COMMENT

One of the major drawbacks of legacy assessment systems is that the feedback comes too late to be of much lasting benefit to the student. If a student completes a paper and submits it, only to learn that he or she missed an essential concept, it is too late to do anything about it. Indeed, I suspect that many online learners do not bother reading all of the feedback provided to them. After all, unless the feedback is relevant to their future progress and academic success, why would students care?

One approach to resolving this problem is by way of a peer review process in which fellow students read over a draft of the paper and offer helpful feedback on it. This can be a mutually beneficial reciprocal process fostering metacognition, or thinking about another student's thinking (University of Florida, n.d.). Indeed, through conducting reviews, the student can even gain insights to apply back to his or her own draft. In addition, the peers collaborate to support each other's learning. Research has found, too, that online students tend to utilize peer review more often when concrete recommendations for improvement are offered (Van der Pol et al., 2008). In my own experience as an instructor, it is frequently the case that I find myself recommending to my online students that they provide more concrete details and examples to support their ideas. If this recommendation comes across during peer review, I suspect that the final product can be much more academically robust and meaningful.

Here is a video on using the Peer Review tool in Canvas:

UPDATE

Big data offer all sorts of opportunities for enhancing online education; however, I remain cautious about overreliance on big data for crafting student learning experiences. Big data can, for instance, enable universities to make predictions regarding which students will succeed in their course or their degree program. To boost retention, universities can target those students who are struggling early on, before the students completely give up. Whatever support is needed -- additional counseling or tutoring, remedial coursework, etc. -- can then be offered and the student's progress further monitored (Gutieerez, 2019). In some of my current online classes, Civitas is used to provide instructors with rich data regarding students in their classes, including degree of involvement in the course. Students with low participation can then receive outreach from the instructors with offers of encouragement and support.

Here is a brief video on the Civitas Student Success Platform as utilized by Lone Star College in Texas:

Another way big data can be utilized is to offer students individualized online learning expreriences tailored to their particular abilites, skills, and learning styles (Guttierez, 2019). In that way, the path can be paved for students to experience optimal success in mastering new concepts and competencies.

In both cases, however, I remain a bit cautious. For one thing, it can become easy for instructors to rely largely on the big data stream to guide how they interact with and support students. In my own experience, a weekly journal assignment enables me to guage where each student is in the course, and what challenges he or she may be experiencing, and in a far more comprehensive way than Civitas does. In regard to providing individualized learning, we have certainly come a long way (fortunately) from the "lecture at the blackboard" one-size-fits-all approach to learning. But at some point, I also am hesitant about directing learning toward identified learning styles. Does that mean the student is missing out on the challenges of learning in other ways? For instance, I have many online students in a course with a lab component who complain about having to follow written instructions; they explain that they are visual learners, and would much prefer to see a video of the lab and follow along. But is doing so really benefitting students in the long run? Or is the task of having to learn in varied ways preparing them more effectively for long-term success, in the workplace and everyday life in addition to the classroom?

References

Guttierez, D. (2019, November 28). Big data & higher education: How are they connected? Retrieved from https://insidebigdata.com/2019/11/28/big-data-higher-education-how-are-they-connected/

University of Florida (n.d.). Designing effective peer and self assessment. Retrieved from https://citt.ufl.edu/resources/assessing-student-learning/designing-effective-peer-and-self-assessment/

Van der Pol, J., Van den Berg, B. A. M., Admiraal, W. F., & Simons, P. R. J. (2008). The nature, reception, and use of online peer feedback in higher education. Computers & Education, 51(4), 1804-1817.