R. Biehler and Y. Fleischer, “Introducing students to machine learning with decision trees using CODAP and Jupyter Notebooks,”10.1111/test.12279__Teaching Statistics, vol. 43, pp. 3–2, 2021, doi:10.1111/test.12279 .

R. Biehler, A. Eichler, R. Hochmuth, S. Rach, and N. Schaper, Eds., Lehrinnovationen in der Hochschulmathematik. Berlin, Heidelberg: Springer Spektrum, 2021.

R. Biehler and H.-G. Weigand, “D-Geometrie–virtuell und real,” mathematik lehren, vol. 2021, no. 228, pp. 2–5, 2021.

B. Pepin, R. Biehler, and G. Gueudet, “Mathematics in Engineering Education: a Review of the Recent Literature with a View towards Innovative Practices,”10.1007/s40753-021-00139-8__International Journal of Research in Undergraduate Mathematics Education, vol. 7, no. 2, pp. 163–188, 2021, doi:10.1007/s40753-021-00139-8 .

L. Kempen and R. Biehler, “Design-Based Research in der Hochschullehre am Beispiel der Lehrveranstaltung eEinführung in die Kultur der Mathematik“,” in Lehrinnovationen in der Hochschulmathematik . Konzepte und Studien zur Hochschuldidaktik und Lehrerbildung Mathematik, R. Biehler, A. Eichler, R. Hochmuth, S. Rach, and N. Schaper, Eds. Berlin, Heidelberg: Springer Spektrum, 2021, pp. 4773525.

C. Winsløw, R. Biehler, B. Jaworski, F. Rønning, and M. Wawro, “Education and professional development of university mathematics teachers,” in Research and Development in University Mathematics Education, V. Durand-Guerrier, R. Hochmuth, E. Nardi, and C. Winsløw, Eds. Routledge, 2021, pp. 59–79.

L. Höper, L. Malin, and R. Biehler, “Schatten von 3D-Objekten: Modellierung mit GeoGebra 3D und Anwendungen in der Computergrafik,” mathematik lehren, vol. 2021, no. 228, pp. 19–22, 2021.

S. Hüsing, N. Weiser, and R. Biehler, “Faszination 3D-Film: Entwicklung einer 3D-Konstruktion,” mathematik lehren, vol. 2021, no. 228, pp. 23–27, 2021.

M. Schürmann et al., “Consultation Phases in Mathematics Learning and Support Centres,”10.1007/s40753-021-00154-9__International Journal of Research in Undergraduate Mathematics Education, vol. 8, no. 1, pp. 94–120, 2021, doi:10.1007/s40753-021-00154-9 .

S. Podworny and R. Biehler, “The process of actively building a model for a randomization test – insights into learners’ modeling activities based on a case study,”10.1080/10986065.2021.1922837__Mathematical Thinking and Learning, vol. 24, no. 4, pp. 291–311, 2021, doi:10.1080/10986065.2021.1922837 .

D. Frischemeier, R. Biehler, S. Podworny, and L. Budde, “A first introduction to data science education in secondary schools: Teaching and learning about data exploration with&;scp&;CODAP&;/scp&;using survey data,”10.1111/test.12283__Teaching Statistics, vol. 43, no. , pp. 82–89, 2021, doi:10.1111/test.12283 .

M. Schürmann et al., “Opportunities and Possibilities of a Network of Mathematical Learning and Support Centres in Germany,” Sigma newsletter, vol. 22, pp. 5–6, 2021.

J. Schönherr, S. Schukajlow, and J. Blomberg, “Was ist eine gute Skizze? Strategiewissen beim mathematischen Modellieren im Bereich der Geometrie fördern,” mathematik lehren, vol. 224, pp. 22–27, 2021.

J. Schönherr, S. Schukajlow, J. Blomberg, and C. Leopold, “Does strategic knowledge matter? Effects of strategic knowledge about drawing on students’ modeling competencies in the domain of geometry,”10.1080/10986065.2021.2012741__Mathematical Thinking and Learning, 2021, doi:10.1080/10986065.2021.2012741 .

J. Schönherr, J. Blomberg, S. Schukajlow, and C. Leopold, “Do emotions and prior performance facilitate the use of the learner-generated drawing strategy? Effects of enjoyment, anxiety, and intramathematical performance on the use of the drawing strategy and modelling performance,”10.1016/j.cedpsych.2021.101967__Contemporary Educational Psychology, vol. 65, 2021, doi:10.1016/j.cedpsych.2021.101967 .

R. I. McLachlan and C. Offen, “Preservation of Bifurcations of Hamiltonian Boundary Value Problems Under Discretisation,” Foundations of Computational Mathematics, vol. 20, no. 6, pp. 1363–1400, 2020.

L. M. Kreusser, R. I. McLachlan, and C. Offen, “Detection of high codimensional bifurcations in variational PDEs,” Nonlinearity, vol. 33, no. 5, pp. 2335–2363, 2020.

K. Flaßkamp, S. Ober-Blöbaum, and S. Peitz, “Symmetry in Optimal Control: A Multiobjective Model Predictive Control Approach,” in Advances in Dynamics, Optimization and Computation, O. Junge, O. Schütze, G. Froyland, S. Ober-Blöbaum, and K. Padberg-Gehle, Eds. Cham: Springer, 2020.

S. Klus, F. Nüske, and B. Hamzi, “Kernel-Based Approximation of the Koopman Generator and Schrödinger Operator,” Entropy, 2020.

R. Hochmuth, M. Liebendörfer, R. Biehler, and A. Eichler, “Das Kompetenzzentrum Hochschuldidaktik Mathematik (khdm),” Neues Handbuch Hochschullehre, vol. 95, pp. 117–138, 2020.