Internet Learning Volume 3, Number 2, Fall 2014 | Page 56

Internet Learning Volume 3 Number 2 - Fall 2014
Using Early Warning Signs to Predict Academic Risk in
Interactive, Blended Teaching Environments
Julie Schell, Brian Lukoff, Cassandre Alvarado
Introduction
Growing evidence in higher education
suggests that interactive teaching
leads to more robust student
learning outcomes than lecture-based instruction
(see Crouch & Mazur, 2001; Hake,
1998; Lasry, Mazur, & Watkins, 2008; Nicol
& Boyle, 2003). This phenomenon transcends
geographic and disciplinary boundaries,
and institutions across the globe are
investing in initiatives to support interactive
pedagogical models (Becerra-Labra,
Gras-Marti, & Torregrosa, 2012). As online
learning becomes more accessible, interactive
teaching often includes web-facilitated
and blended learning (Allen & Seaman,
2014) to drive engagement. As a result, instructors
can drive student success more effectively
in and out of class.
In what seems to be universal pushes
for technology-driven educational reform
there is one reality that is under-studied and
under-acknowledged: Even in classes where
master instructors use interactive methods
with the most effective online tools, there
remain students who do not succeed. This
is the research problem of this study: even
when state-of-the art pedagogies and technologies
are used, there are still students
who do not succeed. For example, there still
exist students who do not exhibit sufficient
levels of gain in conceptual understanding
of subject matter, academic performance,
engagement in course activities, and beliefs
and attitudes about academic competence.
In this paper, we define those underachieving
students in interactive classrooms as atrisk.
As educational reformers continue to
emphasize interactive, blended learning as
a critical element of change in higher education,
the lack of extant effort to address
the needs of at-risk students in such environments
is an important research problem.
Is there something educators can do to help
these at-risk students? That is the underlying
question of this study.
In the NMC Horizon Report 2014
Higher Education Edition (Johnson et al.,
2014), the authors lament that higher educators
have not yet “embraced” the potential to
use extensive educational data generated by
students to improve college student success.
In this paper, we demonstrate how we used
on and off-line data to chart a path early on
in the semester for improving course-level
student success in a blended, flipped physics
classroom. The purpose of this study
is to offer an evidence-based process for
identifying characteristics correlated with
student academic underachievement at the
course level in blended, interactive teaching
environments that qualify as early warning
signs and to recommend early intervention
points. We hypothesize that students’ beliefs
that they can reach a high level of achievement
in a course, defined as their self-reported,
perceived academic self-efficacy,
will have a strong relationship with later
course performance, as will a number of
other simple measurements that are available
in the first few weeks of instruction. We
explore this hypothesis with the purpose of
presenting a simple process that instructors
can use to identify at-risk students in inter-
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