This week, I decided to record how I used a highlighting pen to mark texts while I was reading Williamson, Bayne & Shay (2020) paper. where each column represent a page, and each mark represent approximately 3 lines of text. I used a traffic-light system to indicate how much texts were highlighted. This recording was inspired by the text-highlighting functionality of common e-reading software like Kindle. At a functional level, records like this provide a teacher some insights into what their students might think is important message in a prescribed reading. Similar to Kindle, collation of such data from a group of students allows features like “frequently highlighted text” to be highlighted for a reading activity.
However, as suggested by Williamson, Bayne & Shay (2020), datafication increases the risk of pedagogic reductionism as well as limiting the way a teacher see their students. If a teacher uses text highlighting as a parameter to measure students’ intellectual engagement, it also defines such behaviour as the model way a student should interact with a reading material. Teachers may be prompted to reinforce e-reading app as the “official” way or indeed approved way to read one’s course reading. Students might also be prompted to look good in their data by simply highlight most (if not all) of the text, gaming the system to generate an all-green pattern.
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.