The demand for personalized learning experiences and effective analytics in education has significantly increased. The integration of technology in education has brought about significant changes in teaching and learning practices. In the era of digital technology, the integration of education technology in the classroom has led to a change in teaching methods and learning strategies. In this paper, we introduce the KNIGHT (AI in Education at Hochschule für Technik (HFT) Stuttgart) framework, which is a holistic solution designed to tackle the complex issue of personalized education in a digital era. The paper explores the application of multimodal data integration, the novel application of deep reinforcement learning to education analytics, and the ethical consideration of privacy-preserving personalized feedback. The proposed framework’s efficacy is substantiated through a case study, demonstrating its potential to revolutionize personalized education. This paper provides a comprehensive overview of the current discourse, providing valuable insights for educators, policymakers, and researchers into the multifaceted landscape of modern education, contributing to ongoing discussions and advancements in educational technology.

This paper describes the intention to integrate Internet of Things (IoT) and Industry 4.0 related learning resources in a remote and virtual lab-based environment for higher education and research. The objective of this concept is to provide a laboratory environment as integral part of the curriculum at universities and as, in equal measure, an industry-related service for researchers. The educational aim of the lab focusses on the development of competences to meet current and future professional industrial requirements. The paper describes the challenges which need to be tackled for the technical integration and the design of the learning environment and it is structured into three main chapters: (1) Description of the intention for the project and outline of the idea for an Industry 4.0-/IoT-Lab platform. (2) Presentation of the didactical approach and description of the implementation based on three scenarios. (3) Presentation of key findings and first results as well as current tasks.

Purpose: This paper presents a maturity model for digital transformation effectiveness in laboratories (labs) with education and research purposes.Design/methodology/approach: The model was developed using design science research methodology, expert interviews and case studies.Findings: The model fulfills three practical goals: (1) to establish comparability of the effectiveness of the digital transformation of labs, (2) to provide lab operators from academia and industry with a guide for (further) transformation and (3) to build initial trust among lab users. In addition, the maturity model contributes to the literature on digital lab transformation by capturing, describing, structuring and evaluating relevant dimensions, items and levels. Model strengths and weaknesses, areas for improvement, international applicability and practical and reusable recommendations are presented as well as the added value in assessing lab functionalities and lab sustainability.Practical implications: Although originally developed as a maturity model driven by lab education, the model is also suitable for the transformation of research labs in manufacturing technology management. Digital labs can efficiently support industry training and research and development activities as well as simulate the development of new processes prior to their implementation.Originality/value: Especially for these use cases, the authors see application potentials for the use of online labs from an organizational perspective and from the perspective of stakeholders such as industry users and operators with a manufacturing background, who use and develop transformed labs for teaching and research.