Internet Learning Volume 3, Number 2, Fall 2014 | Page 58

Using Early Warning Signs to Predict Academic Risk in Interactive, Blended Teaching Environments that one can successfully complete a task (Bandura, 2003). Theories of self-efficacy suggest that the courses of action that individuals take in their lives are driven by their beliefs about their own abilities. In particular, researchers use self-efficacy to explain academic, career, and life decisions and outcomes (Lent, Brown, & Larkin, 1984; Multon, Brown, & Lent, 1991). The basic theory suggests that an individual’s perceptions of their own ability or competence (i.e., their perceived self-efficacy), regardless of accuracy, will lead them toward specific courses of action and not others. The present study was designed with self-reported perceived academic self-efficacy as a unit of analysis, whereby academic self-efficacy is defined by students’ beliefs about their academic competence (Pajares, 1996; Pajares & Miller, 1994). In a review article, Pajares (1996) documented the literature demonstrating positive relationships between self-reported academic self-efficacy, academic performance, and choice of college major. In particular, Hackett and Betz (1989) suggested that self-reported academic self-efficacy is more predictive of mathematics interest or choice than actual performance (Hackett & Betz, 1989). We used the theory of self-efficacy to guide our investigation into early predictors of academic success or the lack thereof. Peer Instruction One interactive teaching method that has gained international prominence is Peer Instruction, developed by Eric Mazur at Harvard University in the 1990s (Mazur, 1997). Peer Instruction is often used with the web-facilitated pedagogy, Just-in-Time Teaching, to create a “flipped classroom,” which incentivizes students to prepare before class by completing online pre-class assignments that require them to interact with the subject matter and reflect on their understanding prior to the class period. Instructors then use feedback from students’ pre-class assignments to plan class time. During class, instructors pose a series of questions often, but not always, using web-facilitated learning tools, such as classroom response systems. These questions pushed to students through technology serve to elicit, confront, and resolve (ECR) their misunderstandings and misconceptions (Heron, Shaffer, & McDermott, n.d.). In Peer Instruction, teachers use short, conceptually based questions called ConcepTests to facilitate the ECR technique (Mazur, 1997). The implementation of interactive teaching throughout the course for this study, included facilitating Peer instruction using a cloud-based classroom response system called Learning Catalytics. Students use their own devices (smartphones, tablets, or laptops) to interact and response to the questions. While Peer Instruction does not require the use of technology, the basic protocol for in-class questioning with Peer Instruction using a web-based response system is as follows: 1. Instructor gives a mini-lecture on selected concept. 2. Instructor poses a question using Learning Catalytics, which delivers the question to each student’s personal device. 3. Students are given time to think individually about their response. 4. Students submit first-round responses using their personal devices. 5. Instructor reviews first-round feedback and data using an instructor-only dashboard through Learning Catalytics. 6. Instructor uses Learning Catalytics to pair students with someone with a different answer. The instructor 57