Big Data vs Small Data

 I thought that for my third blogpost for the week I would take a look at one of our readings for the week. While I am very much a beginner to the process I am looking forward to exploring data analytics more in coming courses within the ISLT program. Thus, my interest was peaked by several of the readings for this week in class, especially the one from Watson, Wilson, Drew and Thompson on Small Data in the educational analytics process. The authors argue that the use of "big data" in the learning process has ultimately been a failure.

For the authors the distinction between big and small data comes in the number of students analyzed and the attention to detail given to each student. The big data process focuses on large numbers of students looking for overall patterns in engagement. This study however, focuses only on one student and uses the data on that students interaction with an online learning environment to come to conclusions on its effectiveness.

Especially interesting to me in regards to looking at the individual under this level of scrutiny is that the authors are not trying to find a "typical" student and from that generalize to larger conclusions. Instead, the authors even suggest that by focusing on the individual they can craft narratives that "approach the complexities of real life". To me this kind of an approach gets at the learning process at it occurs in a much better way than just analyzing general trends in large groups of learners.

For this study the authors chose one student who initially struggled with an online blogging assignment. They trace the feedback given to the student and the way that the student responded to it. They also note the student's recognition that online learning opens them up to greater scrutiny from the larger group. 

One particular success the authors see in small data vs large is the distinction between the feelings that the student were having around their learning and the actual result. By focusing minutely on the students process of going through the materials the authors were able to craft a narrative of the student's growth and development that was not reflected either in the actual evaluated results of the modules used or in the student's own reflections on that process. Thus, the authors conclude that their method gave them access to the learning process in a way that big data never could.