Lankeit, E., &; Biehler, R. (2024). The meaning landscape of the concept of the total derivative in multivariable real analysis textbooks: an analysis based on a new model of meaning. ZDM – Mathematics Education.https://doi.org/10.1007/s11858-024-01584-w 
LibreCat: /record/54144
DOI: 10.1007/s11858-024-01584-w

Hoffmann, M., &; Biehler, R. (2023). Student Teachers ’ Knowledge of Congruence before a University Course on Geometry. In M. Trigueros, B. Barquero, R. Hochmuth, &; J. Peters (Eds.), Proceedings of the Fourth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2022, 19-22 October 2022). University of Hannover and INDRUM.
LibreCat: /record/31849

Hoffmann, M., &; Biehler, R. (2023). 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. ZDM – Mathematics Education.https://doi.org/10.1007/s11858-023-01505-3 
LibreCat: /record/45786
DOI: 10.1007/s11858-023-01505-3

Ostsieker, L., &; Biehler, R. (2023). 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 (pp. 181–201). Springer International Publishing.https://doi.org/10.1007/978-3-031-14175-1_9 
LibreCat: /record/35697
DOI: 10.1007/978-3-031-14175-1_9

Kortemeyer, J., &; Biehler, R. (2023). Analyzing the Interface Between Mathematics and Engineering in Basic Engineering Courses. In Practice-Oriented Research in Tertiary Mathematics Education (pp. 669–692). Springer International Publishing.https://doi.org/10.1007/978-3-031-14175-1_32 
LibreCat: /record/35678
DOI: 10.1007/978-3-031-14175-1_32

Kortmeyer, J., &; Biehler, R. (2023). The use of integrals for accumulation and mean values in basic electrical engineering courses. In T. Dreyfus, A. S. Gonzalez-Martin, E. Nardi, J. Monaghan, &; P. W. Thompson (Eds.), The Learning and Teaching of Calculus Across Disciplines – Proceedings of the Second Calculus Conference (pp. 121–124). MatRIC.
LibreCat: /record/48480

Biehler, R., Engel, J., &; Frischemeier, D. (2023). Stochastik: Leitidee Daten und Zufall. In R. Bruder, A. Büchter, H. Gasteiger, B. Schmidt-Thieme, &; HG. Weigand (Eds.), Handbuch der Mathematikdidaktik. Springer.https://doi.org/10.1007/978-3-662-66604-3_8 
LibreCat: /record/47416
DOI: 10.1007/978-3-662-66604-3_8

Biehler, R., Frischemeier, D., Gould, R., &; Pfannkuch, M. (2023). Impacts of Digitalization on Content and Goals of Statistics Education. In B. Pepin, G. Gueudet, &; J. Choppin (Eds.), Handbook of Digital Resources in Mathematics Education. Springer International Publishing.
LibreCat: /record/48042

Biehler, R., &; Krüger, K. (2023). Von Glückstal (Ukraine) nach Frankfurt: Problemlösen, Algorithmen, Stochastik – Nachruf auf Arthur Engel. GDM-Mitteilungen, 115, 57–65.
LibreCat: /record/49049

Biehler, R., Liebendörfer, M., Gueudet, G., Rasmussen, C., &; Winsløw, C. (2023). Practice-Oriented Research in Tertiary Mathematics Education – An Introduction. In Practice-Oriented Research in Tertiary Mathematics Education. Springer International Publishing.https://doi.org/10.1007/978-3-031-14175-1_1 
LibreCat: /record/35669
DOI: 10.1007/978-3-031-14175-1_1

Liebendörfer, M., Büdenbender-Kuklinski, C., Lankeit, E., Schürmann, M., Biehler, R., &; Schaper, N. (2023). Framing Goals of Mathematics Support Measures. In Practice-Oriented Research in Tertiary Mathematics Education (pp. 91–117). Springer International Publishing.https://doi.org/10.1007/978-3-031-14175-1_5 
LibreCat: /record/35681
DOI: 10.1007/978-3-031-14175-1_5

Biehler, R., Liebendörfer, M., Gueudet, G., Rasmussen, C., &; Winsløw, C. (Eds.). (2023). Practice-Oriented Research in Tertiary Mathematics Education. Springer International Publishing.https://doi.org/10.1007/978-3-031-14175-1 
LibreCat: /record/46157
DOI: 10.1007/978-3-031-14175-1

Biehler, R., Liebendörfer, M., &; Schmitz, A. (2023). Lernvideos und ihre Erstellung - Das Projekt studiVEMINTvideos. Mitteilungen der Gesellschaft für Didaktik der Mathematik, 114, 8–12.
LibreCat: /record/43504

Hoffmann, M., &; Biehler, R. (2022). Schnittstellenaufgaben in der Analysis I zur Verknüpfung von Schul- und Hochschulmathematik - Aufgabenbeispiele und Ergebnisse einer Evaluationsstudie. In S. Halverscheid, I. Kersten, &; B. Schmidt-Thieme (Eds.),  Bedarfsgerechte fachmathematische Lehramtsausbildung. Analyse, Zielsetzungen und Konzepte unter heterogenen Voraussetzungen  (pp. 351–368). Springer Spektrum.
LibreCat: /record/31367

Biehler, R., &; Hoffmann, M. (2022). Fachwissen als Grundlage fachdidaktischer Urteilskompetenz – Beispiele für die Herstellung konzeptueller Bezüge zwischen fachwissenschaftlicher und fachdidaktischer Lehre im gymnasialen Lehramtsstudium. In V. Isaev, A. Eichler, &; F. Loose (Eds.), https://doi.org/10.1007/978-3-662-63948-1_4__Professionsorientierte Fachwissenschaft. Kohärenzstiftende Lerngelegenheiten für das Lehramtsstudium Mathematik (pp. 49–72). Springer.https://doi.org/10.1007/978-3-662-63948-1_4 
LibreCat: /record/31365
DOI: 10.1007/978-3-662-63948-1_4

Nieszporek, R., Griese, B., &; Biehler, R. (2022). Facilitators’ Orientations Towards Learning Goals, Perceived Challenges, and Teaching Resources for a PD Course on Conditional Probability. In S. A. Peters, L. Zapata-Cardona, F. Bonafini, &; A. Fan (Eds.), Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics. International Association for Statistical Education.https://doi.org/10.52041/iase.icots11.t4b2 
LibreCat: /record/35696
DOI: 10.52041/iase.icots11.t4b2

Biehler, R. (2022). Revisiting Fundamental Ideas for Statistics Education From the Perspective of Machine Learning and Its Applications. In S. A. Peters, L. Zapata-Cardona, F. Bonafini, &; A. Fan (Eds.), Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics. International Association for Statistical Education.https://doi.org/10.52041/iase.icots11.t1a2 
LibreCat: /record/34919
DOI: 10.52041/iase.icots11.t1a2

Biehler, R., De Veaux, R., Engel, J., Kazak, S., &; Frischemeier, D. (2022). Editorial: Research on Data Science Education. Statistics Education Research Journal, 21(2), Article 1.https://doi.org/10.52041/serj.v21i2.606 
LibreCat: /record/34920
DOI: 10.52041/serj.v21i2.606

Biehler, R., Langlotz, H., &; Zappe, W. (2022). Alles normal?! Daten auf Normalverteilung prüfen–mit schulischen Mitteln. Mathematik Lehren, 2022(232), 41–45.
LibreCat: /record/35718

Biehler, R., &; Griese, B. (2022). Modellieren im Stochastikunterricht: Annahmen hinterfragen, Ergebnisse validieren. Mathematik Lehren, 2022(232), 2–6.
LibreCat: /record/35926