Teaching and learning strategies for the derivative in engineering education: A scoping review protocol

Abstract

The derivative is a fundamental concept in engineering education, as it enables students to model and interpret phenomena related to rates of change, optimization, and the analysis of physical processes. However, its teaching in higher education often emphasizes decontextualized algebraic procedures, with limited integration of authentic engineering problems and interactive digital technologies. This protocol outlines a scoping review aimed at mapping the available evidence on teaching and learning strategies for the derivative in undergraduate engineering education that incorporate authentic engineering problems, with or without the support of digital technologies. The review will follow the methodological framework proposed by the JBI Manual for Evidence Synthesis and the reporting guidelines of PRISMA-ScR. The review is guided by the PCC framework: (P) undergraduate engineering students; (C) didactic strategies for teaching and learning the derivative grounded in authentic engineering problems, with or without the support of digital technologies; and (C) higher education engineering programs. Searches will be conducted in Scopus, Web of Science, ERIC, and SciELO for peer-reviewed publications published between 2000 and 2026 in English, Spanish, and Portuguese. Two reviewers will independently screen and select studies using Rayyan, and disagreements will be resolved by consensus. Data will be extracted using a pilot-tested data extraction form and synthesized through descriptive statistics, thematic categorization, and narrative synthesis. The review will provide a comprehensive mapping of didactic strategies, types of authentic problems, and reported learning difficulties related to the derivative in engineering education. The findings are expected to inform instructional design and support the development of evidence-based teaching practices in calculus courses for engineering students.

The authors' abstract, as published at the source. PLoS ONE, 2026 · DOI ↗