This study investigated the satisfaction of 303
undergraduate students who enrolled in traditional 200-level
criminology/ criminal justice courses. University students were offered
the opportunity to self–select into one of four blended online ratios
ranging from 10%, 30% 70% to 90% of the course operating within an
online environment. OLS linear regression analysis suggests that
students who selected lower intervals of online blended instruction (or
high intervals of F2F instruction) were statistically more likely to
report higher levels of overall satisfaction in the course.
Alternatively, the findings suggest that higher ratios of student
selected online instruction may lead to higher levels of student
dissatisfaction. OLS data findings reported that younger university
students who require more flexibility and convenience of scheduling, are
enrolled in higher course loads and/or majoring or minoring in the
subject matter produced statistically higher levels of student
satisfaction.
Keywords: Online;
Blended; Hybrid; Face to Face; F2F; Student Satisfaction;
Learner-Content; Learner-Instructor; Learner-Learner;
Learner-Technology; Interaction; Student Satisfaction Survey
In the current COVID19 pandemic environment [1],
post-secondary academic institutions and instructors are scrambling for a
best practices model to continue to teach their students. Additionally,
the university student (or consumer) searches for the instructional
delivery that suits their needs and priorities. With the increasing cost
of living, expectation of employment, travel, tuition and textbooks,
students are consciously re-assessing the value for their dollar to
determine which institution is right for them. We know when universities
offer the availability of online and blended courses [2] as well as
flexibility in scheduling [3,4] students prefer and are likely more
satisfied with their courses [4]. Blended learning offers a solution to
traditional face to face lecture contact, combining technology with
interval levels of face to face instruction.
It certainly appears that undergraduate students as
consumers of educational attainment want more choice and selection of
course instruction, not less. As consumers of learning, student
satisfaction needs to be accounted for. As Brooks [5] suggests, a
significant majority (83%) of students preferred some form of blended
instruction rather than a traditional face to face (10%) or
traditional online (7%) course. The Center for Applied Research also
reports that prefer digital mediums, that device ownership (tablets,
smartphones, tablets) is greater among students than the public
marketplace and students view their technology as important to their
education and success (2016:5). The use of technology within an online
environment appears to breed a form of success and/or satisfaction not
found within traditional face to face courses. This study explores the
use of interval/ ratio levels of student self-selection of course
delivery to determine if/ and at what ratios of blended course delivery
impacts overall reported student satisfaction.
Student satisfaction can be conceptualized using a
variety of indices from objective performance measurements assessing
grade attainment to subjective measures of student attitudes on process-
based learning and its efficacy [6]. Student satisfaction surveys have
been numerous and rely on similar questions [7]. As a result, many
satisfaction surveys probe the interactions learners have with one
another, their instructor, course content, online technology and the
method by which it is delivered [8]. There is
ample research to suggest that blended learning instruction can
impact student satisfaction. Blended learning generally offers
differing environments that connect traditional lectures with
some form of online learning [10]. A meta-analysis by Moskal
et al. [10] examined the adoption of blended learning to its
implementation and outcomes. The study reported higher levels
of satisfaction among students who enrolled in blended courses
versus fully online or lecture-based modes of instruction [10].
Research suggests that even if there may be no difference within
instructional delivery, students still prefer blended learning.
Owston et al. [11] found similar levels of satisfaction when students
were asked to compare their blended course instructional delivery
to other traditional courses they previously had taken; almost
70% of students reported they would take a blended course again.
This was also confirmed by Madriz and Nocente (2016) who
surveyed nearly 600 undergraduate students finding overall levels
of satisfaction were higher among blended learning and student’s
willingness to take another blended course. Vernadakis et al. [12]
compared blended and face to face (F2F) sections and found that
students enrolled in blended sections reported significantly higher
satisfaction (conceptualized from a twelve-question survey). Forte
and Root (2011) reported similar findings in which students who
enrolled in a blended format had higher levels of satisfaction
versus traditional courses with some levels of web-enhancement.
Melton et al. [13] compared the satisfaction of students enrolled
in four general health courses finding that satisfaction scores were
statistically higher for those students enrolled in three blended
learning courses than one traditional F2F course. Therefore,
there appears to be significant advantages for students when
employing a blended learning method to their course load. A
study conducted by Dziuban et al. [14, 15] reported higher levels
of student satisfaction in a variety of blended courses with 85%
of students agreeing that they were satisfied and 67% reporting
they would like to take another blended course.
Utilizing both
blended and F2F instructional delivery within a nursing student
population, Kumrow (2007) found that blended students were
more satisfied than unsatisfied. These studies have all implied that
there is an importance of learning independently outside of the
classroom which has positive impacts on satisfaction, grades and
future expectations for blended courses [16]. The question may
not be why an instructor may implement blended learning, but
rather why wouldn’t an instructor consider this blending learning
opportunity. Student satisfaction includes inherent factors which
are often difficult to operationalize such as the motivation to taking
a course to a student’s level of pleasure throughout the course to
the effectiveness of the educational experience (Wang, 2003). Wu
et al. (2008) suggest that higher levels of student satisfaction within
a blended learning approach is due to a student’s perceived ease
of use, value of the content and the climate or environment itself
(for involvement and social interaction).
Further research by Wu
and Liu (2013) confirmed that perceived ease of use is positively
correlated with student satisfaction. Sahin and Shelley [17]
suggest, it is not just ease of use but also the value and usefulness of
the content (similar to any traditional F2F or fully online course).
Therefore, each instructor’s inherent design, organization, choice
and ease of software implementation and adoption (or lack
thereof) of content and value within performance measures
can impact student satisfaction. As such, the value of learning
interactions and outcomes can often be associated not just with
student satisfaction but also the choices instructors make when
selecting software and organizing a course. This best reflects what
we know in blended learning. While blended learning appears to
offer significant value and benefits to students, choices instructors
make should ensure that there is an ease and proficiency of use of
software within course delivery is paramount to ensuring student
success and/or satisfaction. Should students not be proficient
in the software and/or frustrated with the layout of the course
design, satisfaction may wane. Therefore, student success and
satisfaction can closely be tied to the design of the blended course.
The design and implementation of blended instruction requires
a thoughtful approach to content, the technology being utilized and
performance measurements [18,19]. Some studies offer quality
assurance checklists to assist instructors (Chauhan et al., 2016)
however, there is no uniform one size fits all strategy. Therefore,
instructors need to ensure that new online learning environments
are designed appropriately for their targeted audience while also
meeting the needs and expectations of students [17]. Due to the
holistic and individualized approach to the adoption, development
and implementation of courses (not just blended), it creates a level
of difficulty and uncertainty in ascertaining what blending works,
with which student populations and whether these courses can
even be compared to traditional F2F or fully online courses. As
meta-analyses of studies have identified, there is a lack of matched
or equivocal groups of students to make often generalizable
comparisons between blended, traditional face to face and
online courses [6,16,20].
As such, there are limitations to simply
suggesting that blended learning, as a one size fits all strategy
will be effective. Satisfaction is often measured conceptually or
operationally differently across studies which can lead to mixed
results. Other studies have proposed that success be measured
in terms of mean/average disparities of grades between groups
of students but perhaps the performance measurements in the
courses were different. Some studies lack more rigorous testing
to examine correlations and/or relationships. As such, there are
limitations in asserting that blended learning is simply better than
traditional face to face or online learning instruction. This is not
simply the fault of poor research methodologies but rather the
lack of being able to randomly select students (for ethical reasons)
and how university and college courses are offered/ distributed
to instructors on an annual basis (leading to logistical issues). The
lack of random sampling and selection, experimental designs and
rigorous testing means that instructors and students should have
a healthy level of skepticism of blended learning.
Meta-analyses
indicate promise in the adoption of blended learning but due to the lack of rigorous methodological approaches, there is no one
perfect strategy on how to employ it [6,16,20]. An instructor’s
selection of design and construction of blended learning within
a course can and should be individualized to fit every instructor
and student’s needs and priorities [22]. Therefore, there is not
likely one specific percentage or interval that can be used to assert
where blended learning is more successful than unsuccessful [23].
There does not appear to be a one size fits all ratio of blended
instruction that will universally be effective [11]. Several studies
and meta-analyses have reported similar findings where students
prefer and/or rank blended course instruction over traditional
face to face instructional delivery [20, 23] despite a lack of
consensus of the appropriate ratios of blending. It should be noted
that comparisons are often made between blended learning and
traditional and/or online courses as if blended ratios were at a fixed
ratio [10].
Despite these limitations, the evidence still supports
the use of blended and online learning environments in that they
can offer higher levels of student satisfaction than traditional face
to face (F2F) instruction [16, 24]. This would suggest that there
may be tipping points (for every instructor) when comparing
success and satisfaction in and out of the classroom. As Shea et
al. (2006) point out, having examined thirty-two colleges, an
instructor’s teaching presence is positively related to a student’s
sense of learning community and direct instructional facilitation.
Therefore, while students may appreciate the convenience of
hybrid/blended/independent time, that friendly face in the
course is also likely a necessity when constructing a course that
will ensure student satisfaction. A 2009 study by Morris and Lim
examined the influence of instructional delivery and student
learning interactions. Their findings suggest that in addition to
age and prior experiences with distance learning opportunities
impact students’ satisfaction; a student’s preference in delivery
format and average study times are increasingly relevant factors
in student satisfaction. This study suggests we need to consider
other circumstantial and/or situational factors that are relevant
to whether student satisfaction is attained - flexibility and
convenience within a student’s life.
A 2016 government report reports that college and university
students are working harder than ever before, where students
are often taking full course loads (considered full time) while also
employed either part or full time. Nearly half of students taking a
full course load (41%) were currently employed either part or full
time (Kena et al., 2016: 221). Of all students reporting, two in ten
(18%) were employed 20-34 hours a week and one in ten students
(7%) were working over 35 hours a week (Kena et al., 2016: 221).
Therefore, flexibility is a significant need for a majority of students
[10,11]. Owston et al. [11] found that students typically benefit
from increased time and spatial flexibility during the delivery of
their courses providing them more resources and autonomy to
regulate their own learning. As Packham et al. [25] suggest, the
causes of student failure in online courses are often attributed
to issues of family, employment and management support.
Therefore, providing more flexibility in time management has a
significant impact on satisfaction [3, 26]. Therefore, generating
an instructional delivery that facilitates choice and selection of
blended learning may allow for higher levels of student success
and/or satisfaction.
There is evidence to suggest that student selection of
instructional format (when students are offered the opportunity
to choose) may have an impact on student satisfaction. A study
by Yatrakis and Simon [27] found that students who chose to
enroll in courses within an online format achieve higher rates
of satisfaction and a perceived retention of information than do
students who enroll in online courses where no choice is provided.
This concurs with the research of Debrourgh (1999) in that selfselection
and satisfaction can be linked to a student’s retention of
information. The findings of Yatrakis and Simon [27] suggest that
students feel a greater degree of satisfaction when allowed to selfselect
for online courses and that choice may carry over into their
perception of retained information. These results can be used to
support choice and self-selection as satisfying the preferences of
the student consumer. This study explores the interval levels of
student chosen instructional delivery on overall reported student
satisfaction. While the majority of research points to selection
being an advantageous option for students, other research [28]
suggest a level of mixed results in whether instructional delivery
has an impact on student satisfaction. Some studies have found no
significant differences between the ratios of blended instructional
delivery and satisfaction [29,30]. As such, this exploratory study
seeks to add to the limited amount of research on student choice
of blended instructional delivery and how other factors (explored
above) impact on student satisfaction.
This exploratory study examined students enrolled in seven
undergraduate courses offered over a sixteen-week semester
cycle. This was a convenient sample of students where no random
selection existed. This is obviously a limitation but one that
allowed student choice and selection of course instruction. Initially,
there were 334 participants registered for the seven 200-level
criminology/ criminal justice courses. Twenty-two students
were removed from the study having dropped or withdrawn
from the course throughout the semester. An additional nine
students were removed from the study for not having completed
survey instruments. Therefore, the sample size for the purpose
of analysis was 303 participants. This study conceptualized and
operationalized four blended delivery systems that students could
select as developed by Twigg [31] and the Sloan Consortium [9]:
(1) replacement (90% F2F:10% online); (2) supplemental (70%
F2F:30% online) and two emporium options (3) 30% F2F:70%
online and (4) 10% F2F:90% online. The most traditional offering
was replacement delivery where 90% of the course would be face
to face (F2F) and 10% within an online environment. As students
considered transitioning away from face to face traditional mlectures, they could connect with one another and the instructor
through the use of discussion boards and additional digital-based
lectures (rather than F2F).
Once a student had selected their
desired blended instructional delivery, they could opt to revise
this offering after the first exam (one month; 8 classes into the
course). This offered each student more flexibility, an operational
component of Twigg’s [31] buffet style approach Students were
asked to complete several pre-test and post-test surveys which
included Elaine Strachota’s Student Satisfaction Survey (2006)
to ascertain satisfaction within each interval of student’s chosen
blended learning which will be explored below. Each of the
courses utilized a hard copy and/or digital textbook to ensure ease
of access. Instructor developed Microsoft power point modules
were used to supplement the textbook and offer additional
resources and examples to ensure the retention of key concepts.
Supplemental technical reports, peer reviewed articles and online
open sourced audio-visual clips were also used to stimulate
critical thinking and problem solving skills while ensuring overlap
of important concepts and themes in the course. The course
was rigorous in a sense that students would be asked to engage
in significant reading and watching/viewing videos with a rigid
structure/ schedule to ensure timelines were maintained and
no additional time was offered for any groups of students being
studied. The course was designed to ensure consistency across
time, content and performance measurements [32]. Performance
measures included three in-class examinations (75%) and three
assignments (25%) with deadlines within the semester.
As explained previously, the study sample began with 334
eligible students enrolled in seven 200-level criminology/ criminal
justice courses within a liberal arts university in the midwestern
United States. Thirty-one students were removed from the
study for (i) having dropped or withdrawing from the course or
(ii) not completing their self-administered surveys. Therefore,
303 students were used for the analysis of this study. Students
were asked to complete a short open-ended self-administered
questionnaire at the beginning of the course. Responses were
relevant to establishing a baseline of data points to understand
the profile of the sample (Table 1 below). Table 1 provides a
general demographic profile of the 303 students enrolled in the
study. In terms of age distribution, a substantial majority (92%) of
undergraduate students were aged 21 21 or under which would
suggest that it would be typical of a traditional university 200-level
course. Women represented a larger percentage (55%) of the
students enrolled in the criminology/ criminal justice courses
which mirrored the University’s student body demographics.
The
majority of students enrolled in courses self-identified as White
(72%) and a large concentration of students self-identified as
Black and/or African American (24%). Asian (2%) and Native
American (1.6%) students were also well represented in the
course, which closely resembled the student body population of
the institution. The University campus in which these courses
were facilitated in have a diverse population across it from large
concentrations of Black and African American residents (16%)
as well as Hispanic/ Latino residents (14%) which mirrored the
student body populations of 21% and 15% respectively. Within
this study, approximately 16% of the students self- identified as
Hispanic and/or Latino. These demographic numbers on race and
ethnicity would suggest that visible minorities were slightly oversampled
in terms of their population in the area and within the
student body population. While this may have an impact on results
of the study, this profile of students was somewhat representative
of the Institution’s student body.
In an effort to test for student
motivation and needs, the pre-test questions probed for students
to reflect on whether flexibility and convenience (in time, travel
to campus) was a factor for selecting a particular form of course
instruction. A significant percentage of students enrolled in these
courses agreed (60%) or strongly agreed (17%) that flexibility and
convenience of scheduling impacted their decision on which ratio
of blended learning instruction they would select. Approximately
3% of students reported a neutral response however, over 20%
of students reported it would not affect their decision. This
might suggest a number of factors that were not studied from
whether a student was already on campus and felt more online
instruction may not be useful, that a student’s schedule did or did
not allow for revisions and whether this course should have been
introduced to students with more advance warning could have
impacted a student’s decision.
These findings would substantiate
the importance of flexibility and convenience that student’s
require and perhaps why students may consider blended or online
learning. However, as noted above, this was not an issue for nearly
one in five students. Student profile data attained from pre-test
surveys was also corroborated with a more rigorous and valid
reporting measurements attained from the University Registrar.
Table 2 examines the validation measurements that were used to
also generate variables of interest for further predictive analysis.
Within Table 2, undergraduate students enrolled in the seven
criminology/ criminal justice courses were asked to provide their
student number so that further variables (their current course
load, their designated field of study and current grade point
average) could be utilized as a more valid representation of their
student history at the Institution. A significant percentage of
students (94%) were currently enrolled in three or more classes,
which is considered a full-time course load. Additionally, there
were more students (8%) were taking the most courses allowed
(without permission at five courses) than those students who
were only taking two courses in the semester they were taking
this course (7%). This finding would suggest that there were
no students taking this course as their sole component of their
university workload. This would suggest (not accounting for
students who may be registered students at another university
and the University where this study was conducted) that the
findings identified in this study may be significantly different than
those studies who may be unaware or not have controlled for
course load. This is why the methodological approach within this
(exploratory) study will likely generate unique findings that could
be more consistent with traditional university students taking
larger course loads than those students who are enrolled as part
time or single course consumers.
The relative importance of the course was another variable
of interest that is often not considered particularly pertinent
or tested within the literature. Within this study, there was an
expectation that undergraduate university students who are
more likely to engage in a designated career path (in this case
criminology/ criminal justice) may feel that face to face course
work might be more ideal or are more motivated to take face to
face courses versus students who enroll in the course to fill an
elective within their liberal arts degree. This 200-level course was
a pre-requisite for additional courses within the degree program
and as such, a majority of the students (62%) had enrolled in these
seven courses to fill that pre-requisite for their major/minor of
study in criminology/ criminal justice. A smaller but still relatively
large component of the students participating in this study (38%)
had enrolled in the course either in fulfillment of their liberal arts
degree requirement, as an elective and/or not having declared
a major or minor in criminology/ criminal justice (which would
have likely occurred prior to this course). This finding would
suggest that there is still significant variance within the variable
that the author felt could be a concern for further analysis. A
final variable of interest that was validated through University
records was a student’s cumulative grade point average (GPA), A
student’s GPA would be compiled from their course work within
the University and any other courses they may have transferred
into from previous universities or colleges.
This study purposely
chose to use validated University records rather than selfreported
scores from students as they would be more reliable and
accurate considering that GPA is generally from a score of zero to
a 4.0/4.5. Once a student’s GPA was coded, it was then categorized
into University pre-determined values of an A, B, C, D and F and/or
probationary status. Most students may characterize themselves
as excellent however, a validated assessment of student GPA
found that only 14% had attained a cumulative A average. The
predominant number of students had attained a B (44%) and C
(31%) cumulative GPA. Approximately one in ten students (12%)
were considered at more high risk of poor or failing cumulative
work. Obviously, the finding here is that a large majority of
students had completed coursework in a good to fair job prior
to enrolling in the course. As such, they may be inherently more
likely to be satisfied with their previous work while also be very
concerned with their grade in this course. Throughout the survey
process, students were asked to select their mode of instructional
delivery (viewed below).
Table 3 highlights the student self-selection and/or reselection
of online instructional delivery within the seven
criminology/ criminal justice courses. As viewed above, 45%
of students preferred the 70:30 blended option of course instruction; where 70% of the course would be taught face to face
(F2F) and 30% within an online environment. Approximately
2$% enrolled in a 10% online learning environment, similarly
to 20% of students who selected a 70% online environment.
Only 10% (31) of the 303 students selected an almost entirely
90% online environment. It should be noted that at no point in
time, across all seven classes did any one student ever ask or
want to select an option of 100% face to face. While this was not
an option that students were offered, no one student even chose
to ask. This in and of itself, was an interesting finding as there
would be an expectation that if 20% of students who reported
that convenience and flexibility was not an issue, that one of those
students or perhaps other students who had performed well in
traditional face to face courses may not want to change (and/
or choose to register/ enroll in this study). As explained within
the methodology, to offer students additional flexibility and/or
a choice, students were offered the opportunity to revise their
initial blended course delivery. When provided this opportunity,
10 students revised their initial choice. This accounts for only
3% of all students.
This would suggest that 97% of students were
satisfied with their initial choice. Therefore, this study can infer
that students appear to be confident in determining which level/
ratio/ interval of online instruction they favor. This might suggest
that offering this option to traditionally based F2F courses may not
require instructors to be overly concerned about student’s ease of
access or uncertainty over their initial decision. Of the 10 students
who revised their initial instructional delivery, each of these 10
students initially chose less face to face engagement (90:10 or
30:70). When asked to re-select their desired blended course
instruction, 10 of 10 students re-selected options with more face
to face interactions. Similar to the initial student selection process,
no students wanted or preferred a re-imagined 100% face to face
course. Operationalizing Twigg’s [31] classification of blended
learning, a majority of undergraduate university students selected
a replacement (25%) or supplemental approach (48%) rather than
an emporium approach (26%). This finding suggests that students
in this study preferred higher intervals of face to face instruction
than higher ratios of online instruction. Reiterating what was
mentioned previously, no one student sought out an entirely face
to face traditional course which they originally enrolled in. These
findings would infer that students did appreciate the opportunity
to select their own instructional delivery. However, Might this
appreciation have an impact on satisfaction?
To assess student satisfaction, participating undergraduate
students were asked to complete a follow-uo post-test survey
once the course was complete and grades assigned. The six-item
index of satisfaction was developed by Strachota [33] and further
redesigned into what she coined as the Student Satisfaction Survey
(2006). Table 4 highlights the findings of the general satisfaction
of students within the sample. To pilot her survey instrument,
Strachota [8] found this general satisfaction dimension had a
reported.90 Chronbach alpha (ranging from zero to one) which
is exceptional. The findings from Table 4 indicate that students
enrolled in seven 200-level criminology/ criminal justice courses
were very satisfied with the course utilizing Stachota’s general
satisfaction survey (2006). Nine of ten students agreed or strongly
agreed with the statement that they were very satisfied with the
course while only 3% (9) of the 303 students reported being
very dissatisfied with the course. Nearly the same percentage
of students (87%) reported that they would take another selfselected
blended instructional course again if it was offered.
Further extrapolating the data, one in ten (12%) students reported
that they would not recommend this course to others. When
considering learning needs, there was significantly more variation
in student responses. Approximately eight in ten students (82%)
agreed or strongly agreed that the course met their learning needs
with 18% reporting the course did not meet their learning needs.
Three-quarters (75%) of respondents agreed or strongly agreed
with the statement that they learned as much in this course (as
compared to other face to face courses they had taken previously)
[34-40].
Interestingly, 30% of students reported that they generally
believed that blended courses would not be as effective as face to
face courses. Therefore, the student responses to satisfaction in
the course report some unusual and contradictory findings where
students appear to have been very satisfied with the course, there
were issues whether they would take another self-selected course
(despite previous frequency distributions which inferred some
level of appreciation) and/or whether the learning and instruction
met their needs. It could be concluded that perhaps the instructor’s
learning and/or instructional materials may not have matched
the expectations of students. More research is certainly need
to justify this potential inference. To assess and predict student
satisfaction, an ordinary least squares (OLS) linear regression
was utilized for further analysis. As such, survey item/ statement
three required a change in coding to ensure that each of the six
item likert scales could be aggregated from strongly disagree
(0) to strongly agree (3); within the appropriate direction. This
allowed for the generation of a larger index of scores from 0-18.
As seen in the frequency distributions above, there was enough
variability in each of the variable to make conclusions about the
potential relationship of that variable (age, sex, race, flexibility,
course load, fulfillment of course credit, GPA and student choice of
course instruction) and general satisfaction. Student self-selection
was coded appropriately from low online instructional delivery to
high) [41-50]. The OLS regression data is below.
The linear regression model, located in Table 5, was found to
be statistically significant (.001 with a confidence level of 95%
with the p < .05 being significantly different than zero). Student
self-selection and seven variables of interest were found to explain
48% of student satisfaction based on the Nagelkerke R Square
(.482). The regression reported a Chi-square of 209.46 and a model
-2 Log likelihood of 111.29 (with 8 degrees of freedom). Four
cases were removed from the analysis when the variance inflation
factor (VIF >4) and tolerance (TOL) levels of 2.0 or above were
controlled for. Student self – selection of instructional delivery
was found to be the second most important variable to predict
student satisfaction. This finding would suggest that the lower
the ratio of online blended learning, the higher the likelihood of
student satisfaction. Put another way, the higher the percentage
of independent or online learning within courses, the more likely
students in this sample would be dissatisfied. This finding suggests
that as interval levels of blended learning increase, it can have a
detrimental effect on student satisfaction. This might suggest that
not all blended learning is the same and that there may be tipping
points where satisfaction may become dissatisfaction. However,
it should be noted that student choice of instructional delivery
was not the only statistically significant variable within the model
(based on the Beta values) [51-59].
The most significant predictor of the course satisfaction
regression model was the flexibility and convenience of the course
offerings. This is consistent with previous research in the field in
that blended learning courses can predict student satisfaction.
This suggests that not only is flexibility important in scheduling
but additionally, that those students who enroll in more courses
within a semester are more likely to be satisfied than students
who enroll in lower numbers of courses simultaneously. The
evidence, supported by the data, suggests that age was also a
predictor of satisfaction. It appears that older students who
participated in the study were more likely than younger adults
to be dissatisfied with the course. This is somewhat surprising as
it could be hypothesized that older students may be more likely
to require more flexibility and convenience (due to employment,
child care, etc.). However, this could be a case where ease of use
(as explored in the literature) may have been an impact variable
rather than age. Other demographic variables including sex and
race were found to not have any statistical significance within the
model. This is consistent with some of the research findings [16].
Students with higher course loads appeared to be more satisfied
with the course. This could be due to the opportunity to have a
more balanced and/or flexible schedule however, it is more likely
that attaining more course independent time to complete work
and assignments had an impact. However, more research is needed
before this can be verified but it is certainly an interesting finding.
A finding not often examined in the research is whether student
interest or motivation, as denoted by a student’s major or minor
level of study, has an impact on their reported satisfaction. The
data suggests that students who had declared a major or minor in
the study of criminology/ criminal justice were more likely to be
satisfied with the 200-level criminology/ criminal justice course
they enrolled in. Therefore, students who utilized this course as an
elective for their liberal arts degree were less likely to be satisfied
with the course. This might suggest that how the instructor
constructed this course may have inherently benefitted students
who declared a major or minor in the field of interest versus those
who may have had less interest in the course content. Obviously
more research is necessary to understand how student motivation
impacts satisfaction.
As an exploratory case study, the findings of this
research
would suggest that more examination of blended learning and
intervals/ratios of blended learning need to be examined. Simply
offering blended learning does not have an impact on course
satisfaction (as all forms of instructional delivery in this study had
some form of online delivery). This would suggest that there is a
tipping point where students find satisfaction with the blended
offering but too much blended learning (using the instructional
delivery explained within the methods section) has an inverse
relationship to student satisfaction. This study finds that student
selected ratios or intervals of blended learning that offer more face
to face interaction rather than less result in higher levels of student
satisfaction. This finding would certainly suggest that while
students appreciate the convenience and flexibility of hybrid and
blended instruction, they still want (in this instructor’s course)
face to face interactions. Therefore, when constructing courses,
instructors should be diligent to ensure that they are present
and that students receive that face to face time (that even digital
recordings are unable to capture). That rapport and relationship
building appears to be important to student satisfaction in this
study (however more in-depth research is needed). However, as
expressed in the literature review, there is no perfect one size fits
all strategy to implement blended learning as each instructor will
construct their own course, based on their needs and the needs of
their students.
As referenced in the literature, convenience and flexibility
remains a significant factor when understanding the circumstances
students face and satisfaction within their courses. This also may
hold true for instructors as well. With a relatively good variance
explained within the model, there appears to be hope on the
horizon that the use of this a consistent construction and design
of a course could reap benefits with instructors and students alike
(without significant revision each year). While more research is
needed to identify more conclusive findings, blended learning is
an increasingly attractive alternative to traditional face to face
or online learning and has a significant impact on a student’s or
consumer’s satisfaction particularly post-COVID-19. As students
continue to search their desired instructional delivery it would
be wise that instructors consider offering more choice and
selection to ensure each student can attain their desired learning
interactions within the same class based on their motivations.
Allowing student self-selection also might alleviate the finding
that with more online instruction, Allowing student discretion to
make their instructional delivery selection places more emphasis
on their decision making rather than potentially blaming one form
of instructional delivery over another. Despite these findings,
it is clear that more research is needed on intervals of blended
learning, stronger comparison groups and how student selection
impacts not simply student satisfaction but also grade attainment
and/or other measures of student success.
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