The Open UniversitySkip to content

Developing Students' Written Communication Skills with Jupyter Notebooks

Willis, Alistair; Charlton, Patricia and Hirst, Tony (2020). Developing Students' Written Communication Skills with Jupyter Notebooks. In: The 51st ACM Technical Symposium on Computer Science Education (SIGCSE ’20).

Full text available as:
PDF (Accepted Manuscript) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (1MB) | Preview
DOI (Digital Object Identifier) Link:
Google Scholar: Look up in Google Scholar


Written communication skills are considered to be highly desirable in computing graduates. However, many computing students do not have a background in which these skills have been developed, and the skills are often not well addressed within a computing curriculum. For some multidisciplinary areas, such as data science, the range of potential stakeholders makes the need for communications skills all the greater. As interest in data science increases and the technical skills of the area are in ever higher demand, understanding effective teaching and learning of these interdisciplinary aspects is receiving significant attention by academics, industry and government in an effort to address the digital skills gap.

In this paper, we report on the experience of adapting a final year data science module in an undergraduate computing curriculum to help develop the skills needed for writing extended reports. From its inception, the module has used Jupyter notebooks to develop the students' skills in the coding aspects of the module. However, over several presentations, we have investigated how the cell-based structure of the notebooks can be exploited to improve the students' understanding of how to structure a report on a data investigation. We have increasingly designed the assessment for the module to take advantage of the learning affordances of Jupyter notebooks to support both raw data analysis and effective report writing.

We reflect on the lessons learned from these changes to the assessment model, and the students' responses to the changes.

Item Type: Conference or Workshop Item
Copyright Holders: 2020 Association for Computing Machinery.
Keywords: Written communication; assessment; data science; Jupyter
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 68285
Depositing User: Alistair Willis
Date Deposited: 29 Nov 2019 12:17
Last Modified: 29 Nov 2019 17:51
Share this page:


Altmetrics from Altmetric

Citations from Dimensions

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU