Thursday, 14 April 2022

Behind 'Design principles for developing critique and academic argument in a blended-learning data visualization course'

Written for visual design educators and social semiotic researchers interested in students' use of data visualisations for argument.


Professor Arlene Archer and my chapter, 'Design principles for developing critique and academic argument in a blended-learning data visualization course', is to be published in 'Learning Design Voices'. Edited by Professor Laura Czerniewicz, Tasneem Jaffer and Shanali Govender. the book is produced by the University of Cape Town's (UCT) Centre for Innovation in Learning and Teaching (CILT). Its compilation aims to catalyse a discussion of key themes shaping practice in online learning design. Our contribution falls under the book's 'Learning materials, activities and processes' section. The book's other two tackle 'Learning Design as field, praxis and identity' and 'Humanising Learning Design'.


Our new chapter is a sequel to 'Exploring academic argument in information graphics' (2020), in which we proposed the framework for argument in data visualizations shown in Table 1. This social semiotic framework provides a holistic view that is useful for providing feedback and recognising students’ work as realised through the ideational, interpersonal, and textual meta-functions. For example, in addition to the verbal (written) mode that they are usually assessed on in Higher Education, students' digital poster designs must also consider composition, size, shape and colour choices.


Table 1. Framework for analysing and producing argument in data visualisation.
Designed by Arlene Archer and Travis Noakes, 2021.

Framework for analysing and producing argument in data visualisation

When the course was first introduced, many students' were able to produce attractive posters, but there seemed scope to support them in developing better arguments by revising the course's contents. Our follow-up piece describes how using this framework proved helpful for changing a second-year journalism, blended-learning course and helping students' argument-development:

In five-weeks, the lecturer had to teach novices- data infographics, graphic design and Excel software, visual design aesthetics and multimodal argumentation via data visualization designs. Many changes were considered for improving the posters’ argument and the lecturer changed the 2018 syllabus structure by adding two new sections (for ‘Multimodal argument’ and ‘Creative ideas for infographic design’, see Table 2).

Table 2. Lesson topic changes from 2017 to 2018's course

Lesson topic changes from 2017 to 2018's course

A midway assessment was also introduced in which students’ infographic arguments were tested as works-in-progress. Reviewers’ feedback presented those who went for the wrong goalposts with opportunities for changing their direction by the final assessment. The new sections and mid-way assessment proved helpful for supporting 2018's students on aggregate with developing better arguments via infographic posters. The initial course was arguably weighted too much on using new tools for aesthetic design. By contrast, the new iteration was weighted towards teaching opaque discursive conventions and how to make a coherent, strong infographic poster argument using different modes that travel well as they traverse different formats. 

To illustrate the benefits of this shift, our article focuses on two students, whose work differed from those of the 2017’s class in presenting meta-level critiques. As a result of some of the curriculum interventions, students began to engage with normative attitudes and societal discourses that shaped the information they shared. They began to flag how the graphs they shared might represent a numeric simplification of a qualitatively complex situation, and to point to the ways in which the categories for comparison may be blurred.

Before presenting two in-depth student cases, we described how several principles for learning design informed our analysis of student work using this framework:

1) Delimiting the scope of the task
2) Encouraging the use of readily accessible design tools
3) Considering gains and losses in digital translations
4) Implementing a process approach for developing argument and encouraging reflection
5) Developing meta-languages of critique and argument
6) Acknowledging different audiences and the risks of sharing work as novices


"Tumi" and "Mark" followed different approaches to metalevel critique in their data visualization project's. Tumi’s presentation (see Figures 1 and 2) critiqued the usefulness of Youth Explorer for exploring education in a peripheral township community versus a suburban ‘core community’. In contrasting the Langa township ward's educational attendance data versus the leafy suburb of Pinelands, she flagged why the results may be skewed unfavourably against Langa- children from peripheral communities often travel to core communities for schooling, so data for both core and peripheral communities “can be blurred to some extent”. Tumi also flagged that youth accused of contact crime were not necessarily ‘convicted or found guilty’.


Figure 1. Tumi's findings slide 2018

Tumi's findings slide 2018

Figure 2. Tumi's limitations slide 2018

Tumi's findings limitations slide 2018

By contrast, Mark’s poster (see Figure 3) critiqued the statistics available for understanding ‘poor grade 8 systemic results’ and the reasons for higher drop-out rates in schooling between suburbs. His poster explored the limitations of what Youth Explorer can tell us about systemic tests and how these link to dropout rates and final year pass rates. He argued that a shortcoming is the dataset’s failure to convey 'the role that extra-curricular support plays' in shaping learners’ results. Mark's poster reflected the fact that many children from affluent homes go for extra lessons after school to improve subject results. This knowledge of concerted cultivation was based on his personal experience, but is unaccounted for in most official accounts of educational input.


Figure 3. Mark's data visualisation poster 2018

Mark's data visualisation poster 2018

Both cases reveal how teaching a social semiotic approach for analysing and producing argument proved helpful. It informed changes to a data visualisation poster course that could better support students’ development as critical designers and engaged citizens- the two aspirant media professionals' meta-critiques flagged important challenges in relying on data that may be incorrect and incomplete, accurately spotlighting the inherent difficulties of simplifying qualitative complexity into numbers for their audiences.


If you would like to view a presentation on our research, please visit my earlier blog post at 
https://www.travisnoakes.co.za/2021/10/the-presentation-developing-critique.html.


Acknowledgements

The research is based upon work supported by the British Academy Newton Advanced Fellowship scheme. Travis’ research was supported by a Postdoctoral Fellowship (2019-21) at the Cape Peninsula University of Technology. Both authors thank the University of Cape Town’s Centre for Film and Media Studies for facilitating our research with students between 2017 and 2018. In particular, we thank Professor Marion Walton and Dr Martha Evans for their valued assistance. We also greatly appreciate the feedback from the editors and reviewers at Learning Design Voices.


Need support doing Social Semiotic research in Africa?

Both Arlene and Travis are members of the South African Multimodality in Education research group (SAME) hosted by UCT. Should you be interested in sharing your multimodal research project with its experts, please contact SAME.

I hope that you will read our chapter and find it informative. You are most welcome to give readers and I your feedback in the moderated comments section below.

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This blog is moderated due to problems experienced by a few readers who could not submit unmoderated comments. Please keep your comment length under 300 words; any longer and you will struggle to submit it. Ta, Travis.

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