Marc Philipp Janson

On September 1, 2024, I took up the tenure-track professorship in Educational Psychology with a focus on Educational Design and Educational Effectiveness at the University of Education Karlsruhe. At the Institute of Psychology, my research focuses on self-regulated learning (SRL) in intelligent tutoring systems (ITS). Within this research program, I supervise the doctoral dissertation of my research associate Julia Hilpert. Previously, I worked at the University of Mannheim, where I continue to lead a research project until 2026. Before pursuing my academic career, I co-developed the intelligent tutoring system CoTutor, which I continue to use for research purposes.

You can reach me at janson(at)ph-karlsruhe.de.

Research Areas and Interests

Self-Regulated Learning in Digital Learning Environments

Initiating and maintaining goal-directed learning activities is a major self-regulatory challenge (Schunk & Zimmerman, 2023; Zimmerman & Schunk, 2011). This also applies to digital learning environments (Azevedo et al., 2011; Winters et al., 2008). In my research, I investigate interindividual and intraindividual differences in self-regulated learning behavior, their antecedents, and their predictive validity.

The use of behavioral data from ecologically valid digital learning environments provides unique insights into learning behavior compared with relying exclusively on self-report data. Several research programs involving different collaboration partners are currently underway, each pursuing different theoretical approaches.

Evaluation and Optimization of Intelligent Tutoring Systems

My research focuses on the investigation, development, and evaluation of digital learning systems, particularly intelligent tutoring systems (Kulik & Fletcher, 2016; Mousavinasab et al., 2021), that support learners in digital self-regulated learning (Azevedo et al., 2011; Schunk & Zimmerman, 2023; Winters et al., 2008; Zimmerman & Schunk, 2011). Within this area, I pursue several projects:

• Fitting Feedback (doctoral research project): Feedback effects generally vary considerably (Hattie & Timperley, 2007; Kluger & DeNisi, 1996; Wisniewski et al., 2020), including in the context of practice testing (Adesope et al., 2017; Naujoks et al., 2022). My research has focused on increasing the effectiveness of informative feedback by adapting it to interindividual differences. For this purpose, I integrated several theoretical approaches (Higgins, 2000; Kluger & DeNisi, 1996) into the theory of Fitting Feedback. This theory proposes that framing performance feedback in accordance with learners' own strategic orientations can enhance motivation and performance. The research program conducted to date comprises six empirical studies in which performance feedback was framed in different ways in the context of practice testing.
• Variability and Adaptivity: Digital learning environments provide opportunities to adapt learning materials to learners' individual needs (Shute & Towle, 2003). Learning materials can be presented based on learners' previous learning histories. My research investigates whether semi-generative learning content and increased variability can improve learning outcomes through so-called desirable difficulties (Bjork & Kroll, 2015) and whether they can counteract unfavorable learning behaviors among students, such as massed learning (Carpenter et al., 2012; Schwerter et al., 2022).
• Judgments of Learning (JOLs): Metacognitive beliefs about one's own learning progress are essential for regulating learning behavior. In a current research project, we evaluate how learners' own assessments of their learning progress, or judgments of learning (JOLs; Rhodes, 2016), predict learning behavior in digital learning environments. This work addresses an important research gap because previous research has rarely examined ecologically valid settings or the long-term effects of JOLs (Soderstrom et al., 2016).

Meta-Analysis on Teachers' Reference Norm Orientations

Achievement evaluation involves assessing results against comparison standards (Heckhausen, 1974). Different standards of comparison can be used for this purpose. These include criterion-referenced standards, which evaluate a result against predefined objective criteria. In addition to such criterion-referenced standards, evaluators may use intraindividual or interindividual comparisons, assessing a person's performance either against their own previous performance (individual comparison standard) or against the performance of others (social comparison standard).

Research on teachers' reference norm orientations has been highly influential (Rheinberg, 1980, 1982; see also Mischo & Rheinberg, 1995; Rheinberg & Krug, 1993). With only a few exceptions (Dickhäuser et al., 2017; Lüdtke et al., 2005; Retelsdorf & Günther, 2011), however, the literature has remained largely confined to German-speaking countries. An up-to-date systematic review of the existing literature and a quantitative synthesis are still lacking.

Selected Publications

• Hilpert, J., & Janson, M. P. (2026). Tracing affect in digital learning: Combining log data and introspective momentary assessments, Computers & Education, 105668.
• Janson, M. P., Wissel, S., Ingendahl, F., & Undorf, M. (2026). Judgments of learning in the wild: Establishing ecological validity with an intelligent tutoring system in a field study Learning and Instruction.103, 102293.
• Janson, M. P., Wenker, T. und Bäulke, L. (2024). Only a matter of time? Using logfile data to evaluate temporal motivation theory in university students' examination preparation. British Journal of Educational Psychology, 1–16.
• Janson, M. P. und Dickhäuser, O. (2023). More fit, less load? Cognitive processes of feedback framed toward own preferences. The Journal of Experimental Education : JXE, 1–21.
• Janson, M. P., Siebert, J. und Dickhäuser, O. (2023). Everything right or nothing wrong? Regulatory fit effects in an e-learning context. Social Psychology of Education, 26, 107–139.
• Janson, M. P., Siebert, J. und Dickhäuser, O. (2022). Compared to what? Effects of social and temporal comparison standards of feedback in an e-learning context. International Journal of Educational Technology in Higher Education, 19, 1–26.
• Janson, M. P. und Dickhäuser, O. (2019). Prüfungsvorbereitung an der Hochschule mittels Lernsoftware: Die Effekte von Wenn-Dann-Plänen. Unterrichtswissenschaft, 47, 295