This week I tried to analyse what data various platforms try to collect from users through cookies. Cookies are often described as the main source of profit for companies (van Dijck et al., 2018). What kind of software teachers might use in their teaching? Teachers should protect their students (McKinney de Royston et al., 2021). How teachers can think not only of platform effectiveness but of privacy issues too.
Visualization design choices: a teacher is in the middle of the graph. Different colours show what data about students can be provided to platforms by choosing to use one or another platform.
Finding 1: Teachers need to carefully assess what third-party platforms are used in the learning process. For example, if Coursera is used and promoted to students, a lot of personal data about students will be collected. Does a teacher who is often viewed in our society as a protector of students (McKinney de Royston et al., 2021) can do that?
Finding 2: educational platform ‘Coursera’ collects most of the personal data. It applies various principles of datafication and personalisation (van Dijck et al., 2018). Teachers do not need to fully rely on various educational online resources and need to assess the privacy regulations in each chosen platform.
The relationship between data and ‘teaching’.
This block helped me realise the relationship between lesson preparation and overall performance. Moreover, the number of various cookies I receive online from different websites. Besides, it helped me think about the responsibility I carry by offering students various online websites.
Furthermore, various creative data representations such as Internet cookies represented as simple eatable cookies are necessary because dashboards often impose limits (Williamson et al., 2020). Also, how each data visualisation choice can have a big impact on teaching. To make datafication effective teachers should collect data about their practices themselves because otherwise it can be associated with surveillance (Brown, 2020). Data and teaching values need to be aligned to make it efficient.
This block also helped me to realize the importance of platformization and data literacy in the relationship between data and ‘teaching’.
Platformization is becoming more and more popular (van Dijck et al., 2018). It worries a lot of students and parents due to focus on profit rather than educational achievements. At first glance, various free online resources seem appealing. However, the amount of personal data which is collected on online platforms is can be harmful. Datafication and personalisation should be followed by surveillance, privacy, data security, ethical and pedagogical foundations. This can be hardly found in nowadays online educational giants, such as Coursera.
Data literacy among teachers is undermined. Strong data literacy is essential and should be developed among educators (Williamson et al., 2020). Teachers need to know how to process and understand data (Raffaghelli & Stewart, 2020). Data literacy can help to reduce unknown unknowns. It needs to have in mind various societal, institutional, individual and contextual practices. To make data literacy learning to appeal, it needs to involve various visualisations, interactive, constructive and insightful suggestions for useful tools (Sander, 2020).
References
Brown, M. (2020). Seeing students at scale: How faculty in large lecture courses act upon learning analytics dashboard data. Teaching in Higher Education, 25(4), 384-400.
McKinney de Royston, M. et al. (2021). “I’m a Teacher, I’m Gonna Always Protect You”: Understanding Black Educators’ Protection of Black Children. American educational research journal, 58(1), pp.68–106.
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), pp.435–455.
Sander, I. (2020). Critical big data literacy tools—Engaging citizens and promoting empowered internet usage. Data & Policy, 2, pp.Data & Policy, 2020, Vol.2.
van Dijck, J., Poell, T., & de Waal, M. (2018). Chapter 6: Education, In The Platform Society, Oxford University Press.
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.
One reply on “Teaching with data”
Great to see you continue your exploration of cookies here, and that the data visualisation tasks have surfaced some useful insights for your teaching.
Drawing on the literature is a real strength of this summary, where you make some key connections between the increasing use of data and its impact on teaching practices.
‘To make datafication effective teachers should collect data about their practices themselves because otherwise it can be associated with surveillance (Brown, 2020)’
This sounds like a useful approach, however, I wonder how many teachers would be in a position to undertake, and understand, these kind of technical skills. Your conclusions concerning the need for data literacy are well made, however, but I also wondered if you saw a tension between ‘critical awareness’ *of* data and ‘technical skills’ *with* data, and whether both these perspectives can really be achieved.