In a previous post I discussed the Open Homework System (OHS) by Lalonde. I identified the challenge of buy-in from institutions, staff, students, and technical support staff. I imagine that the most relevant data collection to clarify that scope would stem from the largest group of stakeholders: students. Prompting the inquiry of this line from the movie “Field of Dreams”: If you build it, they will come.
Prinsloo and Slade discuss the use of “harvesting and analys[ing]” (Prinsloo & Slade, 2014, p. 306) of data for determining things like enrolment and staffing. But there is caution to simply using data. A personal example of this is in the program that I am enrolled in: It is advertised as having the option to vote on five courses, with the top 3 chosen being taught. Students went into the program with this thought, and having reviewed the options, had their picks and were ready to vote. They soon found out that the school had already chosen the three courses they were going to offer. According to the program, this was based on previous years of data and previous student choices. Without the curiosity that human nature would prompt, an assumed dependence on simply data caused students to no longer have the option to have their intended vote. This may raise the moral question of false advertising and using strictly data to inform decisions that Prinsloo & Slade discuss throughout their article.
Marsh et al. share that “data-driven decision making (DDDM)” (p. 2) comes from the viewed success of industry and manufacturing. In education, the user must also consider that there are countless ways to analyze data sets (p. 3), while it can be used to add to the framework of education through the triage that Prinsloo discusses, it must be analyzed effectively and thought through with morals and ethics and psychology to determine students’ best interest.
My prime take-away is that we cannot rely strictly on data alone. This is akin to relying on AI answers alone without thought or further curiosity. Data or AI lack the human characteristics of navigating data and having informative inquiry to the results. However, data is not as scary as it may seem, and can be quite valuable (Zettelmeyer, 2015).
Prinsloo, P., & Slade, Sharon. (2014). Educational triage in open distance learning: Walking a moral tightrope. The International Review of Research in Open and Distributed Learning, 15(4), 306–331.
Marsh, J. A., Pane, J. F., & Hamilton, L. S. (2006). Making Sense of Data-Driven Decision Making in Education. 15.
Zettelmeyer, F. (2015, May 1). A Leader’s Guide to Data Analytics. Leadership & Careers. https://insight.kellogg.northwestern.edu/article/a-leaders-guide-to-data-analytics/