Posts by reyjunco:
Today at the EDUCAUSE 2013 conference in Anaheim, I unveiled new research on textbook analytics. Textbook analytics are an emerging subcategory of learning analytics, which is the use of student-generated data to predict learning. These predictive analytics promise the ability to identify at-risk students and to help faculty adjust their teaching in real-time.
However, up to now, learning analytics projects have collected limited data. Typical learning analytics systems are tied to Learning and Course Management Systems (LCMSs) and collect data like number of logins, number of discussion posts, etc. Additionally, research showing the predictive ability of learning analytics is limited because these studies relate grade-earning activity with course grades. In other words, students earn grades for discussion posts on LCMSs, so of course number of posts would be related to student course grades.
Textbook analytics provide information on how much students are reading and how they are engaging with their digital textbooks. CourseSmart has developed a textbook analytics platform that unobtrusively calculates an Engagement Index based on how students are interacting with their textbook.
CourseSmart provided data on 233 students including their Engagement Index scores, their background characteristics, and their final course grades. Using a blocked linear regression controlling for gender, race/ethnicity, and prior academic achievement (student transfer GPA), I found that the Engagement Index was significantly predictive of final course grades. In fact, the Engagement Index was a stronger predictor of final course grades than prior academic achievement (see figure below), which has been shown in previous research to be the strongest single predictor of student success.
What was especially interesting was that highlighting was related to student course outcomes, although not in the way that you might think. Those students who were in the top 10th percentile of number of highlights had significantly lower course grades than students in the lower 90th percentile. This is congruent with previous survey research showing that low-skill readers highlight more text and more often than high-skill readers. These results show that perhaps these types of analytics can identify students who need help with their reading skills.
Textbook analytics open up possibilities for real-time and unobtrusive formative assessment for faculty. With a single index, instructors can gauge how much and how well students are engaging with their textbooks, identifying at-risk students before they ever turn in a gradable assignment or interact on the LCMS. Plus, textbook analytics open up possibilities for new methods to research student reading and its relationship to student outcomes.
You can read more about this in the CourseSmart research report : Evaluating How the CourseSmart Engagement Index Predicts Student Course Outcomes
Student affairs professionals: I need your help for my next book, Engaging Students through Social Media: An Evidence-Based Approach for Student Affairs being published by Wiley/Jossey-Bass. I’m looking for examples of how you are using social media in your functional areas. Successes and challenges are both welcome! Feel free to post your story in the […]
I am delighted to announce that later this semester, I will be joining the faculty of the Purdue University Libraries as an associate professor. At Purdue, I will focus on emerging technologies in education with a special focus on the first year experience. If you don’t already know about the great work happening in educational […]
If you are a regular reader of this blog, you likely already know that there is a growing body of research that examines how college students use Facebook and the outcomes of such use. For instance, researchers have examined how Facebook use is related to various aspects of the college student experience including learning, student […]
On Monday, the Federal Trade Commission (FTC) published Mobile Apps for Kids in which they reported the results of their recent survey of how well mobile apps for kids conform to Children’s Online Privacy Protection Act (COPPA) requirements. The results were alarming: 59% of apps transmitted the mobile device ID (which includes among other things the app name, […]
My most recent paper on multitasking, In-class multitasking and academic performance, has uncovered some interesting results. I conducted a survey of 1,839 college students and asked them how often they multitask during class by using Facebook, texting, emailing, searching for content not related to the class, IMing, and talking on the phone. I also collected students’ actual overall […]
My friends over at Project Information Literacy have just released this infographic to summarize their recent research on how college students find and use information. Data in this infographic come from PIL’s publications Balancing Act: How College Students Manage Technology While in the Library during Crunch Time and Truth Be Told: How College Students Evaluate and Use […]
Recently, Kaplan Test Prep released data from a survey showing how college admissions officers check applicant profiles in order to make admissions decisions. This isn’t a new phenomenon: since 2008, I’ve been answering questions about whether residence life, judicial affairs, and other university departments should monitor their students’ Facebook accounts. Here are some reasons why […]