Make an Update: Describe and evaluate an innovative assessment approach or technology.

An innovative assessment approach, proposed by Bill Cope in his video on learning analytics, focuses on the use of data mining to assess students. The data produced by educational environments, specifically the data generated by e-learning platforms such as Scholar, support instructors in evaluating students in a number of ways. For example, students who are not posting regularly on discussion forums can be identified and remedial action can be taken to enhance motivation. At a more complex level, it can go as far as identifying click patterns indicating boredom (Bienkowski et al., 2012).

Although data mining seems, at first impression, to be an approach that is primarily used in higher education, there are numerous good examples of its use in K-12 online education. A study by Hung et al. (2012) used this innovative approach to assess the engagement of students in an online program as part of the course evaluation process. Data mined included average frequency of logins per course, the average frequency of tab accessed per course (if the course was organized using “tabbed” navigation), and many others. These types of assessments whether used to assess students or on a broader level, to evaluate courses are cost-effective, less intrusive, and quicker than administering traditional assessments. Despite the benefits of data mining, there are some drawbacks. Platforms such as Facebook mine data to target ads that we may want to see or not! This makes me wonder about how data mining in education could potentially be misused. For example, could academic views be analyzed to “profile” students according to political-ideological beliefs? Could this then be sold? Should students then be fully informed about how these huge amounts of data are being used? There are many questions that we need to reflect on as data mining is increasingly being used in the educational sphere.

Click here for an article on how Facebook is using data mining. 

Click here for a video on the importance of data mining in education

References

Bienkowski, M., Feng, M., & Means, B. (2012). Enhancing Teaching and Learning Through Educational Data Mining and Learning Analytics: An Issue Brief. Retrieved from the US Department of Education website: https://tech.ed.gov/wp-content/uploads/2014/03/edm-la-brief.pdf

Hung, J.-L., Hsu, Y.-C., & Rice, K. (2012). Integrating Data Mining in Program Evaluation of K-12 Online Education. 15(3), 27–41.