Individual Development and Adaptive Learning
Since March 2026, Garvin Brod has been leading the Individual Development and Adaptive Learning Lab at the IWM. The group’s research focuses on the development of learning and self-regulation in the context of digital media and adaptive learning environments. The lab is currently being set up.
Employees
Deputy Head of Lab
+49 7071 979-341a.schueler@iwm-tuebingen.de
Team assistance
+49 7071 979-338p.ebert@iwm-tuebingen.de
Scientist and Junior Research Group Leader
+49 7071 979-160m.su@iwm-tuebingen.deAssociated scientists
Associated Scientist
j.breitwieser@iwm-tuebingen.de
Katharina Fleig
Scientist
k.fleig@iwm-tuebingen.de
Dr. Pauline Frick
Associated Scientist
p.frick@iwm-tuebingen.deAssociated Scientist
e.holstein@iwm-tuebingen.deAnn-Kathrin Krause
Associated Scientist
a.krause@iwm-tuebingen.deAssociated Scientist
m.schaaf@iwm-tuebingen.deAssociated Scientist
s.sukjaitham@iwm-tuebingen.deProjects
SMARTKIDS: Smartphone Use and Child Development
Individual Development and Adaptive Learning
Duration 03/2026 - open
Registration for the SMARTKIDS Study is now open (German only): Register now
Go to projectEffects of Tracing in Augmented Reality
Individual Development and Adaptive Learning
Duration 10/2024 - open
Learning in three-dimensional virtual environments, such as virtual or augmented reality (VR, AR), is gaining increasing relevance in educational contexts, including schools. However, little is currently known about how learners can be effectively supported in processing educational content within these environments. This project investigates whether the well-established learning strategy of tracing—the act of following shapes with one’s finger—can also enhance learning in three-dimensional virtual environments, and which specific aspects of tracing contribute to this effect.
Go to projectFuture Innovation Space
Individual Development and Adaptive Learning
Duration 11/2023 - open
The IWM's 300 m² experience and experimentation space explores how advanced, innovative technologies, educational research and concepts can be effectively combined to support digital teaching and learning. By enabling hands-on experimentation with emerging technologies, it makes the future of education tangible while encouraging reflection on the opportunities and challenges they present. The goal is to develop well-founded didactic applications for future classrooms. Opened in 2023, the Future Innovation Space (FIS) is part of the “lernen.digital” competence network.
Go to projectValidation and reactivation processes in learning with texts and pictures
Individual Development and Adaptive Learning
Duration 01/2021 - open
Learning with texts and pictures, so-called multimedia material, plays a central role in different learning contexts (e.g. school). While the positive effect of text-picture combinations on learning success has been demonstrated frequently, the underlying cognitive processes have received less attention so far. Therefore, the project focuses on the cognitive processes in learning with text-picture combinations. We aim to further develop existing theories and to derive supportive measures for learners.
Go to projectEffects of automated feedback on metacognitive regulation and learning performance
Individual Development and Adaptive Learning
Duration 08/2020 - open
Adaptive learning systems should support learners by, e.g., personalized feedback. In this dissertation project, a tool is developed that automatically analyzes learners' written answers based on Natural Language Processing methods. This tool will then be implemented in a learning environment that provides automatic feedback adapted to the learners' answers. Subsequently, the impact of this feedback on performance and user acceptance will be investigated.
Go to projectChanging misconceptions through refutational text and pictorial representations
Individual Development and Adaptive Learning
Duration 01/2018 - open
Many people have misconceptions about scientific phenomena. Research shows that texts in which these misconceptions are explicitly addressed (refutational text) represent a possibility for long-term revision of misconceptions. This project investigates whether pictorial representations (self-generated drawings, pictures, videos) can further reinforce this positive effect. The results of this project are relevant wherever misconceptions play a role (e.g. school or university).
Go to projectOrder effects when reading multiple texts
Individual Development and Adaptive Learning
Duration 08/2017 - open
When searching for information on the Internet, one often comes across different, often contradictory explanations for the same phenomenon. This project investigates how reading different explanations for the same natural phenomenon affects recall performance and how sequence effects influence recall performance. The results from this project are relevant wherever information retrieval plays a role, for example, in school or university.
Go to projectTüDiLab: The Tübingen Digital Teaching Lab
Individual Development and Adaptive Learning
Duration 07/2016 - open
The Tübingen Digital Teaching Lab (TüDiLab) simulates a classroom equipped with up-to-date digital media and data collection instruments. The project has two aims: (1) practice-oriented professionalization of teachers related to their media competence in the context of the Tübingen School of Education, and (2) research on the effects of teaching with digital media.
Go to project
Publications
Articles (peer-reviewed)
- Fütterer, T., Gerjets, P., Steinhäuser, R., Fabian, A., Udvardi-Lakos, N., Greene, J. A., Bernacki, M. L., Brod, G., & Trautwein, U. (2026). Why using AI as a learning coach can improve education. Nature Human Behaviour. Advance online publication. https://doi.org/10.1038/s41562-026-02524-2
- Bruckbauer-Schwed, M., Roth, L. H. O., Plöderl, M., Tomasevic, A., Keglevic, M., & Laireiter, A.-R. (2026). Dynamic Exploratory Graph Analysis (dynEGA) of affect and self-harm urge in Non-Suicidal Self-Injury (NSSI): Three illustrative case studies. Psychiatry Research Case Reports, Article 100342. https://doi.org/10.1016/j.psycr.2026.100342
- Lin, W. M., FitzGibbon, L., Theobald, M., Breitwieser, J., Brod, G., Murayama, K., & Sakaki, M. (2026). The dynamic interplay between goal setting, performance, and emotions in self-regulated learning: A computational modeling approach. Journal of Educational Psychology, 118(5), 811-828. https://doi.org/10.1037/edu0001022
- Breitwieser, J., Brod, G., & Malmberg, L.-E. (2026). Testing a three-phase model of the relationship between motivational appraisals, observable engagement, and subjective engagement: Insights from combining mobile learning data and daily diaries. Journal of Educational Psychology, 118(4), 556-576. https://doi.org/10.1037/edu0001009
- Tissot, T. T., & Roth, L. H. O. (2026). Anti-obesity medication use sparks effort-based sanctions and social penalties. Scientific Reports, 16, Article 13033. https://doi.org/10.1038/s41598-026-42166-y
- Bernier, J., Heyer, N., Su, M., Yan, L., Ha, J., Islam, R., Jordan, M., & Nelson, B. (2026). A design-based approach to playful algebra learning with DragonBox Algebra. Digital Experiences in Mathematics Education. https://doi.org/10.1007/s40751-026-00195-2
- Theobald, M., Lin, W. M., Sakaki, M., Murayama, K., & Brod, G. (2026). How (much) do people revise their goals after success and failure? The Triple-A model of goal revision. Educational Psychologist, 61(1), 35-55. https://doi.org/10.1080/00461520.2025.2533232
- Jankowski, J.*, Roth, L. H. O.*, Meindl, D., Clay, G., Mlynski, C., Freiman, O., Nordmann, A., Stenzel, L., & Wagner, V. (2026). What is self-control and how can we measure it? Frontiers for Young Minds, 14, Article 1565481. *shared first authorship. https://doi.org/10.3389/frym.2026.1565481
- Hoch, E., Stürmer, S., Jonkmann, K., & Scheiter, K. (2026). Paper-pencil vs. e-exams: Revisiting the screen inferiority effect during high-stakes testing at university. Learning and Instruction, 101, Article 102226. https://doi.org/10.1016/j.learninstruc.2025.102226
- Su, M., Chi, M.T.H., & Nagashima, T. (2026). Applying the PAIR-C Framework to foster deep understanding and address misconceptions in science education. Journal of the Learning Sciences, 35(1), 130-175. https://doi.org/10.1080/10508406.2025.2546471
Research data
- Lin, W. M., FitzGibbon, L., Theobald, M., Breitwieser, J., Brod, G., Murayama, K., & Sakaki, M. (2026). The dynamic interplay between goal setting, performance, and emotions in self-regulated learning: A computational modeling approach [Data set]. https://supp.apa.org/psycarticles/supplemental/edu0001022/edu0001022_supp.html
- Sukjaitham, S., Brod, G., Breitwieser, J., & Schaaf, M. (2026). Exploring the feasibility of personalized AI feedback to improve children’s planning skills [Data set]. https://doi.org/10.17605/OSF.IO/4W6RZ
View dataPreregistrationStudy material
- Frick, P., & Schüler, A. (2026). Validation of illustrated texts: Can pictures raise awareness of inconsistencies? [Data set]. https://osf.io/pg67h/
View dataPreregistration 1 | 2 | 3 Study materialCode
- Breitwieser, J., Bittermann, A., Theobald, M., Lauer, T., Schaaf, M., & Brod, G. (2026). Supplementary materials for: Digital prompting in education: A design framework and bibliometric analysis [Data set]. https://doi.org/10.23668/psycharchives.21866
View dataPreregistrationStudy material
- Breitwieser, J., Bittermann, A., Theobald, M., Lauer, T., Schaaf, M., & Brod, G. (2024). A bibliometric analysis of digital prompting interventions in education [Data set]. https://doi.org/10.23668/psycharchives.14126
Other publications
- Breitwieser, J., Bittermann, A., Theobald, M., Lauer, T., Schaaf, M., & Brod, G. (2026). Digital prompting in education: A design framework and bibliometric analysis. Educational Psychology Review, 38(1), 66. https://doi.org/10.1007/s10648-026-10164-1
- Breitwieser, J., Schaaf, M., & Brod, G. (2026). Evidence-based adaptivity decisions for educational interventions. PsyArXiv. https://doi.org/10.31234/osf.io/jrthz_v1
View preprintDataStudy material
- Sukjaitham, S., Schaaf, M., Brod, G., & Breitwieser, J. (2026). Adaptivity makes feedback effective: Evidence from AI-generated feedback on children’s plans. PsyArXiv.
View preprintPreregistrationStudy material
- Lörch, L., & Brod, G. (2026). Intelligent tutoring systems in open-ended, multimodal domains reviewing the evidence from arts, music, and sports. Research Square. https://doi.org/10.21203/rs.3.rs-8797891/v1
- Brod, G. (2026). Agency does not equal choice – conceptualizing agency for learning in the age of AI. Learning and Individual Differences, 125, Article 102841. https://doi.org/10.1016/j.lindif.2025.102841