Citations (35)
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Thembinkosi Peter Mkhatshwa. (2022) A study of calculus students’ difficulties, approaches and ability to solve multivariable optimization problems. International Journal of Mathematical Education in Science and Technology 53:11, pages 2987-3014.
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Yanning Yu & David H. Uttal. (2022) Gestures, embodiment, and learning the rate of change. Mathematical Thinking and Learning 24:3, pages 203-229.
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Thembinkosi P. Mkhatshwa. (2020) Calculus students’ quantitative reasoning in the context of solving related rates of change problems. Mathematical Thinking and Learning 22:2, pages 139-161.
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Thembinkosi P. Mkhatshwa. (2019) Students’ quantitative reasoning about an absolute extrema optimization problem in a profit maximization context. International Journal of Mathematical Education in Science and Technology 50:8, pages 1105-1127.
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Jim Gleason, Spencer Bagley, Matthew Thomas, Lisa Rice & Diana White. (2019) The calculus concept inventory: a psychometric analysis and implications for use. International Journal of Mathematical Education in Science and Technology 50:6, pages 825-838.
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Mahmut Kertil, Ayhan Kursat Erbas & Bulent Cetinkaya. (2019) Developing prospective teachers’ covariational reasoning through a model development sequence. Mathematical Thinking and Learning 21:3, pages 207-233.
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Thembinkosi Peter Mkhatshwa & Helen M. Doerr. (2018) Undergraduate Students’ Quantitative Reasoning in Economic Contexts. Mathematical Thinking and Learning 20:2, pages 142-161.
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Eric Weber, Michael A. Tallman & James A. Middleton. (2015) Developing Elementary Teachers’ Knowledge about Functions and Rate of Change through Modeling. Mathematical Thinking and Learning 17:1, pages 1-33.
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Articles from other publishers (27)
Mahmut Kertil, Ayhan Kursat Erbas & Bulent Cetinkaya. (2022) Pre-service Mathematics Teachers’ Understanding of Rate of Change Throughout a Model Development Sequence. International Journal of Science and Mathematics Education 21:6, pages 1769-1796.
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Steven R. Jones & Robert Ely. (2022) Approaches to Integration Based on Quantitative Reasoning: Adding Up Pieces and Accumulation from Rate. International Journal of Research in Undergraduate Mathematics Education 9:1, pages 8-35.
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Yaprak ARMUTCU & Ayten Pınar BAL. (2023) The Effect of Mathematical Modeling Activities on Students' Mathematical Modeling Skills in the Context of STEM Education. International Journal of Contemporary Educational Research 10:1, pages 42-55.
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Hans-Stefan Siller, Hans-Jürgen Elschenbroich, Gilbert Greefrath & Katrin Vorhölter. (2022) Mathematical modelling of exponential growth as a rich learning environment for mathematics classrooms. ZDM – Mathematics Education 55:1, pages 17-33.
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Emily E. Scott, Jack Cerchiara, Jenny L. McFarland, Mary Pat Wenderoth & Jennifer H. Doherty. (2022) How students reason about matter flows and accumulations in complex biological phenomena: An emerging learning progression for mass balance. Journal of Research in Science Teaching 60:1, pages 63-99.
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Evgenios Avgerinos & Dimitra Remoundou. (2021) The Language of “Rate of Change” in Mathematics. European Journal of Investigation in Health, Psychology and Education 11:4, pages 1599-1609.
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Mahmut KERTİL. (2021) Conceptual Analysis of Derivative as a Rate of Change and Analysis of the Mathematics TextbooksTürevin Değişim Oranı (Hızı) Yorumunun Kavramsal Analizi ve Matematik Ders Kitaplarının İncelenmesi. Sakarya University Journal of Education 11:3, pages 545-568.
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Lluís Albarracín, Carlos Segura, Irene Ferrando & Núria Gorgorió. (2021) Supporting mathematical modelling by upscaling real context in a sequence of tasks. Teaching Mathematics and its Applications: An International Journal of the IMA.
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Zeynep ÇAVUŞ ERDEM & Ramazan GÜRBÜZ. (2021) Investigation of Learning Environment Based on Mathematical Modeling ActivitiesMatematiksel Modelleme Etkinliklerine Dayalı Öğrenme Ortamının İncelenmesi. Necatibey Eğitim Fakültesi Elektronik Fen ve Matematik Eğitimi Dergisi 15:1, pages 62-94.
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Kristin Frank & Patrick W. Thompson. (2021) School students’ preparation for calculus in the United States. ZDM – Mathematics Education 53:3, pages 549-562.
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Joseph A. Lyon, Hayden W. Fennell & Alejandra J. Magana. (2020) Characterizing students' arguments and explanations of a discipline‐based computational modeling activity. Computer Applications in Engineering Education 28:4, pages 837-852.
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Mahmut KERTİL. (2020) Covariational Reasoning of Prospective Mathematics Teachers: How Do Dynamic Animations Affect?. Turkish Journal of Computer and Mathematics Education (TURCOMAT).
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Carli D. Flynn, Cliff I. Davidson & Sharon Dotger. (2018) Development and Psychometric Testing of the Rate and Accumulation Concept Inventory. Journal of Engineering Education 107:3, pages 491-520.
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Corey Brady. (2018) Modelling and the representational imagination. ZDM 50:1-2, pages 45-59.
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Jonas B. Ärlebäck & Helen M. Doerr. (2017) Students’ interpretations and reasoning about phenomena with negative rates of change throughout a model development sequence. ZDM 50:1-2, pages 187-200.
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Radovan Antonijević. (2018) Characteristics of the process of solving mathematical tasks. Nastava i vaspitanje 67:3, pages 439-451.
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Steven R. Jones. (2017) An exploratory study on student understandings of derivatives in real-world, non-kinematics contexts. The Journal of Mathematical Behavior 45, pages 95-110.
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Jennifer A. Czocher. (2017) How can emphasizing mathematical modeling principles benefit students in a traditionally taught differential equations course?. The Journal of Mathematical Behavior 45, pages 78-94.
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