R. Biehler, A. Eichler, R. Hochmuth, S. Rach, and N. Schaper, “Einführung: Lehrinnovationen in der Hochschulmathematik – praxisrelevant – didaktisch fundiert – forschungsbasiert,” 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. 1–6.

R. Biehler, “Mathematikvorkurse als Brücke in das Studium–Einführung,” 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. 285–290.

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.

O. Schütze, O. Cuate, A. Martín, S. Peitz, and M. Dellnitz, “Pareto Explorer: a global/local exploration tool for many-objective optimization problems,” Engineering Optimization, vol. 52, no. 5, pp. 832–855, 2020.

S. Klus, F. Nüske, S. Peitz, J.-H. Niemann, C. Clementi, and C. Schütte, “Data-driven approximation of the Koopman generator: Model reduction, system identification, and control,” Physica D: Nonlinear Phenomena, vol. 406, 2020.

S. Peitz and S. Klus, “Feedback Control of Nonlinear PDEs Using Data-Efficient Reduced Order Models Based on the Koopman Operator,” in Lecture Notes in Control and Information Sciences, vol. 484, Cham: Springer, 2020, pp. 257–282.

K. Bieker, S. Peitz, S. L. Brunton, J. N. Kutz, and M. Dellnitz, “Deep model predictive flow control with limited sensor data and online learning,” Theoretical and Computational Fluid Dynamics, vol. 34, pp. 577–591, 2020.

S. Peitz, S. E. Otto, and C. W. Rowley, “Data-Driven Model Predictive Control using Interpolated Koopman  Generators,” SIAM Journal on Applied Dynamical Systems, vol. 19, no. 3, pp. 2162–2193, 2020.

J. Schumacher and S. Rezat, “Rekonstruktion diagrammatischen Schließens beim Erlernen der Subtraktion negativer Zahlen. Vergleich zweier methodischer Zugänge,” in Zeichen und Sprache im Mathematikunterricht, G. Kadunz, Ed. Springer, 2020.

J. Schumacher, “Deduktion und Abduktion beim diagrammatischen Schließen – das didaktische Potential der Peirceschen Semiotik,”10.17877/DE290R-21555__2020, doi:10.17877/DE290R-21555 .

R. Gerlach, A. Ziessler, B. Eckhardt, and M. Dellnitz, “A Set-Oriented Path Following Method for the Approximation of Parameter Dependent Attractors,”10.1137/19m1247139__SIAM Journal on Applied Dynamical Systems, pp. 705–723, 2020, doi:10.1137/19m1247139 .

H. Amiri, H. Glöckner, and A. Schmeding, “Lie groupoids of mappings taking values in a Lie groupoid,”10.5817/AM2020-5-307__Archivum Mathematicum, vol. 56, no. 5, pp. 307–356, 2020, doi:10.5817/AM2020-5-307 .

H. Glöckner and N. Masbough, “Products of regular locally compact spaces are k_R-spaces,” Topology Proceedings, vol. 55, pp. 35–38, 2020.

H. Glöckner, “Smoothing operators for vector-valued functions and extension operators,” arXiv:2006.00254. 2020.

H. Glöckner, “Lie groups of real analytic diffeomorphisms are L^1-regular,” arXiv:2007.15611. 2020.

D. J. N. Limebeer, S. Ober-Blöbaum, and F. H. Farshi, “Variational integrators for dissipative systems,” IEEE Transactions on Automatic Control, vol. 65(4), pp. 1381–1396, 2020.

C. I. Hernández Castellanos, S. Ober-Blöbaum, and S. Peitz, “Explicit Multi-objective Model Predictive Control for Nonlinear Systems  Under Uncertainty,”10.1002/rnc.5197__International Journal of Robust and Nonlinear Control, vol. 30(17), pp. 7593–7618, 2020, doi:10.1002/rnc.5197 .

C. I. O. Hernández Castellanos, G. Schütze, J.-Q. Sun, S. Ober-Blöbaum, and G. Morales-Luna, “Numerical computation of lightly multi-objective robust optimal solutions by means of generalized cell mapping,” Mathematics, vol. 8(11):1959, 2020.

Y. Lishkova, S. Ober-Blöbaum, M. Cannon, and S. Leyendecker, “A multirate variational approach to simulation and optimal control for flexible spacecraft,” 2020.

T. Faulwasser, K. Flaßkamp, S. Ober-Blöbaum, and K. Worthmann, “A dissipativity characterization of velocity turnpikes in optimal control problems for mechanical systems,” 2020.

J. Cresson, F. Jiménez, and S. Ober-Blöbaum, “Modelling of the convection-diffusion equation through fractional restricted calculus of variations,” 2020.

F. Jean, S. Maslovskaya, and I. Zelenko, “On Weyl’s type theorems and genericity of projective rigidity in sub-Riemannian geometry,”10.1007/s10711-020-00581-z__Geometriae Dedicata, vol. 213, no. 1, pp. 295–314, 2020, doi:10.1007/s10711-020-00581-z .

S. Maslovskaya, J.-B. Caillau, W. Djema, L. Giraldi, J.-L. Jean-Luc, and J.-B. Pomet, “The turnpike property in maximization of microbial metabolite production,” presented at the IFAC 2020 - 21rst IFAC World Congress, 2020.

B. Küster and T. Weich, “Pollicott-Ruelle Resonant States and Betti Numbers,”10.1007/s00220-020-03793-2__Communications in Mathematical Physics, vol. 378, no. 2, pp. 917–941, 2020, doi:10.1007/s00220-020-03793-2 .

M. Hoffmann, “Schnittstellenaktivitäten zum Kongruenzsatz WSW,”10.17877/DE290R-21368__in Beiträge zum Mathematikunterricht 2020, 2020, pp. 1353–1356, doi:10.17877/DE290R-21368 .

M. Hoffmann, “Rezension: Andrew Granville und Jenniver Granville: Prime Supects: The Anatomy of Integers and Permutations,”10.1007/s00591-019-00269-w__Mathematische Semesterberichte, vol. 67. pp. 119–121, 2020, doi:10.1007/s00591-019-00269-w .

M. Hoffmann, “Rezension: Ehrhard Behrends: Parkettierungen der Ebene – Von Escher über Möbius zu Penrose,”10.1007/s00591-019-00264-1__Mathematische Semesterberichte, vol. 67. pp. 115–116, 2020, doi:10.1007/s00591-019-00264-1 .

M. Hoffmann, Ed., Der Mathematikunterricht 66 (6): Geometrie in Schule und Lehramtsausbildung – ein Nachwuchsheft. 2020.

U. Häsel-Weide and M. Nührenbörger, “Tragfähige Grundlagen,” in Kinder lernen Zukunft – Anforderungen und tragfähige Grundlagen, 1st ed., vol. Band 150, U. Hecker, M. Lassek, and J. Ramseger, Eds. Frankfurt a. M.: Grundschulverband, 2020, pp. 108–118.

L. Heckmann and U. Häsel-Weide, “Aufgaben für den inklusiven Mathematikunterricht - aus der Sicht von Lehrkräften.,” in Beiträge zum Mathematikunterricht 2020, H.-S. Siller, W. Weigel, and J. F. Wörler, Eds. Münster: WTM Verlag, 2020, pp. 393–396.

U. Häsel-Weide, “Sachrechnen,” in Didaktik des Unterrichts bei Lernschwierigkeiten: Ein Handbuch für Studium und Praxis, 4th ed., U. Heimlich and F. B. Wember, Eds. W. Kohlhammer GmbH, 2020, pp. 308–318.