A new generation of mathematics textbook research and development View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-09

AUTHORS

Kay L. O’Halloran, Robert A. Beezer, David W. Farmer

ABSTRACT

This paper adopts a multimodal approach to the latest generation of digital mathematics textbooks (print and online) to investigate how the design, content, and features facilitate the construction of mathematical knowledge for teaching and learning purposes. The sequential organization of the print version is compared to the interactive format of the online version which foregrounds explanations and important mathematical content while simultaneously ensuring a high level of connectivity and coherence across hierarchical layers of mathematical knowledge. For example, mathematical content in the online version is linked to definitions, theorems, examples and exercises that can be viewed in the original context in which the material was presented, and the content can also be linked to mathematics software. Significantly, the development process for the new generation of mathematics textbooks involves using a ‘design neutral’ markup language so that the books are simultaneously published as both print books and online books. In this development process, the structure of the chapters, sections, and subsections with their various elements are explicitly marked-up in the master document and preserved in the output format, giving rise to new methodologies for large-scale analysis of mathematics textbooks and student use of these books. For example, tracking methodologies and interactive visualizations of student viewings of online mathematical textbooks are identified as new research directions for investigating how students engage with mathematics textbooks within and across different educational contexts. More... »

PAGES

863-879

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11858-018-0959-8

DOI

http://dx.doi.org/10.1007/s11858-018-0959-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1104894256


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