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