Abstract
Every time that a student uses the internet on a school-issued computer, a trail of data about their online learning experiences is created. Until recently this data has largely gone unnoticed for educational purposes. This chapter will explore how research into the use of student online behavior data can be used to improve teaching and learning in digital environments. Techniques for the collection and analysis of targeted online learner analytics (TOLA) will be presented along with the findings for how TOLA impacted the teaching and learning process of real classroom teachers. The powerful and new form of data has the potential to disrupt the status quo of education, and this chapter will take a research-based look at that future.
TopIntroduction
There has never been a time in the history of education when so much information about student online learning behavior has been collected. Every time a student browses the internet, accesses online content, Googles a question or types in a Google doc, a record of activity is created. This activity is essentially a descriptive pathway of learning that is marked with the breadcrumbs of student internet browsing data. Unfortunately, much of this valuable data about student online learning experiences is not being utilized for instructional purposes.
The field of learning analytics has made some strides in helping educators make sense of this under-utilized data, but by in large learning analytics has had little impact on K-12 public education. Analytics has not had the transformative and disruptive impact on education as it has had in other fields of work.
This chapter will explore the groundbreaking potential of Targeted Online Learner Analytics (TOLA) in the design of instruction that optimizes student learning. Two research studies will be presented. Both studies looked to understand how information about student online activities could affect change within schools. Insights gained from the studies will be explored and a vision for how TOLA has the potential to disrupt the educational setting will be presented.
Key Terms in this Chapter
1:1 Initiative: A program in which every student is issued a mobile learning device such as a laptop, iPad or Chromebook.
Instructional Design: A process of analyzing the learning needs of students through the use of formative practices as part of the Instructional-Evaluation Design Theory to develop a plan to address the needs of the students and meet instructional goals (Reigeluth & Chellman, 1999 AU32: The in-text citation "Reigeluth & Chellman, 1999" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. ; University of Michigan, 1996 ).
Instructional Evaluation: A component of the Instructional-Evaluation Design Theory that relates to “the process for evaluating instruction, (summative and formative)” (Reigeluth & Chellman, 1999 AU33: The in-text citation "Reigeluth & Chellman, 1999" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. , p. 8).
Instructional Planning: A component of the Instructional-Evaluation Design Theory that relates to “the process of creating the instructional plans” (Reigeluth & Chellman, 1999 AU34: The in-text citation "Reigeluth & Chellman, 1999" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. , p. 8).
ThinkingApp: A Chrome extension that enhances the functionality of the Chrome browser by allowing for the collection, review, and submission of student-online-learning behavior associated with a specific online learning experience.