<p>Implicit differentiation is a key topic in first-semester university calculus. Beyond being a useful technique, it is conceptually related to many topics in differential calculus, such as the chain rule and related rates. However, it has received limited research attention. Our study addressed this gap by exploring how students in a first-semester calculus course performed on an activity that emphasized the connection between the symbolic and graphical representations of implicit curves and their derivatives. During class, students worked in small groups on this activity, and later in the semester, responded to a similar question on the midterm exam. We analyzed students’ written responses to both the in-class activity and the exam question using an Implicit Differentiation Knowledge Components (ImDKC) framework. The results show that overall, students performed better on symbolic knowledge components than on graphical ones, indicating difficulties in coordinating these two modalities. The exam performance was significantly higher than during the in-class activity, especially on graphical-symbolic coordination and finding vertical tangent lines. Conversely, students’ performance on two symbolic knowledge components: chain rule and differentiation, significantly declined on the exam compared to the in-class activity.</p>

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Coordinating Symbolic and Graphical Representations in Implicit Differentiation: Insights from First-Semester Calculus Students

  • Orly Buchbinder,
  • Meaghan Allen,
  • Michelle Capozzoli

摘要

Implicit differentiation is a key topic in first-semester university calculus. Beyond being a useful technique, it is conceptually related to many topics in differential calculus, such as the chain rule and related rates. However, it has received limited research attention. Our study addressed this gap by exploring how students in a first-semester calculus course performed on an activity that emphasized the connection between the symbolic and graphical representations of implicit curves and their derivatives. During class, students worked in small groups on this activity, and later in the semester, responded to a similar question on the midterm exam. We analyzed students’ written responses to both the in-class activity and the exam question using an Implicit Differentiation Knowledge Components (ImDKC) framework. The results show that overall, students performed better on symbolic knowledge components than on graphical ones, indicating difficulties in coordinating these two modalities. The exam performance was significantly higher than during the in-class activity, especially on graphical-symbolic coordination and finding vertical tangent lines. Conversely, students’ performance on two symbolic knowledge components: chain rule and differentiation, significantly declined on the exam compared to the in-class activity.