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2013, Vol. 4, No. 1, 68-76 

Online Classes: An Evaluation by Traditional-Aged Students 
 

Stephen Baglione, Saint Leo University  
 

 

Our sample of traditional-age undergraduate students offers self-reported perceptions on online and 
traditional face-to-face classes.  The results reveal that traditional classes are preferred and evaluated 

superior for learning (including high-order levels on Bloom’s Taxonomy), participation, and creating a 
sense of community.  Students also spend more time studying and doing homework in traditional classes.  
Grades are perceived comparable across delivery methods, but students with higher Grade Point 

Averages prefer traditional classes, as do introverts, and males.  Online classes do have advocates, with 
about a quarter of students preferring them to traditional classes because of convenience and flexibility.   
 

 

 Convenience is the most cited reason for taking online classes (Watson & Rutledge, 2005; Wuensch et 

al., 2008). For non-traditional students, it allows them the flexibility to maintain full-time jobs and 

personal commitments while pursuing an education. For this segment, online courses remove time and 

space barriers to provide a viable alternative to traditional face-to-face courses (Tanner et al., 2006).  

Lapsley et al., (2008) found both delivery methods provided equivalent learning opportunities.   

 Convenience attracts students, but they demand more: quality, meaningful assignments, and high-

quality feedback (Tricker et al., 2001), which is timely (Gallien & Oomen-Early, 2008; Shea et al. 2002).  

Structure, as defined by objectives, assignments, and deadlines, also has been shown to influence student 

satisfaction (Stein, 2004). Student-to-student interaction strongly influences satisfaction (Jung et al., 

2002). A lack of collaboration led to negative emotions about an online class (Nummenmaa & 

Nummenmaa, 2008). Faculty interaction with students directly affects student satisfaction (Chickering & 

Gamson, 1987). Effective online faculty have strong written communication skills, promote discussion, 

provide timely feedback, and encourage student collaboration and interaction (Spangle et al., 2002). With 

online courses, a strong predictor of student satisfaction and learning is creating a sense of community 

(Woods & Ebersole, 2003). When compared to traditional classes, almost a third of respondents felt less 

connected (Watson & Rutledge, 2005). Overall faculty should be actively engaged in the class (Jones, 

2012).   

 Studies comparing online and traditional classes have found online superior or equal: i) student self-

reports indicate greater or equal learning in online (Arbaugh & Stelzer, 2003; Fjermestad et al., 2005; 

Hannay & Newvine, 2006); ii) student self-reports indicate more time spent in online (Hannay & 

Newvine, 2006); iii) more active participants (Hiltz & Shea, 2005; Shea et al., 2002); iv) similar or better 

grades in online (Daymont & Blau, 2008; Friday et al., 2006; McLaren, 2004); and v) similar levels of 

satisfaction (Allen et al., 2002; Kelly et al., 2007). Student withdrawals from online classes and students’ 

perceptions that online classes would be easier are related (Nash, 2005). A meta-analysis conducted by 

the Department of Education of 1,000 studies since 1996 found online education marginally better than 

the traditional classroom on learning outcomes (Department of Education, 2010).    

 “The proportion of students taking at least one online course has increased from fewer than 1 in 10 in 

2002 to nearly one-third by 2010, with the number of online students growing from 1.6 million to over 

6.1 million over the same period - an 18.3% compound annual growth rate” (Allen & Seaman, 2012: 3).  

This trend will only continue. The Chronicle of Higher Education examined data trends and polled 

experts, including admissions officials, to predict education in 2020. More than a third of respondents 

predicted 60% of students will be taking only online classes (2009). Much of this increase is attributable 

to the success of for-profit institutions such as The University of Phoenix, “a disruptive innovator” 

(Burnsed, 2011).   

 There are concerns about online classes. “There is no face-to-face contact, no context clues, and no 

opportunity for immediate dyadic communication” (Tanner et al., 2009: 32). Students believe physical 

separation of students and of students and faculty make online classes inferior to traditional classes in 



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communication (student/student and student/faculty), understanding course material, especially complex 

material, and less community and connectedness (Ritter et al., 2010; Wuensch et al., 2008).    

 Concerns also occur on the delivery side. In a survey of almost 5,000 faculty members, two-thirds 

“believe that the learning outcomes for an online course are inferior or somewhat inferior to those for a 

comparable face-to-face course,” although “faculty members with a greater exposure to online education 

have a less pessimistic view than their peers (Allen & Seaman, 2012: 3). “Fewer than 6% of all instructors 

consider online to be either superior or somewhat superior to face-to-face instruction” (Allen & Seaman, 

2012: 9). Online learning is perceived more favorably by students than faculty (Tanner et al., 2009; 

Wilkes et al., 2006). A recent study of human resource professionals undertaken by the Society for 

Human Resources found “44% agreed or strongly agreed that online learning was of lower quality than 

face-to-face, whereas only 3% thought the same of traditional learning” and 60% “agreed or strongly 

agreed with the statement that job applicants with traditional degrees are preferred by my organization to 

applicants with online degrees, presuming work experiences are similar” (Society for Human Resources, 

2010).    

 Gender differences may also exist. Women have done better in both online and traditional classes 

(Friday, 2006). Arbaugh (2005) found the opposite: perceived learning was lower for females than males, 

while Daymont and Blau (2008) found them equal.  
 

Methods 

 

 The survey was developed through a literature review and multiple iterations among undergraduate 

students; a pre-test using protocol analysis with 31 undergraduates was employed. It was administered at 

a southeastern non-secular university to traditional-age undergraduate students. The university has been 

providing online classes since the late 1990s. A convenience sample was used. (Note: Freshmen were 

excluded because they cannot take online classes at the university). The data were analyzed in SPSS 

version 20. Data were recorded by one person and reviewed for mistakes by another. Frequencies were 

then examined to ensure no data were outside the range of feasible answers. Individual questions were 

tested against the scale midpoint of four in a one-sample t-test (seven-point scale). Hypotheses were 

tested at the .05 level. A two-sample t-test was used when comparing across groups, again at the .05 level.  

Pairwise deletion was used (i.e., deleted by individual by question).     

 Logistic regression is used to compare respondents based on preferences (i.e., online or traditional) by 

online classes taken; personality (introvert-extrovert), grade point average (GPA), hours spent studying, 

and gender. The personality scale, from introversion to extroversion, is an eight-item scale bounded by 

strongly agree to strongly disagree (five points) (John & Srivastava, 1999). Logistic Regression does not 

require assumptions about the independent variables (i.e., normality, linearly related, or equal variances 

with groups). Multicollinearity is a potential problem. Outliers are detected through examination of the 

standardized residuals (values greater than three). The -2 Log Likelihood (perfect model equal zero, 

where each cases predicted and actual probabilities are compared and summed) and Goodness of Fit 

indicates model fit (low values better) is used to assess model fit. Chi-squared is also used to assess the 

overall model by comparing the estimated with an intercept only model. Cox & Snell and Nagelkerke R2
 

(bounded by zero and one) indicate the proportion of variability in the dependent variable accounted for 

by the equation’s predictor variables. The Hosmer and Lemeshow Test with a p-value greater than .05 

indicates good fit (Hilbe, 2009). Each predictor’s significance is tested through a Wald statistic. For each 

predictor, we will examine the unstandardized regression coefficient (B), Wald statistic, and odds ratio 

(Exp (B)). The odds ratio represents the increase (decrease if less than one) in the odds of being classified 

in a category (dependent variable equals one).  
   

Results 

 

 The survey was completed by 117 students. Three surveys were unusable because of incomplete data 

(n = 114). All students have taken at least one online class. No question had more than three missing 

values. Respondents are predominately female (64%) (Table 1). They are upper-class (82%) School-of-



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Business students (69%) who live in campus dormitories (52%) with an average GPA of 3.17. They study 

an average of 10 hours weekly (10.07), while working (including work-study and internships) almost 17 

hours (16.55, with 15% not working). They pay for more than a third of their college expense (38%), 

while 17% pay nothing.  They are primarily from suburban areas (39%), followed closely by rural (27%), 

and urban (34%). A third (37%) are not involved with student organizations (18.4% are on a sports team) 

among all the average number of organizations belonged to is 1.46.   
 

Table 1: Demographics (n=114) 
  

Category Percent Category Percent 

Gender  College Major    

Female  64%1 Business 69% 

Male 36% Non-business 25% 

  Undecided 5% 

Residence (home)   Residence (campus)   

Urban 34% On-campus 52% 

Rural 27% Off-campus (family) 20% 

Suburban 38% Off-campus (non-family)  28% 

Class Rank    

Freshman 5%   

Sophomore 11%   

Junior 34%   

Senior 48%   
        1Because of rounding error, totals may not sum to 100% 

 

 They have taken an average of 2.8 online classes (six eight-week terms annually are available and 

students can take one class per term with faculty advisor and department chair approval). The major 

reason for taking online classes is flexible times (62%) followed by traditional classes are at inconvenient 

times (47%), easier workload than traditional classes (29%), save gas money (28%), traditional class 

unavailable (27%), and no travel involved (23%).    

 Respondents found online classes unexciting, predictable, challenging, not fun, and informative, but 

not simple (neutral) (Table 2). They were found to have created synthesis and evaluation. (Students were 

provided with a definition of two levels of Bloom’s Taxonomy to answer questions (Bloom, 1956)).  

Synthesis was defined as use of old ideas to create new ones; generalize from given facts; relate 

knowledge from several areas; and predict, draw conclusions. Evaluation was defined as compare and 

discriminates between ideas; assess value of theories, presentation; make choices based on reasoned 

argument; and verify value of evidence.) (University of Victoria, 2010). Seventy percent of respondents 

were able to identify synthesis when presented with a definition.   
 

Table 2: One-Sample t-Tests (Online Classes) 
 

Questions t-stat. (mean) p-value 

1) Online classes are exciting.1      -5.42 (3.25) .000 

2) Online classes are predictable.   5.50 (4.81) .000 

3) Online classes are challenging.     3.53 (4.46) .001 

4) Online classes are simple.    0.77 (4.11) .444 

5) Online classes are fun.   -6.13 (3.11) .000 

6) Online classes are informative.  4.70 (4.58) .000 

7) Online classes achieve synthesis.  4.72 (4.58) .000 

8) Online classes achieve evaluation.  5.90 (4.72) .000 
        1Poor Description (1) to Perfect Description (7)  

 

 Traditional classes were found to be predictable, challenging, fun, informative, and created synthesis 

and evaluation (Table 3). They were neutral on whether they were exciting and indicated that simple was 

a poor description. 

 

 

 

 



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2013, Vol. 4, No. 1, 68-76 

Table 3: One-Sample t-Tests (Traditional Classes) 
 

Questions t-stat. (mean) p-value 

1) Traditional classes are exciting.1      0.82 (4.12) .415 

2) Traditional classes are predictable.   2.61 (4.38) .000 

3) Traditional classes are challenging.     7.81 (4.95) .000 

4) Traditional classes are simple.    -3.39 (3.50) .001 

5) Traditional classes are fun.   2.24 (4.34) .027 

6) Traditional classes are informative.  10.24 (5.23) .000 

7) Traditional classes achieve synthesis.  9.83 (5.22) .000 

8) Traditional classes achieve evaluation.  8.01 (5.04) .000 
          1Poor Description (1) to Perfect Description (7)  

 

 Traditional classes when compared to online are viewed as more exciting, challenging, fun, and 

informative, and achieving synthesis and evaluation better (Table 4). Online classes are viewed as more 

predictable and simpler.    
 

Table 4: Paired-Samples t-Tests (Online and Traditional Classes Compared) 
 

Questions t-stat. (mean online) (mean traditional) p-value 

1) Traditional/online classes are exciting.1      -4.78  
(3.25) (4.12) 

.000 

2) Traditional/online classes are predictable.   2.34 

(4.81) (4.38) 

.021 

3) Traditional/online classes are challenging.     -3.27 
(4.46) (4.98) 

.001 

4) Traditional/online classes are simple.    2.97 

(4.07) (3.50) 

.004 

5) Traditional/online classes are fun.   -5.75 
(3.13) (4.34) 

.000 

6) Traditional/online classes are informative.  -3.94 

(4.58) (5.25) 

.000 

7) Traditional/online classes achieve synthesis.  -4.18 
(4.57) (5.21) 

.000 

8) Traditional/online classes achieve evaluation.  -2.33 

(4.72) (5.07) 

.022 

         1Poor Description (1) to Perfect Description (7)  
 

 More than half of the respondents (58%) prefer traditional classes (Table 5). They spend more time 

studying and doing homework in them (67%) and participating (67%). Surprisingly, grades are perceived 

equal between online and traditional. Traditional provides a better sense of community (84%), learning 

environment (65%), synthesis (53%), and evaluation (54%). However, when comparing GPAs by 

preference, those who prefer traditional have higher GPAs (t (75) = -2.45; p = .017; M = 2.93 (online) and 

M = 3.21 (traditional)).   

 They were neutral about whether they would take online classes in the future even if the same class is 

available in the traditional format (t (113) = -0.34; p = .732; M = 3.94) (Strongly agree (1) to strongly 

disagree (7)), take more than one online class at a time (t (113) = -0.54; p = .593; M  = 3.90), and, 

unequivocally, that they would not prefer to take all online classes during a semester (t (113) = 4.82;        

p = .000; M = 4.90).    
 

Table 5: Percentages (Online and Traditional Classes Compared) 
 

Questions Online Traditional Equally 

1) I prefer:  20% 58% 23%1 

2) I spend more time studying and doing homework in:  21% 67% 12% 

3) I participate more in:  23% 65% 12% 

4) I get better grades in:  34% 33% 33% 

5) Which provides a better sense of community?  6% 84% 10% 

6) Which provides a better learning environment?  11% 65% 25% 

7) Which provides greater “synthesis?”   12% 53% 35% 

8) Which provides greater “evaluation?”   6% 54% 40% 
   1Because of rounding error, totals may not sum to 100% 



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 Comparing those that prefer online and traditional classes, we estimated a Logistic Regression. The -2 

Log Likelihood value is 54.67, and the model is significantly different from the constant-only model (chi-

squared (5) = 22.60; p < .000) (Table 6). Forty-one percent of the variation in the model is accounted for 

in the predictor (Nagelkerke R
2
 = .41). The Hosmer and Lemeshow Test is not statistically significant 

(5.96 (8), p < .652), indicating a good fit. The hit rate is 81.1%, with 93.1% of respondents who prefer 

traditional classes, and 37.5% who prefer online correctly identified. The Wald statistic is significant for 

the grade point average, hours spent studying, and gender (Table 6).   

 The odds for males are about 538% higher than the odds for females for preferring traditional to online 

classes. A one-unit increase in the personality scale results in a 6% increase in the odds of preferring a 

traditional to online class (Note: Higher values on the personality scale indicate more extroversion.)  

Taking one more online class increases the odds of preferring traditional to online by 21%. Finally, a one-

unit increase in GPA increases the odds of preferring a traditional class versus an online by 1,221%.    
 

Table 6: Logistical Regression 
 

Variable Odds Ratio  SE 

Classes Taken 1.21  .19 

Personality Scale 1.06  .05 

Grade Point Average 12.21*  1.00 

Hours Studying 1.28**  .09 

Gender 5.38*  .83 

Chi-squared  22.60 
(.000) 

 

R2 (pseudo)   .41  

N  114  

          *p<.05   **p<.01 
 

Discussion 
 

 Our results are similar to other researchers: flexibility and convenience are important determinants to 

taking online classes (Bocchi et al., 2004; Hiltz & Shea, 2005) and to a lesser extent, but still important: 

easier workload. Online and traditional classes both provided a predictable, challenging, and informative 

environment that created synthesis and evaluation. Traditional classes are fun, while online are unexciting 

and not fun. When compared together, the traditional class is superior in creating an exciting, challenging, 

fun, and informative environment that achieves synthesis and evaluation better, while creating a better 

sense of community and overall learning environment. This contradicts much of the research where 

learning outcomes are similar. It is similar to evaluations by faculty and HR professionals (Allen & 

Seaman 2012; Society for Human Resources, 2010).    

 Online is clearly perceived inferior in generating a sense of community. Learning and creating an 

online community have been linked (Arbaugh, 2005; Swan, 2003). For these reasons, traditional is the 

preferred delivered method. Students in traditional classes also spent more time studying, doing 

homework, and participating, yet grades across delivery methods are perceived equal across the two.  

Students unequivocally do not want to take all classes online. Online does have advocates. Almost a 

quarter prefer online, about the same number who prefer both, but on all important metrics, traditional is 

perceived superior. Delivery modes are not perceived interchangeable.  

 Females appear to prefer online to males, probably because they are better students: higher GPAs       

(t (101) = -2.45; p = .016; M = 3.10 (male) and M = 3.31 (female)) and more disciplined, although we did 

not measure that. This contradicts prior research which found no differences (Daymont & Blau, 2008).  

Extroverts, not surprising, want the face-to-face platform, where it is easier to exhibit. Taking additional 

online classes increases the preference for traditional classes. The better students, as measured by GPA, 

prefer traditional to online.   

 Online courses because of their flexibility and convenience will continue to flourish. The question 

becomes how to enhance the learning community and ensure comparability in learning. A seismic change 

for online education is massive open online courses (MOOCs). Carnegie Mellon University has offered 

MOOCs for a decade (Perez-Pena, 2012). Coursera, a consortium of universities led by Stanford, 



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Princeton and Duke, offers 100 courses free (Lewin, 2012). EdX, a joint venture of Harvard and MIT, and 

Udacity also offers MOOCs. How this impacts profit-making online institutions, whether it will 

cannibalize participants’ enrollments, and if the marketplace will accept these non-credit courses is 

unclear? Most students are in foreign countries, but that will change, especially if domestic institutions 

offer them for credit? Will faculty be relegated to grading and supplementing free lecturers from a few 

academic stars online? Benefits may include the creation of globally-blended classes where faculty can 

incorporate online material from an array of lecturers, breaking academic silos, and focusing more on 

difficult material in the classroom (Brooks, 2012). Udacity has “placed about half a dozen students into 

jobs” already (Lytle, 2012). Large introductory classes taught in lecture halls may be the first casualty for 

traditional schools (Burnsed, 2011).     
 

Limitations and Future Research 
 

 We did not directly measure learning, nor confirm student grades. We did not control what types of 

courses these students took (i.e., subject matter and course level), and whether there was a relationship 

between learning, for example, and type of course. Our sample was restricted to traditional-age students at 

one university, which is primarily teaching-oriented and the average class size is around 15. Would 

similar results occur with a research-oriented institution that has large lecture hall introductory classes?   

 Future research should compare traditional-age and non-traditional age students. Since our sample is 

traditional-age students, they may value face-to-face interaction and the structure of traditional classes 

more. Learning’s impact can be statistically decomposed through regression analysis (Friday, 2006; 

Hanney & Newvine, 2006). Students did not record satisfaction levels, although we did measure 

components of it. We could gather perceptions from students and faculty about online courses. Finally, 

course duration may impact satisfaction. During a five-week online course, student satisfaction with 

communication with the faculty diminishes but increases for student-to-student communication 

(Fergeson, 2010).    
 

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Stephen Baglione is professor of marketing and quantitative methods at Saint Leo University in 

Florida. He received his Ph.D. in marketing from the University of South Carolina. He has published in 

British Food Journal, Chinese Management Studies, Electronic Markets, Journal of Excellence in College 

Teaching, Journal of Promotion Management, Quarterly Review of Distance Education, and Journal of 

Applied Management and Entrepreneurship. He was a Fulbright Scholar at the University of Ljubljana in 

Slovenia. 


