Jun. Prof. Dr. Marc Philipp Janson

Following the successful acquisition of start-up funding (research seed capital), ongoing research is carried out with the help of project funding totaling €79,700, with the majority of the money being made available from the University of Mannheim's research fund following a decision by the University of Mannheim's Research Council.

The project is dedicated to the following fields of research based on preliminary work.

Initiating and maintaining goal-directed learning activities present a major self-regulatory challenge (Schunk & Zimmerman, 2023; Zimmerman & Schunk, 2011). This is also true in digital learning environments (Azevedo et al., 2011; Winters et al., 2008). In my research, I examine inter- and intraindividual differences in self-regulated learning behaviors, their antecedent conditions, and their predictive validity.

The use of behavioral data from ecologically highly valid digital learning environments provides unique insight into learning behavior compared to self-report data alone. Research programs are currently underway with various collaborative partners using different theoretical approaches.

Preliminary results of this research have already been presented at scientific meetings:

• Janson, M. P., Schnettler, T., & Bäulke, L. (2024, April). Using logfile data to evaluate motivational processes in university students' exam preparation. 2024 AERA Annual Meeting, Philadelphia, USA.
• Wissel, S. Fehringer, B. C. O. F., Münzer, S., & Janson, M. P. (2024, March). Heterogenität in Selbstberichtsdaten zu selbstreguliertem Lernen: Latente Profilanalysen an selbstberichteten selbstreguliertem Lernverhalten. In B. C. O. F. Fehringer (chair), Digital und analoge Diagnostik und Unterstützung von selbstreguliertem Lernen im Hochschulkontext. [Symposium]. 11th conference of Gesellschaft für Empirische Bildungsforschung (GEBF), Potsdam, Germany.
• Janson, M. P., Schnettler, T., & Bäulke, L. (2023, September). Eine Frage der Zeit: Die Verwendung von Logfile-Daten zur Evaluierung der Temporal-Motivation-Theory bei der digitalen Prüfungs­vorbereitung von Studierenden [Research talk]. PAEPS 2023 19. Fach­gruppen­tagung Pädagogische Psychologie, Kiel, Germany.

• Fehringer, B. C. O. F., Janson, M. P., Fehringer, B. C. O. F., & Münzer, S. (2023, September). Visible self-regulation: The association of self-regulation strategies, learning behavior, and exam success [Research talk]. PAEPS 2023 19. Fach­gruppen­tagung Pädagogische Psychologie, Kiel, Germany.
• Janson, M. P., & Janke, S. (2023, March). Goals, behavior, success – the complex triadic association of achievement goals, e-learning behavior, and exam performance [Research talk]. 10th conference of Gesellschaft für Empirische Bildungs­forschung (GEBF), Essen, Germany.
• Janson, M. P., Wissel, S., Fehringer, B. C. O. F., & Münzer, S. (2022, September). Self-reported learning strategies do not predict exam success, but digital learning protocol data dp [Research talk]. 52th conference of the German Psychological Society (DGPs), Hildesheim, Germany.
• Janson, M. P., & Dickhäuser, O. (2021, April). Individual and contextual effects on selfregulation: Comparing the predictive power of university students’ goal orientation on e-learning activities before and during the COVID-19-pandemic [Research talk]. digiGEBF 21: Bildung und Corona – digitale Konferenz der Gesellschaft für Empirische Bildungs­forschung (GEBF), Online.

My research is dedicated to the exploration, development, and evaluation of digital learning systems, particularly intelligent tutorial 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). In this regard, I am pursuing different projects

• Fitting Feedback (PhD project): Feedback effects generally vary widely (Hattie & Timperley, 2007; Kluger & DeNisi, 1996; Wisniewski et al., 2020), which is also evident in the context of practice testing (Adesope et al., 2017; Naujoks et al., 2022). My research has been dedicated to increasing the effectiveness of informative feedback by adjusting for interindividual differences. In doing so, I integrated several theoretical approaches (Higgins, 2000; Kluger & DeNisi, 1996) to the theory of fitting feedback. This implies that framing performance feedback in line with one's own strategic orientations is conducive to motivation and performance. The research program to date on this includes six empirical studies in which performance feedback was provided with different framings in the context of practice testing. The research program has resulted in the following publications (open-access) to date:
  • Janson, M. P., Siebert, J., & Dickhäuser, O. (2023). Everything right or nothing wrong? Regulatory fit effects in an e-learning context. Social Psychology of Education, 26, 107–139. https://doi.org/10.1007/s11218-022-09733-3
  • Janson, M. P., Siebert, J., & 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), 1–26. https://doi.org/10.1186/s41239-022-00358-2
  • Janson, M. P., & Dickhäuser, O. (2023). More fit, less load? Cognitive processes of receiving feedback framed towards own preferences. The Journal of Experimental Education. doi.org/10.1080/00220973.2023.2287453
• Variability/Adaptivity: Digital learning environments offer the opportunity to be inter-individually (adaptively) adjusted to the needs of the learners (Shute & Towle, 2003). In this regard, learning materials can be presented based on previous learning history. In my research, I investigate to what extent semi-generic learning content (variability) can increase learning success via desirable difficulity (Bjork & Kroll, 2015), or counter unfavorable student learning behaviors (massaged learning; Carpenter et al., 2012; Schwerter et al., 2022). Portions of this work have already led to the following contributions:
  • Wissel, S., Janson, M. P., Fehringer, B. C. O. F., & Münzer, S. (2023, September). Self-regulated learning with a digital learning system: Students apply superficial recognition in repeated testing [Research talk]. PAEPS 2023 19th Professional Group Conference on Educational Psychology, Kiel, Germany.
• Judgments of Learning (JOLs): Metacognitive beliefs about one's own learning progress are essential for guiding one's own learning behavior. In a current research project, we evaluate how one's own judgments of learning (JOLs; Rhodes, 2016) predict learning behavior in digital learning environments and thus fill an important research gap, as previous research has hardly shown ecologically valid settings and a long-term view of the effects of JOLs (Soderstrom et al., 2016).
  • Janson, M. P., Wissel, S., Schäfer, F. & Undorf, M. (2024, March). Judgments of Learning prädizieren Lernverhalten und Erfolg in intelligenten tutoriellen Lernsystemen. In Schwerter, J. & von Keyserlingk, L. (chair), Selbsttests, Lernverhalten und Leistung in der Hochschulbildung. Einblicke aus digitale Verhaltensspurdaten und Selbstberichten.[Symposium]. 11th conference of Gesellschaft für Empirische Bildungsforschung (GEBF), Potsdam, Germany.

Performance appraisal is the evaluation of outcomes measured against standards of comparison (Heckhausen, 1974). Different standards (reference norms) can be used for performance appraisal, such as a critical reference norm that evaluates the outcome against established factual criteria. In addition to this factual reference norm, however, judgers may draw on intra- and interindividual comparisons and evaluate the performance of the appraisee against prior performance (individual reference norm) or against the performance of others (social reference norm).

Research on teachers' reference norm orientation has been extremely fruitful (Rheinberg, 1980; 1982; see also Mischo & Rheinberg, 1995; Rheinberg & Krug, 1993). However, except for a few acceptances (Dickhäuser et al., 2017; Lüdtke et al., 2005; Retelsdorf & Günther, 2011), the literature is limited to German-speaking countries and a current systematic survey of the existing literature as well as a quantitative synthesis is lacking.

As part of the current META-BNO research project, I aim to produce such a review paper on the effects of teachers' reference norm orientations with Prof. Dr. Oliver Dickhäuser and with the support of our research interns, Julia Hilpert and Jakob Maurer.

If you have (unpublished) manuscripts or data that should be included in this research project, please feel free to contact us.

In addition to the projects outlined, my research is concerned with the following additional topics and constructs, some of which are related to or arose from the aforementioned research projects or were illuminated in the context of supervised theses:

• Achievement Goals: Achievement goals describe different strategic approaches to goal-directed learning activities. Here, learning goals that focus on skill acquisition can be distinguished from performance goals that focus on skill demonstration (Dweck & Leggett, 1988; Elliot, 2005; Murayama et al., 2012). Currently, I am concerned on the one hand with the extent to which goal orientations are related to learning behaviors in digital learning environments and on the other hand with the question of the content link between goal orientations and regulatory focus theory (Higgins, 2000, 2002). The following (selected) conference papers relate to this work:
  • Janson, M. P., & Janke, S. (2023, March). Goals, behavior, success – the complex triadic association of achievement goals, e-learning behavior, and exam performance [Research talk]. 10th conference of Gesellschaft für Empirische Bildungs­forschung (GEBF), Essen, Germany.
  • Bossert, S., &  Janson, M. P. (2023, August). Beyond approach-avoidance: Achievement goals, regulatory foci, and self-guides. In M. Daumiller & M. P. Janson (chair), Goals, reasons, and complexes: Current advances in achievement goal research. [Symposium]. 19th EARLI Conference, Thessaloniki, Greece.
• Large-scale assessments: I also pursue the use of large data sets to answer psychological questions outside of my research on digital self-regulated learning. I also like to contribute to secondary data analyses from international school performance comparison studies (e.g., PISA). This has resulted in the following work so far:
  • Marksteiner, T., Janson, M. P., & Beißert, H. (2021). Belonging as compensator: Social belonging moderates the relation between bullying and well-being worldwide. Journal of Developmental and Educational Psychology, 52, 116–126. doi.org/10.1026/0049-8637/a000221
  • Marksteiner, T, Janson, M. P., & Dickhäuser, O. (2019, September). Social belonging and well-being: The moderating role of socioeconomic context on the individual, school and country level [Research talk]. paEpsy – Symposium of Educational and Developmental Psychology, Leipzig, Germany.
• Gamification: The use of design principles from (video) games in learning contexts represents another exciting research opportunity in the context of digital learning environments (Kapp, 2012; Sailer & Homner, 2020). I have already dealt with this topic in the context of supervising a master's thesis.