Publikationen

2026

• Richters, C., Stadler, M., Braun, L., Fischer, M. R., & Heitzmann, N. (2026)

  Learning From Errors in Simulations: How Individual Error Responses Shape Collaborative Problem‐Solving Skills

  Journal of Computer Assisted Learning, 42(3), e70251

  https://onlinelibrary.wiley.com/doi/10.1002/jcal.70251

• Wolf, A., Wachter, H., Rehor, V., Hartmann, C., Michaeli, T., & Bannert, M. (2026)

  Teacher’s Metacognitive Regulation of Diagnostic Reasoning in Video-Based Simulations

  Poster presented at the 12th International Biennial Conference of EARLI SIG 16 Metacognition and Self-Regulated Learning, Clermont-Ferrand, France

  A04

2025

• Bach, K. M., Hofer, S. I., & Bichler, S. (2025)

  Adaptive learning, instruction, and teaching in schools: Unraveling context, sources, implementation, and goals in a systematic review

  Learning and Individual Differences, 124, 102781

  https://www.sciencedirect.com/science/article/pii/S1041608025001578?via%3Dihub

  A05

• Bauer, E., Sailer, M., Niklas, F., Greiff, S., Sarbu-Rothsching, S., Zottmann, J. M., Kiesewetter, J., Stadler, M., Fischer, M. R., Seidel, T., Urhahne, D., Sailer, M., & Fischer, F. (2025)

  AI-Based Adaptive Feedback in Simulations for Teacher Education: An Experimental Replication in the Field

  Journal of Computer Assisted Learning

  https://onlinelibrary.wiley.com/doi/10.1111/jcal.13123

  B04

• Edelsbrunner, P. A., Tetzlaff, L, Bach, K. M., Dumas, D., Hofer, S. I., Köhler, C., Kozlova, Z., Moeller, J., Reinhold, F., Roberts, G. J., Sengewald, M.-A., & Bichler, S. (2025)

  Beyond linear regression: Statistically modeling aptitude-treatment interactions and the differential effectiveness of educational interventions

  Learning and Individual Differences, 124, 102812

  https://www.sciencedirect.com/science/article/pii/S1041608025001888?via%3Dihub

  A05

• Kozlova, Z., Bach, K. M., Edelsbrunner, P. A., & Hofer, S. I. (2025)

  Bringing Learners into Focus: A Systematic Review of Learner Characteristics in AR-Supported STEM Education

  Learning and Individual Differences, 122, 102727

  https://www.sciencedirect.com/science/article/pii/S1041608025001037?via%3Dihub

  A05

• Chernikova, O., Sommerhoff, D., Stadler, M., Holzberger, D., Nickl, M., Seidel, T., Kasneci, E., Küchemann, S., Kuhn, J., Fischer, F. & Heitzmann, N. (2025)

  Personalization through adaptivity or adaptability? A meta-analysis on simulation-based learning in higher education

  Educational Research Review, 46, 100662

  https://doi.org/10.1016/j.edurev.2024.100662

• Bauer, E., Heitzmann, N., Bannert, M., Chernikova, O., Fischer, M., Frenzel, A., Gartmeier, M. Hofer, S., Holzberger, D., Kasneci, E., Koenen, J., Kosel, C., Küchemann, S., Kuhn, J., Michaeli, T., Neuhaus, B., Niklas, F., Obersteiner, A., Pfeffer, J., Sailer, M., Schmidmaier, R., Schmidt-Hertha, B., Stadler, M., Ufer, S., Vorholzer, A., Seidel, T. & Fischer, F. (2025)

  Personalizing simulation-based learning in higher education

  Learning and Individual Differences, 122, 102746

  https://doi.org/10.1016/j.lindif.2025.102746

• Hofer, S. I. & Reinhold, F. (2025)

  Scaffolding of learning activities: Aptitude-treatment-interaction effects in math?

  Learning and Instruction, 99, 102177

  https://www.sciencedirect.com/science/article/pii/S095947522500101X?via%3Dihub

  A05

• Bach, K. M., Reinhold, F., & Hofer, S. I. (2025)

  Unlocking math potential in students from lower SES backgrounds – using instructional scaffolds to improve performance

  Npj Science of Learning, 10(1), 66

  https://www.nature.com/articles/s41539-025-00358-7

  A05

2024

• Wachter, H. & Michaeli, T. (2024)

  Analyzing teachers' diagnostic and intervention processes in debugging using video vignettes

  Proceedings of the 17th International Conference on Informatics in Schools (pp. 1-13). Springer

  https://link.springer.com/chapter/10.1007/978-3-031-73474-8_13

  A04

• Steinert, S., Ruf, V., Dzsotjan, D., Großmann, N., Schmidt, A., Kuhn, J., & Küchemann, S. (2024)

  A refined approach for evaluating small datasets via binary classification using machine learning

  Plos one, 19(5), e0301276

  https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0301276

  A05

• Hou, R., Fütterer, T., Bühler, B., Bozkir, E., Gerjets, P., Trautwein, U., & Kasneci, E. (2024)

  Automated assessment of encouragement and warmth in classrooms leveraging multimodal emotional features and ChatGPT

  The 25th International Conference on Artificial Intelligence in Education (pp. 101–112)

  https://link.springer.com/chapter/10.1007/978-3-031-64302-6_5

  INF

• Machts, N., Chernikova, O., Jansen, T., Weidenbusch, M., Fischer, F., & Möller, J. (2024)

  Categorization of simulated diagnostic situations and the salience of diagnostic information

  Zeitschrift Für Pädagogische Psychologie, 38(1-2), 3–13

  https://econtent.hogrefe.com/doi/10.1024/1010-0652/a000364

  B01

• Brandl, L., Stadler, M., Richters, C., Radkowitsch, A., Fischer, M. R., Schmidmaier, R., & Fischer, F. (2024)

  Collaborative problem-solving in knowledge-rich domains: A multi-study structural equation model

  International Journal of Computer-Supported Collaborative Learning, 19(3), 341-368

  https://link.springer.com/article/10.1007/s11412-024-09425-4

  B01 B02 B05

• Nickl, M., Sommerhoff, D., Radkowitsch, A., Huber, S. A., Bauer, E., Ufer, S., Plass, J. L., & Seidel, T. (2024)

  Effects of real-time adaptivity of scaffolding: Supporting pre-service mathematics teachers’ assessment skills in simulations

  Learning and Instruction, 94, 101994

  https://www.sciencedirect.com/science/article/pii/S095947522400121X?via%3Dihub

  A02

• Frenzel, A. C., Goetz, T., & Stockinger, K. (2024)

  Emotions and emotion regulation

  In P. Schutz & K. R. Muis (Eds.), Handbook of Educational Psychology (4 ed., pp. 219-244). New York, NY: Routledge

  C06

• Hartl, A., Starke, E., Voggenreiter, A., Holzberger, D., Michaeli, T., & Pfeffer, J. (2024)

  Empowering Digital Natives: InstaClone - A Novel Approach to Data Literacy Education in the Age of Social Media

  Proceedings of the 55th ACM Technical Symposium on Computer Science Education, (pp 484–490). ACM.

  https://dl.acm.org/doi/10.1145/3626252.3630839

  A04

• Jang, W., Gao, H., Michaeli, T., & Kasneci, E. (2024)

  Exploring Communication Dynamics: Eye-tracking Analysis in Pair Programming of Computer Science Education

  Proceedings of the 2024 Symposium on Eye Tracking Research and Applications (pp. 1-7). ACM.

  https://dl.acm.org/doi/10.1145/3649902.3653942

  A04

• Richters, C., Stadler, M., Radkowitsch, A., Behrmann, F., Weidenbusch, M., Fischer, M. R., Schmidmaier, R., & Fischer, F. (2024)

  Fostering collaboration in simulations: How advanced learners benefit from collaboration scripts and reflection

  Learning and Instruction, 93, 101912

  https://www.sciencedirect.com/science/article/abs/pii/S0959475224000392?via%3Dihub

  A01 B02

• Brunner, K., Obersteiner, A., & Leuders, T. (2024)

  How pedagogical content knowledge sharpens prospective teachers’ focus when judging mathematical tasks: an eye-tracking study

  Educational Studies in Mathematics, 115(2), 177-196

  https://link.springer.com/article/10.1007/s10649-023-10281-6

  A03 A06

• Richters, C., Schmidmaier, R., Popov, V., Schredelseker, J., Fischer, F., & Fischer, M. R. (2024)

  Intervention skills – A neglected field of research in medical education and beyond

  GMS Journal of Medical Education, 41(4), Doc48.

  https://journals.publisso.de/en/journals/jme/volume41/zma001703

  A01 B01

• Kasneci, E., Gao, H., Özdel, S., Maquiling, V., Thaqi, E., Lau, C., Rong, Y., Kasneci, G., & Bozkir, E. (2024)

  Introduction to eye tracking: A hands-on tutorial for students and practitioners

  arXiv

  https://arxiv.org/abs/2404.15435

  INF

• Janssen, L., Schick, K., Neurohr, T., Pitroff, S. I. D., Reiser, S., Bauer, J., Berberat, P. O., & Gartmeier, M. (2024)

  Reflect to interact – Fostering medical students' communication through reflection-focused e-learning

  BMC Medical Education, 24(541), 1-11

  https://link.springer.com/article/10.1186/s12909-024-05368-4

  C03

• Farrell, M., Martin, M., Böheim, R., Renkl, A., Rieß, W., Könings, K. D., van Merriënboer, J. J., & Seidel, T. (2024)

  Signaling cues and focused prompts for professional vision support: The interplay of instructional design and situational interest in preservice teachers’ video analysis

  Instructional Science, 1-39

  https://link.springer.com/article/10.1007/s11251-024-09662-y

  C03

• Sailer, M., Ninaus, M., Huber, S. E., Bauer, E., & Greiff, S. (2024)

  The End is the Beginning is the End: The closed-loop learning analytics framework

  Computers in Human Behavior, Article 108305

  https://www.sciencedirect.com/science/article/pii/S0747563224001730?via%3Dihub

  B04

• Holzberger, D., Brandl, L., Stadler, M., Obersteiner, A., Chernikova, O., Pickal, A. J., Nickl, M., Richters, C., Kron, S., Wecker, C., Heitzmann, N., Irmer, M., Corves, C., Radkowitsch, A., Neuhaus, B. J., Fischer, M. R., Ufer, S., Fischer, F., Sommerhoff, D., Seidel, T. (2024)

  The interplay between expectancy and value and its generalizability across simulation-based learning environments: An individual participant data meta-analysis

  Registered Report in Journal of Educational Psychology

  B05

• Chernikova, O., Stadler, M., Sommerhoff, D., Schons, C., Heitzmann, N., Holzberger, D., Seidel, T. Richters, C., Pickal, A.J., Wecker, C., Nickl, M., Codreanu, E., Ufer, S., Kron, S., Corves, C., Neuhaus, B.J., Fischer, M.R., & Fischer, F. (2024)

  The relation between learners’ experience in simulations and diagnostic accuracy: Generalizability across medical and teacher education

  Computers in Human Behavior Reports, (4), 100454

  https://www.sciencedirect.com/science/article/pii/S2451958824000873?via%3Dihub

  M

• Schons, C., Obersteiner, A., Fischer, F., & Reiss, K. (2024)

  Toward adaptive support of pre-service teachers' assessment competencies: Log data in a digital simulation reveal engagement modes

  Learning and Instruction, 94, 101979

  https://www.sciencedirect.com/science/article/pii/S0959475224001063?via%3Dihub

  A03

• Schick, K., Reiser, S., Janssen, L., Schacht, L., Pittroff, S. I. D., Dörfler, E., Klein, E., Roenneberg, C., Dinkel, A., & Fleischmann, A., Berberat, P. O., Bauer, J. & Gartmeier, M. (2024)

  Training in medical communication competence through video-based e-learning: How effective are video modeling and video reflection?

  Patient Education and Counseling, 121, 108132

  https://www.sciencedirect.com/science/article/abs/pii/S073839912300513X?via%3Dihub

  C03

• Graichen, M., Mikelskis-Seifert, S., Hinderer, L., Scharenberg, K.,& Rollett, W. (2024)

  Unveiling Potential: Fostering Students’ Self Concepts in Science Education by Designing Inclusive Educational Settings

  Education Sciences, 14(6), 632

  https://www.mdpi.com/2227-7102/14/6/632

  B06

• Chernikova, O., Stadler, M., Melev, I., & Fischer, F. (2024)

  Using machine learning for continuous updating of meta-analysis in educational context

  Computers in Human Behavior, 156, 108215

  https://www.sciencedirect.com/science/article/pii/S0747563224000839?via%3Dihub

  M

• Stadler, M., Pickal, A. J., Brandl, L., & Krieger, F. (2024)

  VOTAT in Action

  Zeitschrift Für Psychologie, 232(2), 109–119

  https://econtent.hogrefe.com/doi/10.1027/2151-2604/a000559

  A06

• Kosel, C., Bauer, E., & Seidel, T. (2024)

  Where experience makes a difference: teachers’ judgment accuracy and diagnostic reasoning regarding student learning characteristics

  Frontiers in Psychology, 15

  https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2024.1278472/full

  C01

• Chernikova, O., Holzberger, D., Heitzmann, N., Stadler, M., Seidel, T., & Fischer, F. (2024)

  Where salience goes beyond authenticity

  Zeitschrift für Pädagogische Psychologie, 38(1-2), 15–25

  https://econtent.hogrefe.com/doi/10.1024/1010-0652/a000357

  B01

2023

• Stadler, M., Brandl, L., & Greiff, S. (2023)

  20 years of interactive tasks in large‐scale assessments: Process data as a way towards sustainable change?

  Journal of Computer Assisted Learning, 39(6), 1852-1859

  https://onlinelibrary.wiley.com/doi/10.1111/jcal.12847

  INF M

• Sailer, M., Bauer, E., Hofmann, R., Kiesewetter, J., Glas, J., Gurevych, I., & Fischer, F. (2023)

  Adaptive feedback from artificial neural networks facilitates pre-service teachers’ diagnostic reasoning in simulation-based learning

  Learning and Instruction, Article 101620

  https://www.sciencedirect.com/science/article/pii/S095947522200041X?via%3Dihub

  B04

• Ruf, V., Horrer, A., Berndt, M., Hofer, S. I., Fischer, F., Fischer, M. R., Zottmann, J., Kuhn, J., & Küchemann, S. (2023)

  A literature review comparing experts’ and non-experts’ visual processing of graphs during problem-solving and learning

  Education Sciences, 13(2), 1-19

  https://www.mdpi.com/2227-7102/13/2/216

  C02

• Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., Stadler, M., ... & Kasneci, G (2023)

  ChatGPT for good? On opportunities and challenges of large language models for education

  Learning & Individual Differences, 103, 102274

  https://www.sciencedirect.com/science/article/abs/pii/S1041608023000195?via%3Dihub

  INF

• Schons, C., Obersteiner, A., Reinhold, F., Fischer, F., & Reiss, K. (2023)

  Developing a Simulation to Foster Prospective Mathematics Teachers' Diagnostic Competencies: The Effects of Scaffolding

  Journal für Mathematik-Didaktik, 44(1), 59–82

  https://doi.org/10.1007/s13138-022-00210-0

  A06 A03

• Fink, M. C., Heitzmann, N., Reitmeier, V., Siebeck, M., Fischer, F., & Fischer, M. R. (2023)

  Diagnosing virtual patients: The interplay between knowledge and diagnostic activities

  Advances in Health Sciences Education, 28(4), 1245-1264

  https://link.springer.com/article/10.1007/s10459-023-10211-4

  A01

• Kieser, F., Wulff, P., Kuhn, J., & Küchemann, S. (2023)

  Educational data augmentation in physics education research using ChatGPT

  Physical Review Physics Education Research, 19, 1-13

  https://journals.aps.org/prper/abstract/10.1103/PhysRevPhysEducRes.19.020150

  C02

• Lim, L., Bannert, M., van der Graaf, J., Singh, S., Fan, Y., Surendrannair, S., Rakovic, M., Molenaar, I., Moore, J., & Gašević, D. (2023)

  Effects of real-time analytics-based personalized scaffolds on students’ self-regulated learning

  Computers in Human Behavior, 139, Article 107547

  https://www.sciencedirect.com/science/article/pii/S0747563222003673?via%3Dihub

  A04 C01

• Radkowitsch, A., Sommerhoff, D., Nickl, M., Codreanu, E., Ufer, S., & Seidel, T. (2023)

  Exploring the diagnostic process of pre-service teachers using a simulation – A latent profile approach

  Teaching and Teacher Education, 130, 104172

  https://www.sciencedirect.com/science/article/pii/S0742051X23001609?via%3Dihub

  C04

• Kosel, C., Böheim, R., Schnitzler, K., Holzberger, D., Pfeffer, J., Bannert, M., & Seidel, T. (2023)

  Keeping track in classroom discourse: Comparing in-service and pre-service teachers' visual attention to students’ hand-raising behavior

  Teaching and Teacher Education, 128, 104142

  https://www.sciencedirect.com/science/article/pii/S0742051X23001300?via%3Dihub

  C01

• Heitzmann, N., Stadler, M., Richters, C., Radkowitsch, A., Schmidmaier, R., Weidenbusch, M., & Fischer, M. R. (2023)

  Learners’ adjustment strategies following impasses in simulations—Effects of prior knowledge

  Learning and Instruction, 83, 1-11, 101632

  https://doi.org/10.1016/j.learninstruc.2022.101632

  B03 C02

• Schadl, C., & Ufer, S. (2023)

  Mathematical knowledge and skills as longitudinal predictors of fraction learning among sixth-grade students

  Journal of Educational Psychology, 115(7), 985-1003

  https://psycnet.apa.org/fulltext/2024-00277-001.html

  A02

• Molenaar, I., de Mooij, S., Azevedo, R., Bannert, M., Järvelä, S., & Gasevic, D. (2023)

  Measuring self-regulated learning and the role of AI: Five years of research using multimodal multichannel data

  Computers in Human Behavior, 139, 107540

  https://www.sciencedirect.com/science/article/pii/S0747563222003600?via%3Dihub

  B02

• Kosel, C., Voggenreiter, A., Pfeffer, J., & Seidel, T. (2023)

  Measuring teachers’ visual expertise using the gaze relational index based on real-world eyetracking data and varying velocity thresholds

  Journal of Expertise, 6(3), 267-281

  https://arxiv.org/abs/2304.05143

  A04 C01

• Daumiller, M., Janke, S., Butler, R., Dickhäuser, O., & Dresel, M. (2023)

  Merits and limitations of latent profile approaches to teachers’ achievement goals: A multi-study analysis

  PLoS ONE, 18(4), Article e0284608

  https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0284608

  M

• Becker, S., Knippertz, L., Ruzika, S., & Kuhn, J. (2023)

  Persistence, context, and visual strategy of graph understanding: Gaze patterns reveal student difficulties in interpreting graphs

  Physical Review Physics Education Research, 19(2), 1-12

  https://journals.aps.org/prper/abstract/10.1103/PhysRevPhysEducRes.19.020142

  C02

• Sommerhoff, D., Codreanu, E., Nickl, M., Ufer, S., & Seidel, T. (2023)

  Pre-service teachers’ learning of diagnostic skills in a video-based simulation: Effects of conceptual vs. interconnecting prompts on judgment accuracy and the diagnostic process

  Learning and Instruction, 83, 101689

  https://www.sciencedirect.com/science/article/pii/S0959475222001104?via%3Dihub

  A02

• Hammer, S., & Ufer, S. (2023)

  Professional competence of mathematics teachers in dealing with tasks in lesson planning

  Teaching and Teacher Education, 132, 104246

  https://www.sciencedirect.com/science/article/pii/S0742051X23002342?via%3Dihub

  A02

• Edelsbrunner, P. A., Malone, S., Hofer, S. I., Küchemann, S., Kuhn, J., Schmid, R., ... & Lichtenberger, A. (2023)

  The relation of representational competence and conceptual knowledge in female and male undergraduates

  International Journal of STEM Education, 10(1), 44

  https://doi.org/10.1186/s40594-023-00435-6

  A05

• Gegenfurtner, A., Gruber, H., Holzberger, D., Keskin, Ö., Lehtinen, E., Seidel, T., Stürmer, K., & Säljö, R. (2023)

  Towards a cognitive theory of visual expertise

  Re-theorizing learning and research methods in learning research (pp. 146-163). Routledge

  https://www.taylorfrancis.com/chapters/edit/10.4324/9781003205838-10/towards-cognitive-theory-visual-expertise-andreas-gegenfurtner-hans-gruber-doris-holzberger-%C3%B6z%C3%BCn-keskin-erno-lehtinen-tina-seidel-kathleen-st%C3%BCrmer-roger-s%C3%A4lj%C3%B6

  C01

• Rong, Y., Leemann, T., Nguyen, T., Fiedler, L., & Qian, P. (2023)

  Towards human-centered explainable AI: A survey of user studies for model explanations

  IEEE Transactions on Pattern Analysis and Machine Intelligence, 46, 2104–2122

  https://ieeexplore.ieee.org/document/10316181

  INF

• Bauer, E., Greisel, M., Kuznetsov, I., Berndt, M., Kollar, I., Dresel, M., Fischer, M. R., & Fischer, F. (2023)

  Using natural language processing to support peer‐feedback in the age of artificial intelligence: A cross‐disciplinary framework and a research agenda

  British Journal of Educational Technology, 54(5), 1222–1245

  https://bera-journals.onlinelibrary.wiley.com/doi/10.1111/bjet.13336

  B01

• Irmer, M., Traub, D., Böhm, M., Förtsch, C., & Neuhaus, B. J. (2023)

  Using Video-Based Simulations to Foster pPCK/ePCK—New Thoughts on the Refined Consensus Model of PCK

  Education Sciences, 13(3), 261

  https://www.mdpi.com/2227-7102/13/3/261

  A02 C04 C05 C06

• Von Wachter, J. & Lewalter, D. (2023)

  Video annotation as a supporting tool for video-based learning in Teacher Training: A systematic literature review

  International Journal of Higher Education, 12(2)

  https://www.sciedupress.com/journal/index.php/ijhe/article/view/23002

  C06

• Richters, C., Stadler, M., Radkowitsch, A., Schmidmaier, R., Fischer, M. R., & Fischer, F. (2023)

  Who is on the right track? Behavior-based prediction of diagnostic success in a collaborative diagnostic reasoning simulation

  Large-Scale Assessments in Education, 11(1), Article 3

  https://link.springer.com/article/10.1186/s40536-023-00151-1

  B01 INF M

2022

• Vogel, F., Kollar, I., Fischer, F., Reiss, K. & Ufer, S. (2022)

  Adaptable scaffolding of mathematical argumentation skills: The role of self-regulation when scaffolded with CSCL scripts and heuristic worked examples

  International Journal of Computer-Supported Collaborative Learning, 17, 39–64

  https://link.springer.com/article/10.1007/s11412-022-09363-z

  B04

• Farrell, M., Martin, M., Renkl, A., Rieß, W., Könings, K. D., van Merriënboer, J. J. G., & Seidel, T. (2022)

  An epistemic network ap-proach to teacher students’ professional vision in tutoring video analysis

  Frontiers in Education, 7

  https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2022.805422/full

  C01

• Kron, S., Sommerhoff, D., Achtner, M., Stürmer, K., Wecker, C., Siebeck, M., & Ufer, S. (2022)

  Cognitive and Motivational Person Characteristics as Predictors of Diagnostic Performance: Combined Effects on Pre-Service Teachers’ Diagnostic Task Selection and Accuracy

  Journal Für Mathematik-Didaktik, 43(1), 135–172

  https://doi.org/10.1007/s13138-022-00200-2

  B03 A02 B04 C04

• Knogler, M., Hetmanek, A., & Seidel, T. (2022)

  Determining an Evidence Base for Particular Fields of Educational Practice: A Systematic Review of Meta-Analyses on Effective Mathematics and Science Teaching [Systematic Review]

  Frontiers in Psychology, 13

  https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2022.873995/full

  M

• Seidel, T., Farell, M., Martin, M., Rieß, W., & Renkl, A. (2022)

  Developing Scripted Video Cases for Teacher Education: Creating Evidence-based Practice Representations Using Mock Ups

  Frontiers in Education. Advance online publication

  https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2022.965498/full

  C04

• Bauer, E., Sailer, M., Kiesewetter, J., Fischer, M. R., & Fischer, F. (2022)

  Diagnostic argumentation in teacher education: Making the case for justification, disconfirmation, and transparency

  Frontiers in Education, 7, 977631

  https://doi.org/10.3389/feduc.2022.977631

  A02

• Vorholzer, A., Petermann, V., Weber, J., Belzen, A. U. zu, & Tiemann, R. (2022)

  Explicit instruction on procedural and epistemic knowledge – is it happening? A video-based exploration of classroom practice

  Research in Science & Technological Education, 1–20

  https://www.tandfonline.com/doi/full/10.1080/02635143.2022.2153245

  C04 C05

• Soellner, N., Eiberle, M., Berberat, P., Schulz, C., Hinzmann, D., Rath, S., Haseneder, R., & Gartmeier, M. (2022)

  Just showing is not enough: First-person-view-videos as a feedback tool in resuscitation simulation

  Studies in Educational Evaluation, 72, 101100

  https://www.sciencedirect.com/science/article/abs/pii/S0191491X21001267?via%3Dihub

  B05 C03

• Wildgans-Lang, A., Scheuerer, S., Obersteiner, A., Fischer, F., & Reiss, K. (2022)

  Learning to diagnose primary students’ mathematical competence levels and misconceptions in document-based simulations

  F. Fischer & A. Opitz (Eds.), Learning to Diagnose with Simulations. Springer International Publishing

  A06

• Hachinger, S., Golasowski, M., Martinovič, J., Hayek, M., García-Hernández, R. J., Slaninová, K., Levrier, M., Scionti, A., Donnat, F., Vitali, G., Magarielli, D., Goubier, T., Parodi, A., Harsh, P., Dees, A., & Terzo, O. (2022)

  Leveraging high-performance computing and cloud computing with unified big-data workflows: The LEXIS project

  E. Curry, S. Auer, A. J. Berre, A. Metzger, M. S. Perez, & S. Zillner (Eds.), Technologies and Applications for Big Data Value (pp. 105–127). Springer, Cham

  https://link.springer.com/chapter/10.1007/978-3-030-78307-5_8

  INF

• Rott, K.J., Lao, L., Petridou, E., & Schmidt-Hertha, B. (2022)

  Needs and requirements for an additional AI qualification during dual vocational training: Results from studies of apprentices and teachers

  Computers and Education: Artificial Intelligence, 100102

  https://www.sciencedirect.com/science/article/pii/S2666920X22000571?via%3Dihub

  B06

• Petermann, V., & Vorholzer, A. (2022)

  Relationship between beliefs of teachers about and their use of explicit instruction when fostering students’ scientific inquiry competencies

  Education Sciences, 12(9)

  https://www.mdpi.com/2227-7102/12/9/593

  C05

• Fischer, F., Bauer, E., Seidel, T., Schmidmaier, R., Radkowitsch, A., Neuhaus, B. J., Hofer, S. I., Sommerhoff, D., Ufer, S., Kuhn, J., Küchemann, S., Sailer, M., Koenen, J., Gartmeier, M., Berberat, P., Frenzel, A., Heitzmann, N., Holzberger, D., Pfeffer, J., … Fischer, M. R. (2022)

  Representational scaffolding in digital simulations – Learning professional practices in higher education

  Information and Learning Sciences, 123(11/12), 645–665

  https://www.emerald.com/ils/article-abstract/123/11-12/645/169905/Representational-scaffolding-in-digital?redirectedFrom=fulltext

  A01 A02 B05 M C03

• Irmer, M., Traub, D., Kramer, M., Förtsch, C., & Neuhaus, B. J. (2022)

  Scaffolding Pre-service Biology Teachers’ Diagnostic Competences in a Video-based Learning Environment: Measuring the Effect of Different Types of Scaffolds

  International Journal of Science Education, 44(9), 1506–1526

  https://www.tandfonline.com/doi/full/10.1080/09500693.2022.2083253

  C04

• Behling, F., Förtsch, C., & Neuhaus, B. J. (2022)

  The Refined Consensus Model of Pedagogical Content Knowledge (PCK): Detecting Filters between the Realms of PCK

  Education Sciences, 12(9), 592-612

  https://www.mdpi.com/2227-7102/12/9/592

  C04

• Magraw-Mickelson, Z., Süssenbach, P., & Gollwitzer, M. (2022)

  The virus of distrust: How one victim-sensitive group member can affect the entire group’s outcomes

  European Journal of Social Psychology, 52(3), 487-499

  https://onlinelibrary.wiley.com/doi/10.1002/ejsp.2832

  B05

• Tausendfreund, O., Braun, L.T., & Schmidmaier, R. (2022)

  Types of therapeutic errors in the management of osteoporosis made by physicians and medical students

  BMC Medical Education, 22, 323

  https://link.springer.com/article/10.1186/s12909-022-03384-w

  B02

• Laybourn, S., Frenzel, A. C., Constant, M., & Liesefeld, H. R. (2022)

  Unintended emotions in the laboratory: Emotions incidentally induced by a standard visual working memory task relate to task performance

  Journal of Experimental Psychology: General, 151(7), 1591-1605

  https://psycnet.apa.org/doiLanding?doi=10.1037%2Fxge0001147

  C06

• Raković, M., Fan, Y., van der Graaf, J., Singh, S., Kilgour, J., Lim, L., Moore, J., Bannert, M., Molenaar, I., & Gašević, D. (2022)

  Using learner trace data to understand metacognitive processes in writing from multiple sources

  A. Wise et al. (Eds.), Companion Proceedings of the 12th International Conference on Learning Analytics & Knowledge (pp. 130-141)

  https://dl.acm.org/doi/10.1145/3506860.3506876

  A04

• Von Wachter, J., Lewalter, D., & Frenzel, A. C. (2022)

  Videoannotationen als Tool zur Unterstützung von Unterrichtsreflexionen – Effekte und Grenzen

  Poster auf der 52. DGPs-Tagung Hildesheim

  C06

• Berner, V.-D., Segerer, R., Oesterlen, E., Seitz-Stein, K., & Niklas, F. (2022)

  “Good” or “well calculated”? Effects of feedback on performance and self-concept of 5- to 7-year-old children in math

  Educational Psychology, 42(3), 296-315

  https://www.tandfonline.com/doi/full/10.1080/01443410.2021.2001790

  B04

2021

• Krieger, F., Stadler, M., Bühner, M., Fischer, F., & Greiff, S. (2021)

  Assessing Complex Problem-Solving Skills in Under 20 Minutes

  Psychological Test Adaptation and Development, 2(1), 80–92

  https://econtent.hogrefe.com/doi/10.1027/2698-1866/a000009

  A06

• Fink, M. C., Reitmeier, V., Stadler, M., Siebeck, M., Fischer, F., & Fischer, M. R. (2021)

  Assessment of diagnostic competencies with standardized patients versus virtual patients: Experimental study in the context of history taking

  Journal of Medical Internet Research, 23(3), Article e21196

  https://www.jmir.org/2021/3/e21196

  A01

• Kramer, M., Förtsch, C., & Neuhaus, B. J. (2021)

  Can Pre-Service Biology Teachers’ Professional Knowledge and Diagnostic Activities Be Fostered by Self-Directed Knowledge Acquisition via Texts?

  Education Sciences, 11(5), 244

  https://www.mdpi.com/2227-7102/11/5/244

  C04

• Kramer, M., Förtsch, C., Seidel, T., & Neuhaus, B. J. (2021)

  Comparing two constructs for describing and analyzing teachers’ diag-nostic processes

  Studies in Educational Evaluation, 68, 100973

  https://www.sciencedirect.com/science/article/abs/pii/S0191491X20302212?via%3Dihub

  A02

• Sailer, M., Schultz-Pernice, F., & Fischer, F. (2021)

  Contextual facilitators for learning activities involving technology in higher education: The C♭-model

  Computers in Human Behavior, 121, 106794

  https://www.sciencedirect.com/science/article/pii/S0747563221001175?via%3Dihub

  B06

• Gao, H., Bozkir, E., Hasenbein, J., Göllner R., & Kasneci, E. (2021)

  Digital transformations of classrooms in virtual reality

  Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, 1–10

  https://dl.acm.org/doi/10.1145/3411764.3445596

  INF

• Küchemann, S., Becker, S., Klein, P., & Kuhn, J. (2021)

  Gaze-based prediction of students' understanding of physics line-graphs: An eye-tracking-data based machine-learning approach

  H. C. Lane, S. Zvacek & J. Uhomoibhi J. (Eds.), CSEDU 2020. Communications in Computer Information Sciences (pp. 450-467). Springer

  https://link.springer.com/chapter/10.1007/978-3-030-86439-2_23

  A05 C02

• Kosel, C., Holzberger, D., & Seidel, T. (2021)

  Identifying expert and novice visual scanpath patterns and their relationship to assessing learning-relevant student characteristics

  Frontiers in Education, 5

  https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2020.612175/full

  C03

• Küchemann, S., Malone, S., Edelsbrunner, P., Lichtenberger, A., Stern, E., Schumacher, R., ... & Kuhn, J. (2021)

  Inventory for the assessment of representational competence of vector fields

  Physical Review Physics Education Research, 17(2), 020126

  https://journals.aps.org/prper/abstract/10.1103/PhysRevPhysEducRes.17.020126

  A05

• Kramer, M., Förtsch, C., Boone, W. J., Seidel, T., & Neuhaus, B. J. (2021)

  Investigating pre-service biology teachers’ diagnostic competences: relationships between professional knowledge, diagnostic activities, and diagnostic accuracy

  Education Sciences, 11(3), 89

  https://www.mdpi.com/2227-7102/11/3/89

  C05

• Fink, M. C., Heitzmann, N., Siebeck, M., Fischer, F., & Fischer, M. R. (2021)

  Learning to diagnose accurately through virtual patients: Do reflection phases have an added benefit?

  BMC Medical Education, 21(1), 523

  https://doi.org/10.1186/s12909-021-02937-9

  B03

• Radkowitsch, A., Sailer, M., Schmidmaier, R., Fischer, M. R., & Fischer, F. (2021)

  Learning to diagnose collaboratively – Effects of adaptive collaboration scripts in agent-based medical simulations

  Learning and Instruction, 75, 101487

  https://www.sciencedirect.com/science/article/pii/S0959475221000463?via%3Dihub

  B01 B02 B05

• Sümer, Ö., Goldberg, P., D'Mello, S., Gerjets, P., Trautwein, U., & Kasneci, E. (2021)

  Multimodal engagement analysis from facial videos in the classroom

  IEEE Transactions on Affective Computing, 14(2)

  https://ieeexplore.ieee.org/document/9613750

  INF

• Hofer, S. I., Nistor, N., & Scheibenzuber, C. (2021)

  Online teaching and learning in higher education: Lessons learned in crisis situations

  Computers in Human Behavior, 121, 106789

  https://www.sciencedirect.com/science/article/pii/S0747563221001126?via%3Dihub

  A05

• Grub, A.-S., Biermann, A., Lewalter, D., & Brünken, R. (2021)

  Professional knowledge and task instruction specificity as influencing factors of prospective teachers' professional vision

  Teaching and Teacher Education, 109, Article 103517

  https://www.sciencedirect.com/science/article/abs/pii/S0742051X21002420

  C06

• Holzberger, D., Maurer, C., Kunina-Habenicht, O., & Kunter, M. (2021)

  Ready to teach? A profile analysis on cognitive and motivational-affective teacher characteristics at the end of pre-service teacher education and long-term effects on teachers’ occupational well-being

  Teaching and Teacher Education, 100, Article 103285

  https://www.sciencedirect.com/science/article/abs/pii/S0742051X21000093?via%3Dihub

  B05 M

• Brandl, L., Richters, C., Radkowitsch, A., Obersteiner, A., Fischer, M. R., Schmidmaier, R., Fischer, F., & Stadler, M. (2021)

  Simulation-based learning of complex skills: predicting performance with theoretically derived process features

  Psychological Test and Assessment Modeling, 63(4), 542–560

  https://www.psychologie-aktuell.com/fileadmin/Redaktion/Journale/ptam-2021-4/PTAM__4-2021_6_kor.pdf

  A03 A06

• Seidel, T., Schnitzler, K., Kosel, C., Stürmer, K., & Holzberger, D. (2021)

  Student characteristics in the eyes of teachers: Differences between novice and expert teachers in judgment accuracy, observed behavioral cues, and gaze

  Educational Psychology Review, 33(1), 69-89

  https://link.springer.com/article/10.1007/s10648-020-09532-2

  A04 C01

• Frenzel, A. C., Daniels, L., & Buric, I. (2021)

  Teacher emotions and their impact on student outcomes

  Educational Psychologist, 56(4), 250-264

  https://www.tandfonline.com/doi/full/10.1080/00461520.2021.1985501

  C06

• Holzberger, D., & Prestele, E. (2021)

  Teacher self-efficacy and self-reported cognitive activation and classroom management: A multilevel perspective on the role of school characteristics

  Learning and Instruction, 76, Article 101513

  https://www.sciencedirect.com/science/article/abs/pii/S0959475221000724?via%3Dihub

  B05

• Järvelä, S., & Bannert, M. (2021)

  Temporal and adaptive process of regulated learning – what can multimodal data tell?

  Learning and Instruction, 72

  https://www.sciencedirect.com/science/article/abs/pii/S0959475219307388?via%3Dihub

  A04

• Stadler, M., Iliescu, D., & Greiff, S. (2021)

  Validly authentic: Some recommendations to researchers using simulations in psychological assessment [Editorial]

  European Journal of Psychological Assessment, 37(6), 419–422

  https://econtent.hogrefe.com/doi/10.1027/1015-5759/a000686

  INF

• Gollwitzer, M., Magraw-Mickelson, Z., Vollan, B., & Süssenbach, P. (2021)

  Victim sensitivity in groups: When is one a detriment to all?

  Journal of Theoretical Social Psychology, 5(1), 3-13

  https://onlinelibrary.wiley.com/doi/10.1002/jts5.76

  B05

2020

• Codreanu, E., Sommerhoff, D., Huber, S., Ufer, S., Seidel, T. (2020)

  Between authenticity and cognitive demand: Finding a balance in designing a video-based simulation in the context of mathematics teacher education

  Teaching and Teacher Education, 95, Article 103146

  https://www.sciencedirect.com/science/article/pii/S0742051X20313378?via%3Dihub

  B04

• Brückner, S., Zlatkin-Troitschanskaia, O., Küchemann, S., Klein, P., & Kuhn, J. (2020)

  Changes in Students’ Understanding of and Visual Attention on Digitally Represented Graphs Across Two Domains in Higher Education: A Postreplication Study

  Frontiers in Psychology, 11

  https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2020.02090/full

  A03 C02

• Küchemann, S., Klein, P., Becker, S., Kumari, N., & Kuhn, J. (2020)

  Classification of students’ conceptual understanding in STEM education using their visual attention distributions: a comparison of three machine-learning approaches

  Proceedings of the 12th International Conference on Computer Supported Education (Vol. 1, pp. 36–46). SciTePress

  https://www.scitepress.org/Link.aspx?doi=10.5220/0009359400360046

  A03

• Bauer, E., Fischer, F., Kiesewetter, J., Shaffer, D. W., Fischer, M. R., Zottmann, J. M., & Sailer, M. (2020)

  Diagnostic activities and diagnostic practices in medical education and teacher education: an interdisciplinary comparison

  Frontiers in Psychology, 11, Article 562665

  https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2020.562665/full

  A01

• Reinhold, F., Hofer, S. I., Hoch, S., Werner, B., Richter-Gebert, J., & Reiss, K. (2020)

  Digital support principles for sustained mathematics learning in disadvantaged students

  Plos one, 15(10), e0240609

  https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0240609

  A05

• Jünger, J., Pante, S.V., Ackel-Eisnach, K., Wagener, S., & Fischer, M.R. (2020)

  Do it together! Conception and long-term results of the trans-institutional Master of Medical Education (MME) program in Germany

  GMS Journal for Medical Education, 37(3), Doc33

  https://doi.org/10.3205/zma001326

  B06

• Strohmaier, A. R., MacKay, K. J., Obersteiner, A., & Reiss, K. M. (2020)

  Eye-tracking methodology in mathematics education research: A systematic literature review

  Educational Studies in Mathematics, 104(2), 147-200

  https://link.springer.com/article/10.1007/s10649-020-09948-1

  A03

• Chernikova, O., Heitzmann, N., Fink, M., Timothy, V., Seidel, T., & Fischer, F. (2020)

  Facilitating Diagnostic Competences in Higher Education—A Meta-analysis in Medical and Teacher Education

  Educational Psychology Review, 32(1), 157–196. (joint fist authorship)

  https://doi.org/10.1007/s10648-019-09492-2

  B03

• Stadler, M., Hofer, S., & Greiff, S. (2020)

  First among equals: Log data indicates ability differences despite equal scores

  Computers in Human Behavior, 111, 106442

  https://www.sciencedirect.com/science/article/abs/pii/S0747563220301953?via%3Dihub

  A03 A06 M

• Vorholzer, A., von Aufschnaiter, C., & Boone, W. J. (2020)

  Fostering upper secondary students’ ability to engage in practices of scientific investigation: a comparative analysis of an explicit and an implicit instructional approach

  Research in Science Education, 50(1), 333–359

  https://link.springer.com/article/10.1007/s11165-018-9691-1

  C05

• Kyaruzi, F., Strijbos, J.-W., & Ufer, S. (2020)

  Impact of a Short-Term Professional Development Teacher Training on Students’ Perceptions and Use of Errors in Mathematics Learning

  Frontiers in Education, 5

  https://www.frontiersin.org/article/10.3389/feduc.2020.559122

  B03

• Grünewald, M., Klein, E., Hapfelmeier, A., Berberat, P. O., & Gartmeier, M. (2020)

  Improving physicians' surgical ward round competence through simulation-based training

  Patient Education and Counseling, 103(5), 971-977

  https://www.sciencedirect.com/science/article/abs/pii/S0738399119305415?via%3Dihub

  C03

• Vorholzer, A., Hägele, J. J., & von Aufschnaiter, C. (2020)

  Instruktionen kohärent anlegen und Kompetenzaufbau untersuchen: Zugänge und Herausforderungen am Beispiel experimentbezogener Kompetenz

  Unterrichtswissenschaft, 48(1), 61–89

  https://link.springer.com/article/10.1007/s42010-019-00064-5

  C05

• Kiesewetter, J., Sailer, M., Jung, V.M., Schönberger, R., Bauer, E., Zottmann, JM., Hege, I., Zimmermann, H., Fischer, F., & Fischer, M.R. (2020)

  Learning clinical reasoning: how virtual patient case format and prior knowledge interact

  BMC Medical Education, 20(1), 73

  https://link.springer.com/article/10.1186/s12909-020-1987-y

  B06

• Radkowitsch, A., Fischer, M. R., Schmidmaier, R., & Fischer, F. (2020)

  Learning to diagnose collaboratively: validating a simulation for medical students

  GMS Journal for Medical Education, 37(5)

  https://journals.publisso.de/en/journals/jme/volume37/zma001344

  B01

• Kramer, M., Förtsch, C., Stürmer, J., Förtsch, S., Seidel, T., & Neuhaus, B. J. (2020)

  Measuring Biology Teachers’ Professional Vision: Development and Validation of a Video-based Assessment Tool

  Cogent Education, 7, Article 1823155

  https://www.tandfonline.com/doi/full/10.1080/2331186X.2020.1823155

  C04 C05

• Chernikova, O., Heitzmann, N., Stadler, M., Holzberger, D., Seidel, T., & Fischer, F. (2020)

  Simulation-based learning in higher education: A meta-analysis

  Review of Educational Research, 90(4), 499-541

  https://journals.sagepub.com/doi/10.3102/0034654320933544

  B03 B05 C02

• Küchemann, S., Klein, P., Fouckhardt, H., Gröber, S., & Kuhn, J. (2020)

  Students’ understanding of non-inertial frames of reference

  Physical Review Physics Education Research, 16(1), 010112

  https://journals.aps.org/prper/abstract/10.1103/PhysRevPhysEducRes.16.010112

  A05

• Stadler, M., Radkowitsch, A., Schmidmaier, R., Fischer, M. R., & Fischer, F. (2020)

  Take your time: Invariance of timeon-task in problem solving tasks across expertise levels

  Psychological Test and Assessment Modeling, 65(4), 415–525

  A06

• Gegenfurtner, A., Lewalter, D., Lehtinen, E., Schmidt, M., & Gruber, H. (2020)

  Teacher expertise and professional vision: Examining knowledge-based reasoning of pre-service teachers, in-service teachers, and school principals

  Frontiers in Education, 5, Article 59

  https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2020.00059/full

  C06

• Berndt, M., Thomas, F., Bauer, D., Härtl, A., Hege, I., Kääb, S., Fischer, M. R., & Heitzmann, N. (2020)

  The influence of prompts on final year medical students’ learning process and achievement in ECG interpretation

  GMS Journal of Medical Education, 37(1), 1-19

  https://journals.publisso.de/en/journals/jme/volume37/zma001304

  C02

• Hillmayr, D., Ziernwald, L., Reinhold, F., Hofer, S. I., & Reiss, K. M. (2020)

  The potential of digital tools to enhance mathematics and science learning in secondary schools: A context-specific metaanalysis

  Computers & Education, 153, 103897

  https://www.sciencedirect.com/science/article/pii/S0360131520300968?via%3Dihub

  A05

• Bonnes, C., Leiser, C., Schmidt‐Hertha, B., Rott, K.J., & Hochholdinger, S. (2020)

  The relationship between trainers’ media‐didactical competence and media‐didactical self‐efficacy, attitudes and use of digital media in training

  International Journal for Training & Development, 24(1), 74-88

  https://onlinelibrary.wiley.com/doi/10.1111/ijtd.12171

  B06

• Castner, N., Geßler, L., Geisler, D., Hüttig, F., & Kasneci, E. (2020)

  Towards expert gaze modeling and recognition of a user’s attention in realtime

  Procedia Computer Science, 176, 2020-2029

  https://doi.org/10.1016/j.procs.2020.09.238

  C01

• Schmidt-Hertha, B. (2020)

  Vermittlung medienpädagogischer Kompetenz in der Fort- und Weiterbildung von Lehrkräften

  Zeitschrift für Pädagogik, 66(2), 191-207

  https://content-select.com/de/portal/media/view/5e67bdfd-c068-4851-a8e6-4af1b0dd2d03

  B06

• Klein, P., Lichtenberger, A., Küchemann, S., Becker, S., Kekule, M., Viiri, J., Baadte, C., Vaterlaus, A., & Kuhn, J. (2020)

  Visual attention while solving the test of understanding graphs in kinematics: An eye-tracking analysis

  European Journal of Physics, 41(2), 1-16

  https://iopscience.iop.org/article/10.1088/1361-6404/ab5f51

  C02

• Schmiedeler, S., Khambatta, K., Hartmann, J. & Niklas, F. (2020)

  „Wenn den Zappelphilipp die Aufschieberitis packt“: Zusammenhänge zwischen Prokrastination und ADHS-Symptomen und mögliche Mediatoren

  Zeitschrift für Pädagogische Psychologie, 34, 23-34

  https://econtent.hogrefe.com/doi/10.1024/1010-0652/a000248

  B04

2019

• Braun, L. T., Lenzer, B., Fischer, M. R., & Schmidmaier R. (2019)

  Complexity of clinical cases in simulated learning environments: proposal for a scoring system

  GMS Journal for Medical Education, 36(6), Article Doc80

  https://doi.org/10.3205/zma001288

  A01 B02

• Heitzmann, N., Seidel, T., Hetmanek, A., Wecker, C., Fischer, M. R., Ufer, S., Schmidmaier, R., Neuhaus, B., Siebeck, M., Stürmer, K., Obersteiner, A., Reiss, K., Girwidz, R., Fischer, F., & Opitz, A. (2019)

  Facilitating diagnostic competences in simulations in higher education: A framework and a research agenda for medical and teacher education

  Frontline Learning Research, 7(4), 1–24

  https://frontlinelearningresearch.org//index.php/journal/article/view/384

  A01 B03 C03

• Klein, M., Otto, B., Fischer, M. R., & Stark, R. (2019)

  Fostering medical students’ clinical reasoning by learning from errors in clinical case vignettes: Effects and conditions of additional prompting procedures to foster self-explanations

  Advances in Health Sciences Education, 24(2), 331–351

  https://link.springer.com/article/10.1007/s10459-018-09870-5

  A01

• Vorholzer, A., & von Aufschnaiter, C. (2019)

  Guidance in inquiry-based instruction – an attempt to disentangle a manifold construct

  International Journal of Science Education, 41(11), 1562–1577

  https://www.tandfonline.com/doi/full/10.1080/09500693.2019.1616124

  C05

• Michaeli, T., & Romeike, R. (2019)

  Improving debugging skills in the classroom – the effects of teaching a systematic debugging process

  Proceedings of the 14th Workshop on Primary and Secondary Computing Education (pp. 1-7). ACM.

  https://dl.acm.org/doi/10.1145/3361721.3361724

  A04

• Kühl, S.J., Schneider, A., Kestler, H.A., Toberer, M., Kühl, M., & Fischer M.R. (2019)

  Investigating the self-study phase of an invert-ed biochemistry classroom - collaborative dyadic learning makes the difference

  BMC Medical Education, 19(1), 64

  https://link.springer.com/article/10.1186/s12909-019-1497-y

  B06

• Rohs, M., Schmidt-Hertha, B., Rott, K., & Bolten, R. (2019)

  Measurement of media pedagogical competences of adult educators

  European Journal for Research on the Education and Learning of Adults, 10(3), 304-324

  https://rela.ep.liu.se/article/view/393

  B06

• Braun, L. T., Borrmann, K. F., Lottspeich, C., Heinrich, D. A., Kiesewetter, J., Fischer. M. R., & Schmidmaier, R. (2019)

  Scaffolding clinical reasoning of medical students with virtual patients: Effects on diagnostic accuracy, efficiency, and errors

  Diagnosis, 6(2), 137-149

  https://doi.org/10.1515/dx-2018-0090

  A01

• Klein, P., Küchemann, S., Brückner, S., Zlatkin-Troitschanskaia, O., & Kuhn, J. (2019)

  Student understanding of graph slope and area under a curve: A replication study comparing first-year physics and economics students

  Physical Review Physics Education Research, 15(2), 020116

  https://journals.aps.org/prper/abstract/10.1103/PhysRevPhysEducRes.15.020116

  A03

• Stadler, M., Fischer, F., & Greiff, S. (2019)

  Taking a closer look: an exploratory analysis of successful and unsuccessful strategy use in complex problems

  Frontiers in Psychology, 10

  https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2019.00777/full

  A03 A06

• Sonnenschein, I., Koenen, J., & Tiemann, R. (2019)

  Wissenschaftliches Denken von Lehramtskandidaten. Explorative Studie im Fach Chemie

  Fachdidaktische Forschungen: Band 11. Fachdidaktische Forschung zur Lehrerbildung (pp. 215–225). Waxmann

  C05

2018

• Berndt, M., Strijbos, J.‑W., & Fischer, F. (2018)

  Effects of written peer-feedback content and sender’s competence on perceptions, performance, and mindful cognitive processing

  European Journal of Psychology of Education, 33(1), 31–49

  https://link.springer.com/article/10.1007/s10212-017-0343-z

  B01

• Hofer, S. I., Schumacher, R., Rubin, H., & Stern, E. (2018)

  Enhancing physics learning with cognitively activating instruction: A quasi-experimental classroom intervention study

  Journal of Educational Psychology, 110(8), 1175-1191

  https://psycnet.apa.org/doiLanding?doi=10.1037%2Fedu0000266

  A05

• Tafertshofer, L., Werner, E.-M. & Schmidt-Hertha, B. (2018)

  Grundlagen der Reputation von Studienstandorten: Bewertungsmaßstäbe für die Qualität von Hochschulstandorten und Studiengängen aus der Sicht von sozialwissenschaftlichen Professorinnen und Professoren

  Beiträge zur Hochschulforschung, 2018 (2), 68-88

  B06

• Herppich, S., Praetorius, A.-K., Förster, N., Glogger-Frey, I., Karst, K., Leutner, D., Behrmann, L., Böhmer, M., Ufer, S., & Klug, J. (2018)

  Teachers' assessment competence: Integrating knowledge-, process-, and product-oriented approaches into a compe-tence-oriented conceptual model

  Teaching and Teacher Education, 76, 181-193

  https://www.sciencedirect.com/science/article/abs/pii/S0742051X17303141?via%3Dihub

  A02

• Heitzmann, N., Fischer, F., & Fischer, M. R. (2018)

  Worked examples with errors: When self-explanation prompts hinder learning of teachers’ diagnostic competences on problem-based learning

  Instructional Science, 46(2), 245-271

  https://doi.org/10.1007/s11251-017-9432-2

  B03

2017

• Christ, O., Hewstone, M., Schmid, K., Green, E. G. T., Sarrasin, O., Gollwitzer, M., & Wagner, U. (2017)

  Advanced multilevel modeling for a science of groups: A short primer on multilevel structural equation modeling

  Group Dynamics: Theory, Research, and Practice, 21, 121-134

  https://psycnet.apa.org/doiLanding?doi=10.1037%2Fgdn0000065

  M

• Braun, L. T., Zwaan, L., Kiesewetter, J., Fischer, M. R., & Schmidmaier, R. (2017)

  Diagnostic errors by medical students: results of a prospective qualitative study

  BMC Medical Education, 17(1), 191

  https://doi.org/10.1186/s12909-017-1044-7

  B03

• Koenen, J., Emden, M., & Sumfleth, E. (2017)

  Naturwissenschaftlich-experimentelles Arbeiten

  eitschrift für Didaktik der Naturwissenschaften, 23(1), 81–98

  https://link.springer.com/article/10.1007/s40573-017-0056-5

  C05

• Braun, L. T., Zottmann, J. M., Adolf, C., Lottspeich, C., Then, C., Wirth, S., Fischer, M. R., & Schmidmaier, R. (2017)

  Representation scaffolds improve diagnostic efficiency in medical students

  Medical Education, 51(11), 1118-1126

  https://doi.org/10.1111/medu.13355

  B03 B02

• Vogel, F., Wecker, C., Kollar, I. & Fischer, F. (2017)

  Socio-cognitive scaffolding with computer-supported collaboration scripts: A meta-analysis

  Educational Psychology Review, 29(3), 477–511

  https://link.springer.com/article/10.1007/s10648-016-9361-7

  B02

• Hofer, S. I., Schumacher, R. & Rubin, H. J. (2017)

  The test of basic Mechanics Conceptual Understanding (bMCU): using Rasch analysis to develop and evaluate an efficient multiple choice test on Newton’s mechanics

  International Journal Of STEM Education, 4(1)

  https://link.springer.com/article/10.1186/s40594-017-0080-5

  A05

2016

• Wölfel, T., Beltermann, E., Lottspeich, C., Vietz, E., Fischer, M.R., & Schmidmaier, R. (2016)

  Medical ward round competence in internal medicine - an interview study towards an interprofessional development of an Entrustable Professional Activity (EPA)

  BMC Medical Education, 16, 174

  https://link.springer.com/article/10.1186/s12909-016-0697-y

  B02

2015

• Gartmeier, M., Bauer, J., Fischer, M. R., Hoppe-Seyler, T., Karsten, G., Kiessling, C., Möller, G. E., Wiesbeck, A., & Prenzel, M. (2015)

  Fostering professional communication skills of future physicians and teachers: effects of e-learning with video cases and role-play

  Instructional Science, 43(4), 443–462

  https://link.springer.com/article/10.1007/s11251-014-9341-6

  C03

• Bannert, M., Sonnenberg, C., Mengelkamp, C., & Pieger, E. (2015)

  Short- and long-term effects of students’ self-directed metacognitive prompts on navigation behavior and learning performance

  Computers in Human Behavior, 52, 293-306.

  https://www.sciencedirect.com/science/article/abs/pii/S0747563215004197?via%3Dihub

  C01

2014

• Niklas, F. & Schneider, W. (2014)

  Casting the die before the die is cast: The importance of the home numeracy environment for preschool children

  European Journal of Psychology of Education, 29(3), 327-345

  https://link.springer.com/article/10.1007/s10212-013-0201-6

  B04

• Seidel, T., & Stürmer, K. (2014)

  Modeling and measuring the structure of professional vision in Pre-service teachers

  American Educational Research Journal, 51(4), 739-771

  https://journals.sagepub.com/doi/10.3102/0002831214531321

  C03 C04

• Seidel, T., & Stürmer, K. (2014)

  Modeling the structure of professional vision in pre-service teachers

  American Educational Research Journal, 51, 739-771

  https://journals.sagepub.com/doi/10.3102/0002831214531321

  C01 C06

• Bannert, M., Reimann, P., & Sonnenberg, C. (2014)

  Process mining techniques for analysing patterns and strategies in students’ self-regulated learning

  Metacognition and Learning, 9(2), 161-185

  https://link.springer.com/article/10.1007/s11409-013-9107-6

  A04 B02

• Fischer, F., Kollar, I., Ufer, S., Sodian, B., Hussmann, H., Pekrun, R., Neuhaus, B., Dorner, B., Pankofer, S., Fischer, M. R., Strijbos, J.-W., & Eberle, J. (2014)

  Scientific reasoning and argumentation: Advancing an interdisciplinary research agenda in education

  Frontline Learning Research, 2(2), 28-45

  https://frontlinelearningresearch.org//index.php/journal/article/view/96

  C02

2013

• Obersteiner, A., Reiss, K., & Ufer, S. (2013)

  How training on exact or approximate mental representations of number can enhance first-grade students’ basic number processing and arithmetic skills

  Learning and Instruction, 23, 125–135

  https://www.sciencedirect.com/science/article/abs/pii/S0959475212000667?via%3Dihub

  A06

2010

• Kollar, I., & Fischer, F. (2010)

  Peer assessment as collaborative learning: A cognitive perspective

  Learning and Instruction, 20(4), 344–348

  https://www.sciencedirect.com/science/article/abs/pii/S0959475209000772?via%3Dihub

  B01