Reflection on the entire data visualisation task

Data visualisation to me, before the course, was the big unknown. I only came across the theme of Big Data in the IDEL course and found it daunting and complex yet fascinating and vitally important for what lies ahead in education.

Having said that, I somehow immediately connected with the topic of data through my data visualisations over the past twelve weeks on the Critical Data and Education course. 

I noticed right from the beginning that I had to carefully select a weekly topic to draw a connection to the block’s overarching theme and to manage the data recording as the week went on. Over the course’s whole length, I used a journal, where I maintained a record of my chosen data for the week. On the one hand, it was convenient since I always had it with me and it allowed me to note down details; on the other hand, my data for weeks like week 5 was not falsified since I had not used a tech device.

While it was sometimes challenging to keep up with the collecting process, creating the visualisation was always enjoyable, even though it could be time-consuming. I appreciated the encouragement to be creative and felt inspired by this creative freedom. This experience made the learning on the course authentic and allowed me to set theory and practice in relation to another constantly.  

I learned some valuable lessons in the area of datafication and in connection with the three topics: learning, teaching, and governing with data. Looking back, I notice the broad scope of my data collections, ranging from personal to professional and academic data. 

During the first block ‘learning’ with data, I focused on considerably personal data: my commute, my heart rate and access to my personal devices. I gradually realised how many thoughts flow into data representation, such as the use of colours, shapes and size, and the choice of medium and the significance of the legend and explanation. 

I valued having ‘Dear Data’ (Lupi and Posaveca, 2016) as a physical copy since I liked to browse through on weekends for the delight of their beautiful visualisations. I was fascinated when I learned that I already marvelled at one of Lupis’ visuals in a Milan roastery over a year ago (see: Small coincidental discoveries like this and the data collections of the first block made me realise how present datafication already is in my daily life, yet how little I am aware of it. Reading about learnification (Biesta, 2012), learning personalisation (Thompson and Cook, 2017), and learning analytics (Williamson, 2017) shaped my understanding of how impactful data can be on learning. I increasingly realised that one’s skills in data literacy need improvement and continuing development in order to have personal agency (Tsai et al., 2020). Through the visualisation of my heart rate, I explored the field of learning analytics in the context of emotion and body (Knox et al., 2020), which is such an exciting and intriguing area of increasing importance, yet one that has to be researched further. 

Within block 2: ‘teaching’ with data, I moved on to my professional life, analysing my teaching through the lenses of Bloom’s Taxonomy and Gardner’s Multiple Intelligences, finishing off with a week of data on self-care as work-life balance. By creating the visualisations for this block, I understood that clarity for the ‘reader’ of a visualisation comes with simplicity and transparency of my display and description. Having already developed a better understanding of data in learning, I could build on this knowledge and draw close attention to elements of my teaching practice. Monitoring elements of my teaching inspired me to personalise my students’ learning experience (van Dijck et al., 2018). Once again, I realised how time-intensive it could be when teachers want to collect and use data for their students’ purpose. However, in this context, it emerged again how essential it is that educators put time and effort into acquiring the skills and questioning their handling of data in a professional educational context (Raffaghelli and Stewart, 2020). Teachers’ data literacy skills (Williamson et al., 2020) are critical before they can then move on to coach their students in data security and data literacy. I am concerned that teaching staff can easily be left behind and is at risk of losing agency and the right of co-determination to govern with data in an institutional context. 

Throughout the third block ‘governing’ with data, I collected data on gaming, data flaws and technology in my teaching practice. From the personal and professional level, I now progressed to what felt like the meta-level, which offered me the chance to gain insight into central concepts and theories in critical data and education. In hindsight, this was the most challenging topic since ‘governing’ often seems very distant from daily learning and teaching. Reading into the questions of accuracy (Anagnostopoulos et al., 2013), accountability and transparency (Young, 2017; Williamson, 2017) of data emphasised the significance of my data visualisation. What commenced as a broad-ranging examination of data in my ‘Lebenswelt’ steadily allowed me to change my perspective on the process of data collection, existing data sets and interpretation of data within context.

Moreover, it allowed me to reflect upon the previous themes in the course. Looking back, my instant thought was that I would have chosen different themes for my first two weeks because they seem quite trivial. Nonetheless, maybe it was this banal approach that got me into data visualisations itself! 

Overall, I believe I was able to develop a good understanding of data visualisations in general and how compelling or misleading they can be. Data literacy seems to be more important than ever, and I feel that we as educators are at a tipping point. Data in education needs our full attention if we want to be able to not only keep up with the fast-evolving datafication and data analytics but also participate in the discussion of data storage, usage and protection.


Anagnostopoulos, D., Rutledge, S.A. & Jacobsen, R. (2013). Introduction: Mapping the Information Infrastructure of Accountability. In, Anagnostopoulos, D., Rutledge, S.A. & Jacobsen, R. (Eds.) The Infrastructure of Accountability: Data use and the transformation of American education.

Biesta, G. (2012). Giving teaching back to education: responding to the disappearance of the teacher. Phenomenology & Practice, 6(2), pp. 35-49.

Knox, J., Williamson, B. & Bayne , S. (2020) Machine behaviourism: future visions of ‘learnification’ and ‘datafication’ across humans and digital technologies, Learning, Media and Technology, 45:1, 31-45, DOI: 10.1080/17439884.2019.1623251

Lupi, G. & Posavec, S. (2016). Dear data, London] UK: Particular Books.

Raffaghelli, J.E. & Stewart, B. 2020. [Centering complexity in ‘educators’ data literacy’ to support future practices in faculty development: a systematic review of the literature], Teaching in Higher Education, 25:4, 435-455, DOI: 10.1080/13562517.2019.1696301

Thompson, G. & Cook, I. (2017). The logic of data-sense: thinking through Learning Personalisation, Discourse: Studies in the Cultural Politics of Education, 38:5, 740-754, DOI: 10.1080/01596306.2016.1148833 

Tsai, Y-S. Perrotta, C. & Gašević, D. (2020). Empowering learners with personalised learning approaches? Agency, equity and transparency in the context of learning analytics, Assessment & Evaluation in Higher Education, 45:4, 554-567

van Dijck, J., Poell, T., & de Waal, M. 2018. [Chapter 6: Education](, In The Platform Society, Oxford University Press

Williamson, B. (2017). Big Data in Education: The digital future of learning, policy and practice. 55 City Road: SAGE Publications Ltd

Williamson, B.,Bayne, S., Shay, S. 2020. [The datafication of teaching in Higher Education: critical issues and perspectives]( Teaching in Higher Education. 25(4), pp. 351-365.

Young, H. (2017). Knowledge, Experts and Accountability in School Governing Bodies. Educational management, administration & leadership, 45(1), pp.40–56.

Leave a Reply

Your email address will not be published. Required fields are marked *