Engaged Learning
1
The Engaged Learning Index: Implications for Faculty Development
Laurie A. Schreiner
Azusa Pacific University
Michelle C. Louis
Azusa Pacific University
Student engagement is a construct that has received considerable attention in higher
education research because of its relationship to student learning (Carini, Kuh, & Klein, 2006;
Cross, 2005), its potential connection to student persistence (Milem & Berger, 1997), and
because it serves as an indicator of institutional effectiveness (Shulman, 2005). If postsecondary
educators accept Shulman’s premise that “learning begins with student engagement” (p. 38), then
methods for ascertaining the extent to which students are engaged in the learning process can
provide helpful feedback for faculty who wish to make an impact on student learning.
National surveys of faculty developers indicate that the largest programming need is for
learning-centered pedagogical methods, yet Sorcinelli, Austin, Eddy, and Beach (2006) note that
there are few measures to assess whether such programming efforts have successfully affected
students’ engagement in learning. While broad indicators of student engagement such as the
National Survey of Student Engagement are available at the institutional level, brief but reliable
and valid assessments of students’ engagement in learning are not readily available to faculty. In
a search of the existing literature, only one measure of learning engagement was found that was
accessible to faculty (Handelsman, Briggs, Sullivan, & Towler, 2005). However, this measure
assesses engagement only at the course level and its psychometric properties thus far are based
on a single institution.
In addition, many of the existing approaches for assessing student engagement in learning
focus solely on behaviors, while most researchers agree that academic engagement is a
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multifaceted construct (Bean, 2005; Fredericks, Blumenfeld, & Paris, 2004; Handelsman et al.,
2005). The Engaged Learning Index (Schreiner & Louis, 2006) was developed to extend beyond
behavioral indicators of engagement by also including psychological components in its
assessment of student engagement in the learning process. The purpose of the current study is to
connect what has been learned from research conducted across multiple large national samples
using the Engaged Learning Index to practices that can inform the faculty development process
and provide helpful, immediate feedback to faculty
Conceptual Framework
The advent of the National Survey of Student Engagement (NSSE) in 2000 provided a
means for assessing engagement in a more intentional and empirical way and dramatically
increased the visibility of the construct of student engagement within the field of higher
education. As a result, colleges and universities that use this instrument are gaining an
understanding of the levels of engagement within their first-year and senior students and are
provided with practical ways of supporting and encouraging such engagement. The campus
reforms that have occurred because of NSSE’s visibility and the research it has spawned have
been a valuable contribution to American higher education.
An examination of the items and scales within NSSE (Kuh, Hyek, Carini, Ouimet,
Gonyea, & Kennedy, 2001; National Survey of Student Engagement, 2007), as well as an
exploration of the conceptual framework of the instrument (Kuh, 2003b), reveals that its
intention is to measure “the extent to which students are engaged in empirically derived good
educational practices and what they gain from their college experience” (p. 1). Although recent
efforts have been made to assess student investment in deep learning (NSSE, 2005, 2007),
Nelson Laird, Shoup, Kuh, and Schwartz (2008) note that “the NSSE survey was not specifically
Engaged Learning
3
designed to assess certain precursors to deep approaches to learning, such as student motivation
for learning” (p. 481). The focus of this instrument remains centered on measuring student
behaviors indicative of engagement and the effective educational practices that support such
behaviors. The intent is that these indicators of student engagement can serve as a proxy for
institutional quality.
The use of the term “engagement” in NSSE is synonymous with Astin’s (1984) term
“involvement” in his original articulation of student involvement theory. Although Astin defines
student involvement as “the amount of physical and psychological energy that the student
devotes to the academic experience” (p. 298), his focus is primarily on the behaviors in which
the student engages: participating in campus organizations, interacting with faculty and peers,
attending campus events, and spending time studying, for instance. He articulates a deliberate
choice to focus on the behavioral components of involvement rather than the motivational
components, noting that “it is not so much what the individual thinks or feels, but what the
individual does, how he or she behaves, that defines and identifies involvement” (p. 298).
Bean (2005) has asserted that this view of involvement solely as behavior does not
provide a complete picture of student engagement; while the behavioral component is necessary,
it is not a sufficient definition of engagement. As he notes, “[p]articipating in events without
committing psychological energy to them indicates that they are unimportant to the student and
thus ineffectual in changing the student…. Behavior without thought is not likely to lead to the
gains associated with engagement” (pp. 2-3).
As a result of this need to expand the conceptualization of student engagement in the
learning process to include psychological factors, the Engaged Learning Index (ELI, Schreiner &
Louis, 2006) was developed to measure cognitive, affective, and behavioral components of
Engaged Learning
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engaged learning (Fredericks, Blumenfeld, & Paris, 2004), drawing on multiple disciplinary
perspectives to do so. Grounded in the motivational model of Ryan and Deci’s (2000) selfdetermination theory, the ELI incorporates concepts from the literature in psychology and higher
education, such as flow (Csikszentmihalyi, 1975), mindfulness (Langer, 1997), and deep learning
(Tagg, 2003). The resulting construct of engaged learning is thus conceptualized as “a positive
energy invested in one’s own learning, evidenced by meaningful processing, attention to what is
happening in the moment, and involvement in learning activities” (Schreiner & Louis, p. 9).
The conceptual framework upon which the Engaged Learning Index is grounded is Ryan
and Deci’s (2000) self-determination theory. Based on the construct of intrinsic motivation, this
theory postulates that individuals whose motivation is authentic, or in Baxter-Magolda’s (1999)
term, self-authored, are more interested, excited, and confident as they approach a task, which
then produces higher levels of creativity and persistence within the task, as well as better
performance (Sheldon, Ryan, Rawsthorne, & Ilardi, 1997). Even when controlling for preexisting levels of self-efficacy, these persons experience greater success, “heightened vitality”
(Ryan & Deci, 2000, p. 69), and an enhanced sense of well-being. Self-determination theory
captures the motivational impetus for engagement that has been missing from behavioral models,
such as those represented by Astin’s (1984) involvement theory.
The cognitive and affective elements of engagement that have been incorporated into the
model of engaged learning in this study derive from Csikszentmihalyi’s (1975) concept of flow
and Langer’s (1997) articulation of mindfulness. Flow is often described as an energized, alert
mental state when one becomes immersed in challenging activities that are of interest. This
heightened attention and energy level result when a person is optimally challenged, that is, when
the task presents an opportunity for a person to stretch beyond his or her current performance but
Engaged Learning
5
not beyond one’s capability (Csikszentmihalyi, 1990). Langer’s (1997) construct of mindfulness
adds another dimension to engagement with its emphasis on psychological presence in the
current moment and its focus on novel distinctions. Mindful learning occurs when students
notice what is new or different in the surrounding environment or in the task at hand. This
novelty captures their attention as they attempt to distinguish the new from what they already
know. In Langer’s description of mindfulness, there is a sense of active involvement, high
curiosity, and a particular quality of attention that keeps the learner firmly situated in the present.
Mindfulness also involves perspective-taking and making the material personally meaningful,
both of which lead to the deep learning (Tagg, 2003) that tends to have the most significant and
lasting impact on students’ lives.
Deep learning (Biggs, 1987, 2003; Tagg, 2003) has been described as an approach to the
learning process which focuses on meaning making. In contrast to a surface approach which
relies on rote memorization and focuses on earning a grade or passing a test in order to avoid
failure, deep approaches to learning encourage students to make connections and formulate
personal meaning in the learning process. Making connections to previous learning, to learning
in other courses, and to aspects of students’ personal lives promotes significant learning that lasts
beyond an individual course. Evidence of such learning can be seen in students’ use of strategies
such as discussing ideas with others, asking questions for deeper understanding, applying
knowledge to real-world situations, and integrating concepts with prior learning.
In creating the Engaged Learning Index we also acknowledge that behaviors can be an
indication of students’ psychological engagement in an activity. Thus, Astin’s (1984) concept of
involvement is represented in the instrument by items that focus on active participation in class
discussions and in asking questions of professors during class. The resulting multifaceted
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construct of engaged learning encompasses both the physical and psychological energy to which
Astin (1984) originally referred in his articulation of student involvement.
Methods
Data Sources and Sample
The purpose of the present study is to connect what has been learned from the research
conducted on the Engaged Learning Index (ELI; Schreiner & Louis, 2006) across multiple
undergraduate student samples to implications for how faculty development programs might
encourage and measure the effects of teaching practices that facilitate engaged learning. In the
spring of 2007 the ELI was administered to 2,258 undergraduate students representing the full
range of class levels at 13 different public and private colleges and universities across the United
States. Responses were collected via online surveys administered to students through a contact
on each campus, after the institutional review board on the campus approved the study. Each
campus utilized their own method of sampling students via e-mail contacts. Incentives were
provided in the form of a lottery drawing for $25 Starbucks gift cards.
After deleting part-time students and those cases with missing values or multivariate
outliers, the final sample contained 1,747 full-time undergraduate students. As can be seen in
Table 1, 71.9% of the students in this final sample were women. The sample included 22% firstgeneration students and 75.4% of the sample was Caucasian. Almost two-thirds of the sample
lived on campus. Approximately three-fourths intended to pursue an advanced degree at some
point in their lives; slightly less than one-fourth had transferred into the institution they were
currently attending.
Engaged Learning
Table 1
Demographic Characteristics of Participants (N = 1,747)
Characteristic
Gender
Female
Male
Class
First year
Sophomore
Junior
Senior
Generation
First generation
Not first generation
Degree Aspirations
Bachelors
Teaching credential
Masters
Doctorate
Medical or law
Institution was first choice at enrollment
Yes
No
Housing
On-campus
Off-campus
Race/Ethnicity
African-American
American Indian/Alaska Native
Asian American/Pacific Islander
Caucasian
Hispanic
Multiethnic
Prefer not to respond
Institutional Control
Public
Private
n
%
1256
491
71.9
28.1
454
494
387
412
26.0
28.3
22.1
23.6
384
1363
22
78
349
86
886
280
146
20.0
4.9
50.7
16.0
8.3
1218
529
69.7
31.3
605
1142
34.6
65.4
74
11
105
1317
123
53
64
4.2
.6
6.0
75.4
7.0
3.0
3.8
819
928
46.9
53.1
7
Engaged Learning
8
Measures
The Engaged Learning Index is a 10-item instrument that measures affective, behavioral,
and cognitive components of an individual student’s level of engagement in the learning process
across all academic courses. Each item is expressed as a positive or negative statement to which
the student responds on a six-point Likert-type scale ranging from strongly disagree to strongly
agree. The items are located temporally within the student’s recent experiences. The instructions
for the instrument can be varied to direct students’ attention to one particular course or to all the
courses in which they are enrolled throughout the term. The affective items on the ELI include
feeling energized by learning, feeling that the learning experience is worthwhile, and feeling
bored in class. The behavioral components include discussing what is being learned with other
students outside of class, participating in class discussions, and asking questions in class. The
cognitive components include being interested and paying attention, applying the course material
to other aspects of one’s life, connecting the material to previous learning, and experiencing
one’s mind wandering. Negative items are reverse-scored and are scattered throughout the
instrument in order to prevent response sets.
In an earlier pilot study of the psychometric properties of the ELI, an exploratory
principal components analysis using varimax rotation found that three components with
eigenvalues over 1.0 accounted for 69.19% of the total variance. These components were
labeled Meaningful Processing (accounting for 43.21% of the variance), Focused Attention
(accounting for 14.86% of the variance), and Active Participation (accounting for 11.12% of the
variance). Reliability, as measured by coefficient alpha, has been estimated as α = .85, with scale
alpha coefficients ranging from .73 (Active Participation) to .84 (Meaningful Processing).
Engaged Learning
9
In addition to the ELI items, each participant responded to a variety of items indicative of
desired outcomes of the postsecondary educational experience, such as satisfaction with learning,
academic performance, satisfaction with the college experience, satisfaction with the quality of
interaction with faculty, frequency of interaction with faculty outside of class, and self-reported
learning gains in critical thinking skills. These outcomes were utilized as dependent variables in
the current study, with separate regression equations conducted for each. The variables are
outlined in Table 2, along with their corresponding response scales and coding strategies.
Engaged Learning 10
Table 2
Description of Variables
Dependent Variables:
College Grades
Self-reported variable with response options on a 6-point scale where 1=mostly
A’s 2= A’s and B’s 3=mostly B’s, 4= B’s and C’s 5=mostly C’s 6=below a C
average. Reverse scored.
Critical Thinking Gains
Response to the item: “Compared to when you first started college, how much
do you think you have changed in your critical thinking skills?” Measured with
6-point scale, 1=no change at all, 6=quite a lot of change.
Learning Satisfaction
Response to the item: “Rate your satisfaction with the amount you are learning
in college.” Measured with a 6-point scale, 1=very dissatisfied, 6=very satisfied.
Faculty Satisfaction
Response to the item: “Rate your satisfaction with the amount of contact you
have had with faculty this year.” Measured with a 6-point scale, 1=very
dissatisfied, 6=very satisfied.
Faculty Interaction
Response to the item: “How often do you interact with faculty outside of class?”
Measured with a 4-point scale, 1=never, 4=frequently.
Total Satisfaction
Response to the item: “Rate your overall satisfaction with your college
experience so far.” Measured with a 6-point scale, 1=very dissatisfied, 6=very
satisfied.
Background Variables
First-generation
Definition
First in immediate family to attend college=1; not first to attend college=2
Race/ethnicity
Dummy variable coded 1=white; 0=all other ethnicities.
Gender
Female=1, male=2
Degree Aspirations
Dummy variable. Plan to attain an advanced degree at any point in life, coded
0=no, 1=yes.
Residence
Live on campus, coded 0=no, 1=yes.
Level
Year in postsecondary education, coded 1 = first-year, 2 = sophomore, 3 =
junior, 4 = senior.
Institutional Control
Dummy variable coded 0=no, 1=yes for public universities.
Independent Variables
Definition
Meaningful Processing
Sum of five items from the Engaged Learning Index: (1) I often discuss with my
friends what I am learning in class; (2) I feel as though I am learning things in
my classes that are worthwhile to me as a person; (3) I can usually find ways of
Engaged Learning 11
applying what I’m learning in class to something else in my life; (4) I find
myself thinking about what I’m learning in class even when I’m not in class; (5)
I feel energized by the ideas that I am learning in most of my classes. Each item
is measured on a 6-point scale: 1=strongly disagree, 6=strongly agree. (α = .84)
Focused Attention
Sum of three items from the Engaged Learning Index: (1) It’s hard to pay
attention in many of my classes; (2) In the last week, I’ve been bored in class a
lot of the time; (3) Often I find my mind wandering during class. Each item is
measured on a 6-point scale: 1=strongly disagree, 6=strongly agree. All items
are reverse scored. (α = .82)
Active Participation
Sum of two items from the Engaged Learning Index: (1) I regularly participate
in class discussions in most of my classes; (2) I ask my professors questions
during class if I do not understand. Each item is measured on a 6-point scale:
1=strongly disagree, 6=strongly agree. (α = .73)
Data Analysis and Results
The first phase of data analysis involved a confirmatory factor analysis of the Engaged
Learning Index conducted with AMOS (version 16.0), utilizing the maximum likelihood
estimation procedure. An examination of the data indicated that the sample was representative of
the racial balance on the campuses that had been sampled, but was disproportionately female.
After deleting all cases with missing data or multivariate outliers, standardizing all variables, and
weighting the sample by gender, the three-factor model derived from the exploratory principal
components analysis, with engaged learning as a higher-order factor, was tested for its fit with
the current sample of 1,747 undergraduate students.
The quality of the model’s fit was assessed using two criteria in addition to the traditional
chi-square goodness-of-fit, which was highly inflated due to the large sample size. The
comparative fix index (CFI; Bentler, 1990) compares the improved fit of the hypothesized model
to a null model that assumes the model’s observed variables are not correlated; this null model is
also known as the independence model. CFI values can range from 0 to 1, with 1 indicating a
perfect fit. Values greater than .95 are considered to represent a well-fitting model (Thompson,
2004). The second criterion for fit, the root mean square error of approximation (RMSEA;
Engaged Learning 12
Browne & Cudeck, 1993), is a parsimony-adjusted index that indicates the fit between the
implied and the population covariance matrix. In contrast to the CFI, lower RMSEA levels are
indicative of a better fit, with values closer to 0 being more desirable. A commonly accepted
standard is that RMSEA values of less than .06 represent a well-fitting model (Thompson, 2004).
The CFA indicated that the three-factor model with engaged learning as a higher-order
construct provided an excellent fit, with χ2 (32)= 471.91, p < .001, CFI = .98, and RMSEA =
.046 with 90% confidence intervals of .042 to .049. All measured variables loaded strongly on
their respective latent variables (β range = .61 to .82). The model is depicted in Figure 1.
Engaged Learning 13
.38
e5
Zeli2.56
e4
Zeli4.52
e3
Zeli6.45
e2
Zeli9.55
e1
Zeli11
.61
.75
e11
.92
.72
Meaningful
.67
Processing
.74
.96
e12
.52
e8
Zeli5r.63
e7
Zeli8r.60
.80
.77
e6 Zeli13r
.26
.72
Focused
Attention
Engaged Learning
.51
.57
e13
.33
e10
.67
.82
Zeli3.45
.67
e9
Zeli7
Active
Participation
Figure 1. Confirmatory Factor Analysis Model of the Revised Engaged Learning Index
The second phase of data analysis utilized a series of hierarchical multiple regression
equations, one for each of the desired outcomes that served as dependent variables. In each case,
institutional control (public or private) and student characteristics such as race, gender, firstgeneration status, residence (on or off campus), class level, and degree aspirations were entered
Engaged Learning 14
in the first block of the analysis and students’ responses to each scale of the Engaged Learning
Index were entered as the second block of the analysis. The variables entered in block one as
control variables were chosen due to previous research that had indicated their significant
relationship to at least one of the dependent variables or to student engagement (Hu & Kuh,
2002; Kuh, 2003a; Kuh, Gonyea, & Palmer, 2001; Pascarella et al., 2006; Pike & Kuh, 2005).
Separate regression equations were calculated for the following criterion variables:
students’ satisfaction with faculty, satisfaction with learning, satisfaction with their total college
experience, frequency of interaction with faculty outside of class, self-reported gains in critical
thinking skills during college, and self-reported college grades. Other researchers have found a
significant relationship between students’ self-reported grades and actual grades (Olsen et el.,
1998) and have routinely used self-reported learning gains as an outcome measure (Nelson Laird,
et al., 2008).
Table 3 outlines the means and standard deviations of the ten items in the Engaged
Learning Index, while Table 4 presents the results of each of the regression equations. After
controlling for institutional type and student demographic characteristics, scores on the Engaged
Learning Index accounted for an additional 5% to 30% of the variance in desired outcomes. ELI
scores contributed least to the variance in self-reported college grades and most to the variance in
students’ learning satisfaction, satisfaction with faculty, and gains in critical thinking skills.
Engaged Learning 15
Table 3
Means and Standard Deviations for Engaged Learning Index Items
Item
1. I often discuss with my friends what I’m learning in class.
2. I regularly participate in class discussions in most of my classes.
3. I feel as through I am learning things in my classes that are
worthwhile to me as a person.
4. It’s hard to pay attention in many of my classes. (reverse scored)
5. I can usually find ways of applying what I’m learning in class to
something else in my life.
6. I ask my professors questions during class if I do not understand.
7. In the last week, I’ve been bored in class a lot of the time. (reverse
scored)
8. I find myself thinking about what I’m learning in class even when
I’m not in class.
9. I feel energized by the ideas that I am learning in most of my
classes.
10. Often I find my mind wandering during class.
Note: N = 1,747
M
4.55
4.42
4.78
SD
1.03
1.16
1.00
3.82
4.50
1.22
1.01
4.35
3.64
1.17
1.37
4.34
1.05
4.14
1.05
3.18
1.20
The Meaningful Processing Scale of the ELI was most predictive of the various criterion
variables. The items on the scale appear to measure the psychological energy students invest in
the learning process through thinking about material presented in class even outside of the
classroom setting, believing the learning to be personally valuable, applying course material to
other aspects of their lives, discussing with their friends what they are learning, and feeling
energized by the ideas they are learning. This scale had the largest correlation with students’
satisfaction with the amount they are learning (r = .58; partial r = .45). In addition to its
significant contribution to learning satisfaction, scores on this scale were significantly predictive
of all other criterion variables as well: overall satisfaction with the college experience, gains in
critical thinking skills, college grades, and both frequency and satisfaction with faculty
interaction. Thus, the meaningful processing that is indicative of deep learning appears to be
Engaged Learning 16
significantly associated with students’ overall perception and satisfaction with their campus
experiences, as well as with the quality of their learning.
The Focused Attention scale of the ELI was moderately predictive of learning satisfaction
and was predictive of all other outcomes except gains in critical thinking skills and frequency of
faculty interaction. The Active Participation scale contributed significantly to the variance in
faculty interaction and satisfaction with faculty, as well as college grades and total satisfaction
with the college experience, but was not a significant predictor of learning satisfaction or gains in
critical thinking skills.
Engaged Learning 17
Engaged Learning 18
Table 4
Summary of Hierarchical Regression Analyses for Variables Predicting Desired Outcomes of Postsecondary Experience
____________________________________________________________________________________________________________
Criterion Variables
Variable
Learning
Satisfaction
Faculty
Satisfaction
Faculty
Interaction
β
β
Step 1
Institutional Control
-.02
Gender
-.07**
First generation
-.01
Ethnicity
-.04
Degree aspirations
.07**
College grades
.11***
R2
.03
Step 2
Meaningful Processing
.49***
Focused Attention
.13***
Active Participation
.00
R2 change
.30
2
Total R
.33
N = 1,747 * p < 05; ** p < .01; *** p < .001
College
Grades
Total
Satisfaction
β
Critical
Thinking Skills
Gains
β
β
β
-.05*
-.06**
.02
.01
.05*
.16***
.07
-.08***
-.06*
.02
.03
.06**
.12***
.07
-.03
.00
.00
.07**
.05*
.07**
.09
-.11***
-.18***
.07**
.11***
.13***
NA
.10
-.01
-.03
-.03
.02
.04
.14***
.03
.26***
.06*
.16***
.13
.20
.16**
-.02
.21***
.08
.15
.33***
.01
.00
.10
.19
.06*
.09***
.15***
.05
.15
.26***
.07**
.09***
.10
.13
Engaged Learning 19
Discussion
This study makes two notable contributions to the conceptualization of undergraduate
student engagement in the learning process. First, it confirms that the Engaged Learning Index is
a reliable and valid tool for assessing students’ psychological engagement in learning. The ELI
consists of only ten items, yet is internally consistent (α = .85) with a robust factor structure
containing three components of Meaningful Processing, Focused Attention, and Active
Participation which account for almost 70% of the variance in engaged learning. The
confirmatory factor analysis also demonstrated that engaged learning is a higher-order construct,
so that total scores on the ELI can be utilized meaningfully.
Second, this study demonstrates that engaged learning contributes substantially to the
variation in students’ learning satisfaction, as well as their critical thinking skills, interaction and
satisfaction with faculty, overall satisfaction with the college experience, and, to a lesser extent,
their grades. This significant contribution is over and above the amount of variance explained by
students’ demographic characteristics such as their gender, ethnicity, class level, residence, firstgeneration status, degree aspirations, or type of institution attended. When students are engaged
cognitively, emotionally, and behaviorally in the learning process, they are more likely to be
satisfied with their learning and to report gains in their critical thinking skills. This satisfaction
extends beyond the classroom, as they are also more likely to be satisfied with faculty, are more
likely to interact with faculty outside of class, and express higher levels of satisfaction with their
entire college experience.
Implications for Faculty Development
The concept of engaged learning as measured in the ELI offers additional insights into
student success that are worth exploring further with faculty in the context of faculty
Engaged Learning 20
development programs. There are four implications for faculty development in particular that
arise from these findings.
Measuring engaged learning. The first implication is that the methods often used to
assess students’ engagement in the learning process have not provided a complete picture, as
much of what constitutes engaged learning is not directly observable in student behavior.
Faculty typically rely on observable behaviors as indicators of engagement and may make
judgments about students’ learning based on the level of active participation they see in the
classroom. Yet behaviors such as participating in class discussions and asking questions of
professors account for little, if any, of the variation in student success outcomes. For example,
for every standard deviation increase in Meaningful Processing scores, critical thinking skill
gains increase by one-third of a standard deviation and learning satisfaction increases by almost
half a standard deviation; yet for every standard deviation increase in Active Participation scores,
there is no increase whatsoever in critical thinking skill gains or in learning satisfaction. Active
Participation scores are significantly predictive of students’ interaction with faculty (β = .21),
their satisfaction with faculty (β = .16), and their grades (β = .15), however. This finding may
indicate that students who are behaviorally involved in learning activities are also more likely to
engage in such behaviors as seeking to interact with faculty outside of class, which may increase
their satisfaction with faculty and potentially even their grades. It may also indicate that deep
learning and meaningful processing are not always necessary in order to earn high grades.
Nelson Laird et al. (2008) found that while more frequent use of deep approaches to learning
were related to higher levels of student satisfaction, personal development, and learning gains,
they were not significantly related to students’ grades.
Engaged Learning 21
Using an instrument such as the Engaged Learning Index could provide professors and
faculty developers with more reliable and immediate feedback about students’ engagement in the
learning process. Because the instructions to students can be modified to refer to either a single
class or to all the courses in which they are enrolled in a given semester, the ELI can be used by
individual faculty or by institutions and faculty developers as they examine the overall levels of
engaged learning within various majors, class levels, and programs across the institution. For
example, individual faculty can use the ELI at various times in their classes for feedback to
determine the impact that the course is having on students’ engagement in the learning process.
Faculty developers could also use the ELI as a pretest and posttest measure of the
effectiveness of interventions they design for the improvement of learning-centered teaching. As
Sorcinelli et al. (2006) note, “teaching for student-centered learning” (p. 73) has been identified
by faculty developers as the most important issue to address in faculty development programs,
yet there are few reliable measures for assessing the impact of such programs. Because
psychological engagement is often a precursor to the learning process and leads to higher levels
of learning satisfaction and critical thinking skills, helping students become emotionally engaged
may be as important as teaching knowledge and skills (Handelsman et al., 2005). As faculty
development programs focus more on teaching faculty to become learning facilitators who utilize
a broad range of strategies, the ability to measure student engagement in learning can provide
helpful feedback.
Strategies for deep learning. The second implication for faculty development is the
importance of providing faculty with effective strategies for engaging students in meaning
making. The Meaningful Processing scale was designed to reflect approaches to deep learning
(Barr & Tagg, 1995; Biggs, 1988, 2003; Tagg, 2003) and was the scale most predictive of the
Engaged Learning 22
various student success outcomes in this study. Approaches that encourage deep learning involve
connecting new learning to what is already inside the learner, an “inside-out” approach that
Shulman (2005) asserts is the first step in the learning process. Helping students apply what they
are learning to real-world situations and to personal issues in their lives, as well as helping them
experience such learning as having the potential to meet their future needs, will lead to the kind
of significant learning that lasts beyond the final exam. It is this type of learning that faculty
most desire to facilitate within their students, and for which they often seek professional
development opportunities.
Ryan and Deci’s (2000) self-determination theory grounded the development of the
Engaged Learning Index and thus provides a helpful framework for increasing the levels of
students’ engagement that can lead to deep learning. The major premise of their theory is that
people are more likely to be authentically motivated when an activity or task meets three of their
most basic human needs: their needs for competence, autonomy, and relatedness. As a wider
spectrum of prior learning experiences characterizes today’s college students, the task of
motivating students to take responsibility for their own learning has become increasingly
daunting and remains the primary challenge for educators (Pintrich & Zusho, 2002). Creating
environments that support students’ needs for competence, autonomy, and relatedness can lead to
higher levels of motivation because such environments foster authentic motivation that is not
dependent on extrinsic reinforcers (Ryan & Deci, 2000).
Faculty can create such environments within their classrooms, as they are “the designers
and facilitators of learning activities and tasks, [who] play a key role in shaping students’
approaches to learning” (Nelson Laird et al., 2008, p. 471). An environment that supports
students’ need for competence is characterized by clear expectations, optimal challenges, and
Engaged Learning 23
timely feedback (Chickering & Gamson, 1991; Csikszentmihalyi, 1990; Kashdan & Fincham,
2004). Instructors can provide clear expectations through a syllabus that outlines how
assignments will be assessed and provides helpful information on the structure of the tasks
assigned. Emphasizing the meaningfulness of the activity and articulating the level of effort
required to master it can also equip students with an increased sense of competence. Optimal
challenges occur when the assignment requires students to engage in tasks that realistically
stretch their current capabilities (Csikszentmihalyi, 1990). Boredom and apathy occur when the
challenge is too small; anxiety and withdrawal occur when the challenge is too great; curiosity
and engagement occur when the challenge is optimal (Kashdan & Fincham, 2004).
Timely feedback from faculty fosters competence because it provides information that
can be helpful in modifying future performance (Chickering & Gamson, 1991). Frequent
feedback that provides information specific to the task enhances students’ perceived competence
as it targets specific actions the student can take to move to higher levels of excellence (Ryan &
Deci, 2000). Explaining to students at the beginning of a course the types of strategies that are
likely to lead to their success also enhances students’ perceived academic control, which
researchers have demonstrated is an important factor in their academic success because it is
associated with greater investment of effort and increased positive affect (Perry, 2003). Armed
with a sense that they are capable of succeeding in class, students are more likely to authentically
engage in the learning process.
A learning environment that meets students’ need for autonomy also can enhance
authentic motivation and lead to deep learning. Providing students with choices and
opportunities for self-direction can support their need for autonomy and spark their curiosity. For
authentic motivation to occur, students must see themselves as active agents engaged in a
Engaged Learning 24
meaningful experience integrated with their own goals and values (Ryan & Deci, 2000).
Inherently meaningful assignments tap into students’ interests and require students to think about
their talents and how to apply them in a learning situation. Creating opportunities for students to
design their own assignments, providing choices in types of assignments which can demonstrate
mastery of course concepts, and asking students to connect their learning to important goals in
their lives are strategies faculty can utilize to support students’ needs for autonomy. For classes
where the structuring of assignments allows for limited choice, exams can be designed to allow
students to select from different types of questions or from among several questions to
demonstrate their learning. To whatever extent students can see aspects of their academic tasks
as chosen and relevant to their own goals, they are more likely to experience engaged learning.
Students’ need for relatedness can be supported by learning environments that foster a
sense of community. With the proportion of commuter students increasing across all types of
institutions, the primary opportunity for developing a psychological sense of community on
campus occurs through classroom experiences. A sense of community is comprised of four key
elements: (1) membership, or a sense of belonging; (2) ownership, or a sense of voice and
contribution; (3) relationship, or emotional connections with others in the community; and (4)
partnership, or an interdependence in working toward mutual goals (Schreiner, 1998). Faculty
development programs can emphasize that the first day of class sets the tone for the development
of this sense of community. As the instructor emphasizes relationships between student and
professor, as well as among the students as learning partners, students begin to see themselves as
members of a group that will develop into a community. Learning teams enable students to form
emotional connections with other students, as well as partnerships that can accomplish more than
any individual can. Encouraging feedback from students, such as the “one-minute paper” (Cross,
Engaged Learning 25
1998) that many instructors utilize at the end of a class session, fosters the sense of ownership by
communicating to students that they have a voice and that their contribution to the class matters.
In Kuh et al.’s (2005) study of 20 highly engaging colleges and universities, one common
characteristic the institutions manifested was a campus-wide knowledge of their students—
“where they came from, their preferred learning styles, their talents, and when and where they
need help” (p. 301). Knowledge about one’s students provides faculty with a foundation for
connecting with those students’ interests and prior learning. Relating to students authentically
enables professors to connect with them in and out of the classroom. A recent study of high-GPA
seniors indicated that students were more likely to seek out interaction with faculty outside of
class after they had been engaged in the learning process in the classroom and had connected on
a personal level with the instructor (Noel, 2007). Thus, faculty development programs that assist
faculty in creating a sense of community within their classroom can foster environments that
support students’ need for relatedness and are likely to lead to authentic engagement in the
learning process.
Teaching mindfulness. The third implication of this study for faculty development relates
to the significant contribution that focused attention makes to satisfaction with the learning
process as well as to college grades, satisfaction with faculty interactions, and overall satisfaction
with the college experience. The Focused Attention scale was designed around the construct of
mindfulness (Langer, 1997), which can be taught to students, as they learn to be psychologically
present in the moment and notice what is new or different in the surrounding environment.
Mindfulness also involves perspective-taking (Langer, 1997) and making the material personally
meaningful, both of which lead to the deep learning (Tagg, 2003) that tends to have the most
significant and lasting impact on students’ lives. Taken together, these strategies also encourage
Engaged Learning 26
the development of self-authorship, which is an internally defined belief system and sense of self
that one is able to maintain while taking into consideration the views of others (Baxter Magolda,
1999; Kegan, 1994). As faculty teach students to mindfully consider different perspectives,
approach issues from a variety of viewpoints, and reframe concepts in a novel way, students are
encouraged to take ownership of their learning and begin to internalize their own values and
beliefs.
Creating a seamless learning environment. Finally, by encouraging faculty to focus
intentionally on students’ engagement in the learning process, there is a higher likelihood that
students will seek out ways to interact more regularly with faculty outside of class, leading to
even greater effects on student learning and success. Congruent with Kuh, Kinzie, Schuh, Whitt,
and associates’ (2005) conclusions regarding highly engaging institutions, an “unshakeable focus
on student learning” (p. 65) combined with practical ways for fostering engagement in that
learning, has a multitude of positive outcomes for students and institutions. An important aspect
of faculty development is helping faculty cultivate a greater understanding of the connections
that exist between the strategies they utilize in the classroom to facilitate engaged learning and
those embedded in student development programming. When faculty view themselves as part of
the learning partnerships that can be fostered across campus, a seamless learning environment is
created for students inside and outside of class (Baxter Magolda & King, 2004).
Limitations of the Study
The primary limitation of this study is that the sample, while large and representative in
most respects of the institutions from which it was drawn, was not random. Because females
were overrepresented and many of the outcomes varied significantly by gender, the sample was
weighted for gender (Pike, 2008) and gender was one of the control variables in the regression,
Engaged Learning 27
along with ethnicity, first-generation status, degree aspirations, class level, residence, grades, and
institutional control (public or private). However, it is possible that a different sample of students
may produce slightly different results. The findings reported here are limited to traditionallyaged students at four-year institutions and cannot be generalized to community colleges.
Despite this limitation, the reliability and robustness of the constructs measured by the
Engaged Learning Index have been confirmed across multiple undergraduate samples within
four-year institutions. The current study provides strong support for the dimensions of deep
learning, mindfulness, and involvement in learning activities as collectively contributing to
students’ learning satisfaction, gains in critical thinking skills, frequency and satisfaction with
faculty interaction, total satisfaction with college, and college grades, after controlling for
demographic characteristics. Future research can expand on the contribution of engaged learning
to additional student success outcomes, including other types of learning gains and student
persistence to graduation. A focus on engaged learning as a desired outcome itself, rather than
solely as a means to an end, could generate additional research on the types of pedagogy that
have the greatest impact on engagement in the learning process.
By grounding the constructs of Meaningful Processing, Focused Attention, and Active
Participation in well-established theories of motivation and learning, results of the Engaged
Learning Index can provide faculty with helpful information about aspects of the teaching and
learning process that can enhance students’ authentic motivation for learning. As a result, student
responses to the ELI form a valuable foundation for the creation of a faculty development
program whose outcome is an increased ability for faculty to facilitate the full scope of student
engagement in the learning process within their classrooms.
Engaged Learning 28
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