Marcus Specht

Prof. Dr. Marcus Specht is Professor for Digital Education at the Technical University of Delft and Director of the Leiden-Delft-Erasmus Center for Education and Learning. He is also Professor for Learning Technologies at the Welten Institute of the Open Universiteit. He received his Diploma in Psychology in 1995 and a Dissertation from the University of Trier in 1998 on adaptive information technology. From 2001 he headed the department "Mobile Knowledge" at the Fraunhofer Institute for Applied Information Technology (FIT). From 2005 to 2018 he was Professor for Learning Technologies at the Open Universiteit Nederland and head of the Learning Innovation Lab. His research focus is on Mobile and Contextualized Learning Technologies and Social and Immersive Media for Learning. Prof. Specht is an Apple Distinguished Educator and was President (2013-2015) of the International Association of Mobile Learning.


Current Research

Mobile, context-aware and seamless learning

I started doing research on mobile learning in the domain of museum information systems and museum pedagogics (Gross & Specht, 2001; Oppermann, Specht, & Jaceniak, 1999; Oppermann & Specht, 2000). In that setting I have researched different approaches for ubiquitous user modeling and context-aware mobile learning in rich physical environments. Most of this work has been continued in context-aware learning (De Jong, Specht, & Koper, 2008; Jong, Specht, & Koper, 2010; Zimmermann, Specht, & Lorenz, 2005) in architecture and teacher education.

In the last 8 years I differentiated this research into different components of a seamless learning environment taking into account the learning in situ and contextualized support (De Jong et al., 2008; Jong, Specht, Koper, & de Jong, 2008) by mobile social software, the distribution of information and approaches for contextualized learning support in distributed systems (Glahn & Specht, 2010; Verpoorten, Glahn, Kravcik, Ternier, & Specht, 2009) and the use of situated and ambient displays for learning (D Börner, Kalz, & Specht, 2014; Dirk Börner, Kalz, & Specht, 2013) and applied situated display technology in different school and professional environments. Most of this work is also documented in a book from 2015 I co-edited with Marcelo Milrad and Lung-Hsiang Wong (Wong, Milrad, & Specht, 2015).

In the last three years I focused on the use of sensor information (Schneider, Börner, van Rosmalen, & Specht, 2015) and the design of real-time feedback (Schneider, Börner, Rosmalen, & Specht, 2014a, 2014b) in ubiquitous and seamless learning support. Other works in this domain also include links to learning analytics and personal experience sampling with mobiles (Tabuenca, Kalz, Ternier, & Specht, 2014).


Personalised Learning Technologies

Actually since my PhD I worked on personalized learning technology and different research aspects of it. In the 90’s I did some work on Intelligent Tutoring Systems for learning programming and Statistics (Specht & Oppermann, 1998; Specht, Weber, Heitmeyer, & Schöch, 1997) this work was also related to recommender systems and pedagogical agents in the context of web-based learning systems (Schöch et al., 1998).

Shifting in perspective from control-based systems towards human interaction focused systems is well described in the paper I wrote with a group of people working on personalization for human learning (Dominique Verpoorten, Glahn, Kravcik, Ternier, & Specht, 2009) and this especially for personalized reflection support directed my work towards Learning Analytics and Dashboards for self-regulation and reflection support (Jivet, Scheffel, Drachsler, & Specht, 2017; D. Verpoorten, Westera, & Specht, 2011). Recent works in Learning Analytics combine sensor-networks, augmented reality, and AI to create intelligent interactive systems also embedded in real-world learning and training (Praharaj, Scheffel, Drachsler, & Specht, 2018; Schneider, Börner, van Rosmalen, & Specht, 2015).

For future work on personalized learning I think several developments are interesting and worth some exploration: a) new forms of AI for supporting personalized learning experiences with much stronger AI components for individualized coaching, assessment and training b) massive scale access to learning content and c) real-time manipulation of content and feedback also based on sensor networks.

Game-based learning and Game Design Patterns

In the last ten years I did research on using game design patterns in instructional design and learning solutions. In my research I started mostly from a design-pattern approach and applied different combination of game-design pattern for gamification of learning solutions. In two PhD thesis the overall effects of game-design patterns on learning outcomes have been analyzed for desktop computer games (Kelle, Klemke, & Specht, 2013) as also for mobile games (Schmitz, Klemke, & Specht, 2012). A recent PhD project on mobile learning games has focused on the effects of game patterns in pervasive mobile learning and coupled games to combine real world learning on the job with instruction and informal learning support (Schmitz, Klemke, Walhout, & Specht, 2015). I am currently continue this line of work with two new PhD students about real-time feedback and game design in sensor-based learning systems (Marcus Specht, 2014).

Collaborative and distributed learning technology

From 2001 to 2005 I coordinated the European Research Project Remote Access to Field Trips (RAFT) with 2.9 Mil Euro project funding. In the project we developed new technologies to extend current field trip approaches with video-conferencing, distributed task management, and shared data collection in school excursions (M. Kravcik, Kaibel, Specht, & Terrenghi, 2004; Milos Kravcik et al., 2003; M Specht, Kaibel, & Apelt, 2005; Marcus Specht & Kravcik, 2006). Research enabled remote participation and connection of distributed groups working on inquiry-based learning scenarios. From 2012 to 2015 I coordinated the European Project weSPOT ( with 2.9 Mil Euro funding, which focused on mobile inquiry-based learning in schools and higher education making use of mobile technologies for linking formal and informal learning support (Firssova et al., 2014; Kalz et al., 2014; Mikroyannidis et al., 2013).

Out of this research close cooperation with several Dutch schools in our close environment developed as also with the AGORA school. In the AGORA school system all classical curricula and scheduling components are dropped and the students basically work with a SCRUM solution to develop their individual learning plans and work on them in groups as also monitor their progress. In my recent research I am focusing on these possibilities of agile learning and making use of agile planning and agile processes in learning and especially school contexts.

Selected Publications 2018/2019

Mobile and Inquiry-Based Learning

Suárez, Á., Specht, M., Prinsen, F., Kalz, M., & Ternier, S. (2018). A review of the types of mobile activities in mobile inquiry-based learning. Computers & Education, 118, 38-55.

Specht, M., & Suarez, A. (2018). Eine Analyse von Interaktionsmustern für mobiles forschendes Lernen. In Handbuch Mobile Learning (pp. 345-363). Springer VS, Wiesbaden.

Rusman, E., Ternier, S., & Specht, M. (2018). Early Second Language Learning and Adult Involvement in a Real-World Context: Design and Evaluation of the" ELENA Goes Shopping" Mobile Game. Journal of Educational Technology & Society, 21(3).

Learning Analytics

Jivet, I., Scheffel, M., Specht, M., & Drachsler, H. (2018, March). License to evaluate: Preparing learning analytics dashboards for educational practice. In Proceedings of the 8th International Conference on Learning Analytics and Knowledge (pp. 31-40). ACM.

Di Mitri, D., Schneider, J., Specht, M., & Drachsler, H. (2018). From signals to knowledge: A conceptual model for multimodal learning analytics. Journal of Computer Assisted Learning, 34(4), 338-349.

Augmented Reality and Sensor Technology

Specht, M., Hang, L. B., & Barnes, J. S. (2019). Sensors for Seamless Learning. In Seamless Learning (pp. 141-152). Springer, Singapore.

Limbu, B. H., Jarodzka, H., Klemke, R., & Specht, M. (2018). Using sensors and augmented reality to train apprentices using recorded expert performance: A systematic literature review. Educational Research Review.

Limbu, B. H., Jarodzka, H., Klemke, R., Wild, F., & Specht, M. (2018). From AR to expertise: A user study of an augmented reality training to support expertise development. Journal of Universal Computer Science, 24(2), 108-128.

Praharaj, S., Scheffel, M., Drachsler, H., & Specht, M. (2018, September). Multimodal Analytics for Real-Time Feedback in Co-located Collaboration. In European Conference on Technology Enhanced Learning (pp. 187-201). Springer, Cham.

Schneider, J., Börner, D., van Rosmalen, P., & Specht, M. (2018). Do you Want to be a Superhero? Boosting Emotional States with the Booth. J. UCS, 24(2), 85-107.

Adoption of ICT in Higher Education

Jokiaho, A., May, B., Specht, M., & Stoyanov, S. (2018). Obstacles to using E-Learning in an Advanced Way. In The International Conference on E-Learning in the Workplace.

Jokiaho, A., May, B., Specht, M., & Stoyanov, S. (2018). Barriers to using E Learning in an Advanced Way. International Journal of Advanced Corporate Learning (iJAC), 11(1), 17-22.

Gamification of Learning

Facey-Shaw, L., Specht, M. M., Van Rosmalen, P., Boerner, D., & Bartley-Bryan, J. (2017). Educational Functions and Design of Badge Systems: A Conceptual Literature Review. IEEE Transactions on Learning Technologies.

Antonaci, A., Klemke, R., Kreijns, K., & Specht, M. (2018). Get Gamification of MOOC right!. International Journal of Serious Games, 5(3), 61-78.

Facey-Shaw, L., Specht, M., Bartley-Bryan, J., & van Rosmalen, P. (2018). Technological and Implementation Issues in Moodle-Based Digital Badge System. In ECGBL 2018 12th European Conference on Game-Based Learning (p. 82). Academic Conferences and publishing limited.

Specht, M., & So, H. J. (2018, November). Mobile Inquiry-based Learning: Relationship among levels of inquiry, learners’ autonomy and environmental interaction. In World Conference on Mobile and Contextual Learning (pp. 22-29).


Find all my publications either at dspace.ou.nl, and

Master thesis topics

Please contact me if you are interested in one of these topics for doing a master thesis.

Tangible interaction for AR Develop a framework integrating AR and tangible object interaction. The thesis should analyse and develop an approach for tangible interaction with AR models, enabling the manipulation and interaction with AR models linked to physical objects.

Radar-based detection of handcrafting activities The thesis should implement a framework to classify simple activities of users based on radar-based sensor framework ( Based on recognised gestures feedback for educational purposes should be given.

Web-based Social Reader framework The thesis should analyse existing solutions and develop a simple framework for web-based social reading implementation allowing for the social annotation and highlight of online textbooks in mobile and tablet based applications.

Tangible Feedback in VR Interaction The thesis should develop a solution for tangible feedback in VR environment based on the SenseGlove ( Furthermore it should analyse the effect of different forms of tangible feedback in VR environments on memorisability and learning of problem solving.

Voice-Based Interaction for Vocabulary Learning The thesis should build an Alexa based skill for vocabulary training. Building on educational systems for vocabulary training and learning strategies the system should help the user in defining a training corpus, build dynamic quizzes, keeping performance statistics and give direct feedback.

Prof. dr. M.M. Specht

Visiting Address
Building 28

Room: 660 West 4rd floor
Van Mourik Broekmanweg 6
2628 XE Delft
The Netherlands

Mailing Address
EEMCS, Web Information Systems
P.O. Box 5031, 2600 GA Delft
The Netherlands