc Jansen. The publication record may be evaluated through the scholarly themes, methodological approaches, publication venues, collaboration patterns, and influence of the individual contributions. In the field of AI Supported Learning, publication analysis can include research on intelligent learning systems, educational data, learning analytics, artificial intelligence applications, and technology-mediated learning environments.
Research Impact
The supplied profile indicates 438 citations and an h-index of 12. Such metrics suggest that the research output has received measurable scholarly attention within the indexed literature. However, citation counts can vary according to discipline, publication age, database coverage, collaboration patterns, and citation practices. Accordingly, research impact is best considered through a combination of quantitative indicators and qualitative assessment of originality, relevance, methodological quality, and contribution to the field.[3][5]
Award Suitability
Marc Jansen’s supplied research profile is relevant to the scope of the Innovative Research Award through its association with AI Supported Learning and its documented record of scholarly output and citation impact. The profile includes 92 documents, 438 citations, and an h-index of 12, providing quantitative evidence of sustained research activity and scholarly visibility.[2]
Conclusion
Marc Jansen of the University of Applied Sciences Ruhr West is associated with research in AI Supported Learning and has a documented profile of 92 documents, 438 citations, and an h-index of 12. The Innovative Research Award recognizes the importance of research that advances knowledge through originality, scholarly rigor, and meaningful contribution. Within the rapidly developing field of artificial intelligence-supported education, research that connects technological innovation with educational objectives remains important to the development of effective and responsible learning environments.[4]
External Links
References
- Elsevier. (n.d.). Scopus author details: Marc Jansen, Author ID 57189244074. Scopus.
https://www.scopus.com/authid/detail.uri?authorId=57189244074
- Marc J, Dan K-Vacs, Maya U. (2025). Integrating generative AI into programming education: Student perceptions and the challenge of correcting AI errors.
https://link.springer.com/article/10.1007/s40593-025-00496-4
- Marc J,J Zbick, M Milrad. (2014). Towards a web-based framework to support end-user programming of mobile learning activities.
https://ieeexplore.ieee.org/abstract/document/6901437
- Marc J, Joerg Z, & et al. (2023). Multi-dimensional tracking in virtual learning teams an exploratory study.
https://www.taylorfrancis.com/chapters/edit/10.4324/9781315045467-154/
- Marc J, A Pupyshev, et al. (2020). Gravity: a blockchain-agnostic cross-chain communication and data oracles protocol.
https://arxiv.org/abs/2007.00966