Beyond Data Literacy in Engineering Education

This is a Preprint and has not been peer reviewed. This is version 2 of this Preprint.


Samira Khodaei  , Mihail Padev, Anas Abdelrazeq  , Ingrid Isenhardt


Data literacy is a key ingredient for engineering education [14]. Through digital transformation, more data are generated in different scientific fields that will be interpreted. As a highly applicable scientific field, mechanical engineering is predestined to integrate data literacy into the higher education curriculum [17]. However, current frameworks rarely consider ethical questions, agency, and media influences to data [2] . As media and data are closely connected, it is valuable for both literacy framework approaches and researchers to consider each other and enhance their models from one another. Formally, the German Media Science Association has addressed current fallacies in educational policies founded on data literacy frameworks [2]. This contribution aims to incorporate the debate from media educators into the definition of data literacy. Additionally, other emerging literacy frameworks will be considered. In our method, a literature review, current literacies will be discussed in order to introduce the concept of literacy circles. Through this approach, an enhanced data literacy definition will consider frameworks beyond the computer science and engineering field.


Comment #61 Peter Pelz @ 2023-10-18 13:20

Based on the reviewers' feedback the decision was made not to accept the paper for a publication within ing.grid. The authors may choose to keep the preprint available or withdraw it.

Invited Review Comment #51 Anonymous @ 2023-09-08 12:02

The presented manuscript tries to discuss the expansion of literacy sciences to a more holistic model for application in engineering by adapting an already strong framework from media literacy. The authors gave a brief introduction to already published work and the context the manuscript will be included. Afterward, critical aspects and classifications of media and data literacies are discussed, with a strong focus on the upcoming arguments of the authors to build a simple model of literacies framework. This model is described in the last section. The conclusion sums up the statements of the authors.

Overall, the manuscript is well written in language and touches an important topic to be discussed scientifically as well application related. But there are several major issues which have to be addressed by the authors. 

Major findings:

  1. The introduction to the topic and the literature overview are not sufficient to understand the motivation of the author’s work. There are a lot more published discussions of this topic (maybe without the focus on engineering) in the available literature. The authors claim that they want discuss "... critique coming from the field of media education science...” but mainly only use one reference (GfM).
  2. A better preparation of the reader by giving more definitions of the used nomenclature and the differences between the discussed literacies (what is data? What is digital?) is necessary. There are some citations, but it is not always clear if these are the definitions the authors used in this manuscript or if this is just an example how one can define it. The chapter “terminology” certainly needs an expansion and a modified structure. A table would help to get a better overview of the author's terminology.
  3. The authors want to animate researchers from the field of media literacy to include other literacy frameworks in their research – “This question requires researchers to go beyond their own research domain and exchange their perspectives on research education among other researchers.” I certainly support this, but the authors itself limit their discussion to engineering. The discussion in this manuscript is limited to theoretical concepts and language. But no examples are giving to locate the arguments within the engineering sciences. One or two examples why this is a unique discussion for engineering or why the focus should be on engineering would be helpful. Especially because the authors already ask for “further interdisciplinary exchange”.
  4. The model seems to be very simple and does not show the relations between the different literacy frameworks. For a thorough discussion, it is necessary to explain the relations of at least two literacy frameworks in detail. Simplification is important for initial understanding, but in this case the simplification covers the important aspects of the model. This is also very important to answer the research question of the authors: “How can data literacy include contexts from other literacy fields (e.g. media literacy)?” What is the context from media literacy that can or should be included and is not already a logical intersection?

Minor findings 

  1. Line 36 to 39 – sentence doubled
  2. Line 40 – “on” should be “one”

Invited Review Comment #27 Anonymous @ 2023-05-25 01:15

The article tries to make an important case for Engineering Education based on developments in the field of literacy studies, more specifically media literacy and data literacy research. The use of language is consistent in most cases, but some revision is still needed (e.g. lines 24 and 39). Some rephrasing would be welcome in cases of definitions and especially in the abstract. The main argument seems to be that Engineering Education needs a framework for the teaching of data literacies that incorporate ethical and critical dimensions of both citizenship and engineering as a profession. The author borrows from studies in media literacies to make the point, but there is a whole plethora of previous, broader and deeper research and propositions about (data, media and general) literacy made in that direction that was not taken into consideration (examples are given at the end of the review). The basic distinction made in the field between literacies as a set of skills and literacies as social practices influenced by cultural, ideological, ethical and context-specific factors is well developed and connected with different views of what criticism may mean in this field and how it relates to the very skills-practices conundrum. There is also an important body of work on critical data studies that is fundamental to defining what critical data literacies should include. Agency and Ethics, moreover, are poorly defined although clearly relatable to reflexivity and agency in the direction aimed at in the article if better articulated. A well know problem in the field of literacy studies is that of how different metaphors (representing conceptual models) are often proposed (continua, hierarchies, circles, networks, dichotomies and so on) are often invoked, but usually in a less productive and consequential way in methodological terms, for lack of exploitation of the attributes of the metaphors themselves. The metaphor itself provides very limited heuristic advantage if its consequences to the conceptual strategy are taken for granted. Overall, the article makes a fair claim about the need to develop a conceptualization of data literacies that goes beyond a set of skills and incorporates ethical, critical, agential and cross-discipinary dimentions. However, the argument in its present elaboration stage falls short of advancing the claim. Neither of the two research questions made explicit in the article seem to have been effectively covered and most of the justifications and consequences of the claim may be relevant for a conceptualization of data literacies, but go far beyond, and come far before, the media literacy literature considered. As a contribution, I would suggest some of the items on the following list that speak directly to the same issues the author is trying to tackle:


Iliadis, Andrew, e Federica Russo. “Critical data studies: An introduction”. Big Data & Society, vol. 3, no 2,  2016, p. 1–7,

Kalantzis, Mary. “Critical literacies pedagogy”. Literacies, Cambridge University Press, 2012, p. 145–70.

Cope, Bill, e Mary Kalantzis. Multiliteracies : Literacy Learning and the Design of Social Futures. Routledge, 2000.

Data Pop Alliance. Beyond Data Literacy: Reinventing Community Engagement and Empowerment in the Age of Data. Data Pop Alliance, setembro de 2015,

Freire, Paulo, e Donaldo Macedo. Literacy: Reading the Word and the World. 1o ed, Routledge, 2005. (Crossref),

Gee, James Paul. “The New Literacy Studies”. The Routledge Handbook of Literacy Studies, Routledge, 2015,

Gray, Jonathan, et al. “Ways of Seeing Data: Towards a Critical Literacy for Data Visualizations as Research Objects and Research Devices”. Innovative Methods in Media and Communication Research, organizado por Sebastian Kubitschko e Anne Kaun, Palgrave, 2016, p. 227–51.

Pangrazio, Luciana. “Reconceptualising Critical Digital Literacy”. Discourse: Studies in the Cultural Politics of Education, vol. 37, no 2, março de 2016, p. 163–74. (Crossref),

Scribner, Sylvia, e Michael Cole. “Unpacking literacy”. Perspectives on Literacy, organizado por E.R. Kintgen et al., Southern Illinois Press, 1988, p. 57–70,

Street, Brian V. Literacy in theory and practice. Cambridge University Press, 1984.

Thomas, Sue, et al. “Transliteracy: Crossing divides”. First Monday, vol. 12, no 12, dezembro de 2007,

Archer, Margaret Scotford. Being Human the Problem of Agency. Cambridge University Press, 2000. Open WorldCat,

Emirbayer, Mustafa, e Ann Mische. “What Is Agency?” American Journal of Sociology, vol. 103, no 4, janeiro de 1998, p. 962–1023. CrossRef,

Kennedy, Helen, et al. “Data and Agency”. Big Data & Society, vol. 2, no 2, dezembro de 2015. CrossRef,

Peacock, S. E. “How Web Tracking Changes User Agency in the Age of Big Data: The Used User”. Big Data & Society, vol. 1, no 2, julho de 2014. CrossRef,

Reyman, Jessica. “User Data on the Social Web: Authorship, Agency, and Appropriation”. College English, vol. 75, no 5, 2013, p. 513.



Download Preprint

  • Published: 2023-01-24
  • Last Updated: 2023-04-27
  • License: Creative Commons Attribution 4.0
  • Subjects: Data Ethics, Data Literacy
  • Keywords: media literacy, data literacy, ethics, interdisciplinary research
All Preprints