Lankeit E, Biehler R. 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. Published online 2024. doi:10.1007/s11858-024-01584-w
LibreCat: /record/54144
DOI: 10.1007/s11858-024-01584-w

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

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

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

Biehler R, Engel J, Frischemeier D. Stochastik: Leitidee Daten und Zufall. In: Bruder R, Büchter A, Gasteiger H, Schmidt-Thieme B, Weigand HG, eds. Handbuch Der Mathematikdidaktik. Springer; 2023. doi: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. Impacts of Digitalization on Content and Goals of Statistics Education. In: Pepin B, Gueudet G, Choppin J, eds. Handbook of Digital Resources in Mathematics Education. Springer International Publishing; 2023.
LibreCat: /record/48042

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

Biehler R, Liebendörfer M, Gueudet G, Rasmussen C, Winsløw C. Practice-Oriented Research in Tertiary Mathematics Education – An Introduction. In: Practice-Oriented Research in Tertiary Mathematics Education. Springer International Publishing; 2023. doi: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. Framing Goals of Mathematics Support Measures. In: Practice-Oriented Research in Tertiary Mathematics Education. Springer International Publishing; 2023:91-117. doi: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. Practice-Oriented Research in Tertiary Mathematics Education. Springer International Publishing; 2023. doi:10.1007/978-3-031-14175-1
LibreCat: /record/46157
DOI: 10.1007/978-3-031-14175-1

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

Nieszporek R, Griese B, Biehler R. Facilitators’ Orientations Towards Learning Goals, Perceived Challenges, and Teaching Resources for a PD Course on Conditional Probability. In: Peters SA, Zapata-Cardona L, Bonafini F, Fan A, 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; 2022. doi:10.52041/iase.icots11.t4b2
LibreCat: /record/35696
DOI: 10.52041/iase.icots11.t4b2

Biehler R. Revisiting Fundamental Ideas for Statistics Education From the Perspective of Machine Learning and Its Applications. In: Peters SA, Zapata-Cardona L, Bonafini F, Fan A, 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; 2022. doi: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. Editorial: Research on Data Science Education. Statistics Education Research Journal. 2022;21(2). doi:10.52041/serj.v21i2.606
LibreCat: /record/34920
DOI: 10.52041/serj.v21i2.606

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

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

Fleischer Y, Biehler R, Schulte C. Teaching and Learning Data-Driven Machine Learning with Educationally Designed Jupyter Notebooks. Statistics Education Research Journal. 2022;21(2). doi:10.52041/serj.v21i2.61
LibreCat: /record/35672
DOI: 10.52041/serj.v21i2.61

Griese B, Nieszporek R, Biehler R. Facilitators’ views on content goals, learning obstacles, and teaching resources in reference to conditional probability. In: ; 2022.
LibreCat: /record/39058

Lankeit E, Biehler R. Mathematik-Vorkurse zur Vorbereitung auf das Studium – Zielsetzungen und didaktische Konzepte. In: Hochmuth R, Biehler R, Liebendörfer M, Schaper N, eds. Unterstützungsmaßnahmen in mathematikbezogenen Studiengängen - Konzepte, Praxisbeispiele und Untersuchungsergebnisse. Springer; 2022:117-141. doi:10.1007/978-3-662-64833-9_4
LibreCat: /record/42653
DOI: 10.1007/978-3-662-64833-9_4

Liebendörfer M, Göller R, Gildehaus L, et al. The role of learning strategies for performance in mathematics courses for engineers. International Journal of Mathematical Education in Science and Technology. 2022;53(5):1133-1152. doi:10.1080/0020739x.2021.2023772
LibreCat: /record/35685
DOI: 10.1080/0020739x.2021.2023772