E. Lankeit and R. Biehler, “The meaning landscape of the concept of the total derivative in multivariable real analysis textbooks: an analysis based on a new model of meaning,”10.1007/s11858-024-01584-w__ZDM – Mathematics Education, 2024, doi:10.1007/s11858-024-01584-w .

M. Hoffmann and R. Biehler, “Student Teachers ’ Knowledge of Congruence before a University Course on Geometry,” in Proceedings of the Fourth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2022, 19-22 October 2022), 2023.

M. Hoffmann and R. Biehler, “Implementing profession orientation as a design principle for overcoming Klein’s second discontinuity – preservice teacher’s perspectives on interface activities in the context of a geometry course,”10.1007/s11858-023-01505-3__ZDM – Mathematics Education, 2023, doi:10.1007/s11858-023-01505-3 .

L. Ostsieker and R. Biehler, “Supporting Students in Developing Adequate Concept Images and Definitions at University: The Case of the Convergence of Sequences,” in Practice-Oriented Research in Tertiary Mathematics Education, Cham: Springer International Publishing, 2023, pp. 181–201.

J. Kortemeyer and R. Biehler, “Analyzing the Interface Between Mathematics and Engineering in Basic Engineering Courses,” in Practice-Oriented Research in Tertiary Mathematics Education, Cham: Springer International Publishing, 2023, pp. 669–692.

J. Kortmeyer and R. Biehler, “The use of integrals for accumulation and mean values in basic electrical engineering courses,” in The Learning and Teaching of Calculus Across Disciplines – Proceedings of the Second Calculus Conference, T. Dreyfus, A. S. Gonzalez-Martin, E. Nardi, J. Monaghan, and P. W. Thompson, Eds. MatRIC, 2023, pp. 121–124.

R. Biehler, J. Engel, and D. Frischemeier, “Stochastik: Leitidee Daten und Zufall,” in Handbuch der Mathematikdidaktik, R. Bruder, A. Büchter, H. Gasteiger, B. Schmidt-Thieme, and HG. Weigand, Eds. Berlin, Heidelberg: Springer, 2023.

R. Biehler, D. Frischemeier, R. Gould, and M. Pfannkuch, “Impacts of Digitalization on Content and Goals of Statistics Education,” in Handbook of Digital Resources in Mathematics Education, B. Pepin, G. Gueudet, and J. Choppin, Eds. Cham: Springer International Publishing, 2023.

R. Biehler and K. Krüger, “Von Glückstal (Ukraine) nach Frankfurt: Problemlösen, Algorithmen, Stochastik – Nachruf auf Arthur Engel,” GDM-Mitteilungen, no. 115, pp. 57–65, 2023.

R. Biehler, M. Liebendörfer, G. Gueudet, C. Rasmussen, and C. Winsløw, “Practice-Oriented Research in Tertiary Mathematics Education – An Introduction,” in Practice-Oriented Research in Tertiary Mathematics Education, Cham: Springer International Publishing, 2023.

M. Liebendörfer, C. Büdenbender-Kuklinski, E. Lankeit, M. Schürmann, R. Biehler, and N. Schaper, “Framing Goals of Mathematics Support Measures,” in Practice-Oriented Research in Tertiary Mathematics Education, Cham: Springer International Publishing, 2023, pp. 91–117.

R. Biehler, M. Liebendörfer, G. Gueudet, C. Rasmussen, and C. Winsløw, Eds., Practice-Oriented Research in Tertiary Mathematics Education. Cham: Springer International Publishing, 2023.

R. Biehler, M. Liebendörfer, and A. Schmitz, “Lernvideos und ihre Erstellung - Das Projekt studiVEMINTvideos,” Mitteilungen der Gesellschaft für Didaktik der Mathematik, vol. 114, pp. 8–12, 2023.

M. Hoffmann and R. Biehler, “Schnittstellenaufgaben in der Analysis I zur Verknüpfung von Schul- und Hochschulmathematik - Aufgabenbeispiele und Ergebnisse einer Evaluationsstudie.,” in  Bedarfsgerechte fachmathematische Lehramtsausbildung. Analyse, Zielsetzungen und Konzepte unter heterogenen Voraussetzungen , 2022, pp. 351–368.

R. Biehler and M. Hoffmann, “Fachwissen als Grundlage fachdidaktischer Urteilskompetenz – Beispiele für die Herstellung konzeptueller Bezüge zwischen fachwissenschaftlicher und fachdidaktischer Lehre im gymnasialen Lehramtsstudium,”10.1007/978-3-662-63948-1_4__in 10.1007/978-3-662-63948-1_4__Professionsorientierte Fachwissenschaft. Kohärenzstiftende Lerngelegenheiten für das Lehramtsstudium Mathematik, 2022, pp. 49–72, doi:10.1007/978-3-662-63948-1_4 .

R. Nieszporek, B. Griese, and R. Biehler, “Facilitators’ Orientations Towards Learning Goals, Perceived Challenges, and Teaching Resources for a PD Course on Conditional Probability,” in Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics, S. A. Peters, L. Zapata-Cardona, F. Bonafini, and A. Fan, Eds. Rosario, Argentina: International Association for Statistical Education, 2022.

R. Biehler, “Revisiting Fundamental Ideas for Statistics Education From the Perspective of Machine Learning and Its Applications,”10.52041/iase.icots11.t1a2__in Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics, 2022, doi:10.52041/iase.icots11.t1a2 .

R. Biehler, R. De Veaux, J. Engel, S. Kazak, and D. Frischemeier, “Editorial: Research on Data Science Education,”10.52041/serj.v21i2.606__Statistics Education Research Journal, vol. 21, no. 2, Art. no. 1, 2022, doi:10.52041/serj.v21i2.606 .

R. Biehler, H. Langlotz, and W. Zappe, “Alles normal?! Daten auf Normalverteilung prüfen–mit schulischen Mitteln,” mathematik lehren, vol. 2022, no. 232, pp. 41–45, 2022.

R. Biehler and B. Griese, “Modellieren im Stochastikunterricht: Annahmen hinterfragen, Ergebnisse validieren,” mathematik lehren, vol. 2022, no. 232, pp. 2–6, 2022.