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Perceptions of Students and Faculty on the Various Delivery Methods of Instruction

Joanne Hood*, Yuchun Chen, Lorraine Jacques, Dustin Hebert

Department of Curriculum, Instruction, and Leadership, Louisiana Tech University, Ruston, Louisiana, USA

Abstract: Previous research has conducted on the sense of community, effectiveness, and learning experience in the face-to-face, hybrid, and online classes. Student preference on any of the delivery methods has not been extensively studied and none was a comparison study of all three delivery methods. This study investigated the perceived course delivery methods of graduate students and faculty at a southeastern university in the United States. Data were collected using a survey modified from Shantakumari and Sajith’s (2015) work. Principal component analysis was used to analyze the survey, yielding three factors (i.e., learning experience, self-efficacy, and ease of use) explaining 73.8% of the variance. Internal reliability was then calculated using Cronbach’s alpha for the entire instrument and for each factor. An overall reliability was above .94 and most of the factors were above .8. Repeated measures ANOVAs were used to determine if there was any significant difference in how the participants rated each delivery method. The overall sample showed interaction effects between the students and faculty on learning experience and self-efficacy, but not on ease of use. Students preferred learning experience in face-to-face and hybrid over online courses. Student sample indicated no significant difference in preferred delivery method regarding self-efficacy or ease of use. Faculty preferred face-to-face, followed by hybrid, followed by online delivery in the learning experience factor, and face-to-face over hybrid and online delivery in the self-efficacy and ease of use factors. The findings provide insight that could support decision-making on course offerings, delivery methods, and faculty workload assignments.

Keywords: delivery methods, face-to-face, hybrid, online, virtual learning

Received March 10, 2022; Revised April 12, 2022; Accepted April 21, 2022

Citation: Joanne Hood, Yuchun Chen, Lorraine Jacques, Dustin Hebert, Perceptions of Students and Faculty on the Various Delivery Methods of Instruction. American Journal of Educational Research, 10 (4). 245-252. January 2022. doi:10.12691/education-10-4-13

1. Introduction

Ever since there was teaching and learning, face-to-face instruction has always been the approach to deliver content knowledge and related skills. It is a traditional method through which knowledge and skills are conveyed in a physical space with student-content, student-instructor, and student-student interactions, which are essential to student learning [1]. The in-person interactions create an immediate venue for students “to ask a question, to share an opinion, or to disagree with a point of view”, which is when “a new concept is clarified, an old assumption is challenged, a skill is practiced, an original idea is formed and encouraged, and ultimately, a learning objective is achieved” [2]. In this physical space, both instructors and students are able to observe each other’s body language, facial expressions, and physical reactions during the learning process. These physical cues help students absorb content knowledge more than verbal instructions alone and also allow instructors to make adjustments to the lessons if necessary [3]. This traditional approach has its value and should not be lost as the world starts to adopt technology-based instruction [4]. The importance of teacher-to-student and teacher-to-teacher interactions has many academic and social benefits that cannot be replaced by other instructional methods.

Instead of a physical space, online learning occurs in a virtual space where students interact with the course content, the instructors, and other students using video conferencing technology (e.g., Zoom or Google meet) and/or through a learning management system (e.g., Moodle or Blackboard). Similar to the traditional face-to-face delivery method, students in a synchronous online course attend classes during a specific time and day predetermined by the registrar’s office and receive instruction through video conferencing technology. Those in an asynchronous class, on the other hand, are presented with course materials and evaluation items through a learning management system, which they have 24/7 access to and are given the opportunity to pace themselves in processing the information and completing the required work as long as deadlines are met. Regardless of the mode (i.e., synchronous and asynchronous), the online delivery method is without geographical restriction and thus increases students’ access to education; a student with Internet connection and the required software can participate in a class from anywhere in the world. This online delivery method is attractive to individuals who have part-time or full-time employment, delayed postsecondary education, financial obligations, dependents at home, and/or other factors that make attending face-to-face classes difficult or impossible [5,6].

Adopting the favorable features from the two delivery methods mentioned above, hybrid learning “happens in an instructional context which is characterized by a deliberate combination of online and classroom-based interventions to instigate and support learning” [7]. In this form of learning, course materials are stored in a learning management system and students are required to go through them before a class meeting, which promotes the convenience and flexibility features of an asynchronous online class [8]. During a class meeting, time is spent on problem-solving tasks, small-group discussions, and hand-on activities to advance content knowledge and related skills [9,10]. Hybrid learning is a student-centered, needs-based approach where students are responsible to make sense of the course materials outside the classroom and instructors are to fulfill the needs of the students during the limited time they have in class [9,11,12,13,14]. This type of instruction has been found to increase learning performance and promote individual confidence as students become active learners and participants in the learning environment [9,15,16].

2. Review of Literature

According to [17], communication is defined as “a group of people who are willing and able to help each other” and it “is more than a way a group of people defines itself: it is a capability that can be developed and improved over time” (p. 60). In order to establish an interdependent and supportive learning community, instructors should establish and reinforce rules, routines and expectations, allot time to get to know the students and for them to get to know each other, give tasks and assignments that promote self-efficacy and cooperation, and communicate with students about evaluation of course materials and grades [9,18,19,20,21]. In a traditional classroom or one with a face-to-face component (i.e., hybrid class), this sense of community seems to be built naturally because both instructors and students are in the same physical space where eye contact, body language, other behaviors can be observed to assist with immediate interactions. It is evident that a significantly greater sense of community and connectedness was found in the face-to-face and hybrid classes than in the online classes [20]. With this in mind, instructors who teach online classes may want to use different instructional strategies defined by [22], align their curricula with constructivism practices recommended by [19], and build a sense of community with an emphasis on connectedness using the essential categories for technology professional development suggested by [23].

Previous research has used student performance to compare effectiveness of two or all three delivery methods, and the findings were inconclusive. While some studies found that students in face-to-face classes earned significantly better test scores than those in online classes [24,25,26,27], others indicated no significant difference in the learning outcomes for the two or among the three platforms [21,28,29,30,31]. Interestingly, inconsistent test scores were found within the study itself when [32] compared the overall course performance of the students from one face-to-face section and the three hybrid sections of the same general health class. In this particular study, (1) students in the hybrid sections performed significantly better on the second written exam and the final course grade than those in the face-to-face section, (2) students in the face-to-face section scored significantly higher on the fourth written exam than those in the hybrid sections, and (3) no significant difference was found on the other four sources of performance indicators [32]. Similar results were also found in [2] study when she examined the final letter grades and failing rates between three face-to-face and three online classes over the course of two academic years. She concluded that “learning effectiveness is a complex concept with multiple dimensions”; in other words, student performance alone is not enough to determine which delivery method is more effective than the other [2]. Teaching style, course design, and frequency and quality of feedback provided by instructors, for example, are influential factors in learning effectiveness.

Another comparison that has been studied frequently is students’ learning experience in courses with different delivery methods. The online environment was perceived to be less intimidating and cause less time pressure than the face-to-face setting; hence, timid students may be more apt to engage in an online class than they would in a traditional environment [33,34,35]. This less intimidating virtual space was found to have better participation quality and more in-depth discussions than a physical space [2] [36,37]. [38], on the other hand, noted that being in an online class was more likely to make students feel more isolated, stressed and frustrated than being in a face-to-face class. Having the opportunity to undergo both the online and face-to-face formats, students in the hybrid setting reported to experience a boost in confidence because they had more room to find a comfort zone, whether it was in the virtual space or physical classroom [9,15,16]. These different types of experiences perceived by the students could potentially lead to their preference in one delivery method over the other. If a student has positive experience in face-to-face learning because s/he is able to carry in-depth discussions and receive meaningful feedback from the instructor, s/he may prefer learning in a physical space more than a virtual one. Another student who is not given enough time to process the course content and complete the work or does not feel emotionally safe in a face-to-face class may feel more comfortable working on her/his own and prefer online learning.

However, a student’s learning experience is not always positively associated with her/his preference in one delivery method over the other. According to [39], cost, socializing/networking, time away from work, self-paced learning, immediate access to the instructor, and immediate interaction with participants are the six influential factors when seeking an education and its delivery method. Tuition, books, and other fees are costs that every student has to pay. Taking online or hybrid classes may save additional fees such as rent and transportation-related costs (e.g., gasoline and parking). The ability to meet new people and expand one’s social and professional network may be easier to accomplish in person, but it can also be done virtually, depending on how much effort one would want to spend on this area. Employment and family obligations are two common reasons that make online or hybrid education an attractive option. Students with the need to receive timely feedback from instructors and/or have prompt interactions with peers in class may lean towards face-to-face education. To date, student preference on any of the delivery methods has not been extensively studied [4,29,32,40] and none has been a comparison study of all three delivery methods. With the intention to provide feedback and recommendations to ensure quality instruction and student learning, the purpose of the study was to examine (a) students’ preferences of delivery methods among face-to-face (i.e., all class sessions held on-ground and in-person), hybrid (i.e., some class sessions held on-ground and in-person with some sessions being supplanted by asynchronous instruction), and online classes (i.e., completely synchronous and/or asynchronous courses held in a virtual space) and (b) faculty’s perceptions of the various methods of delivery.

3. Methods

3.1. Instrument

Modified from [41] earlier work, two versions of the Delivery Methods of Instruction Survey were created, one for each of the target populations (i.e., student and faculty). The survey consists of four sections; there are 10 statements on the learning process in section one, nine statements about the learning content in section two, five statements regarding the ease of use on technology in section three, and five demographic questions in the last section. All 24 statements on the first three sections were converted to a reference for all three delivery methods, remaining as much of the original context, sentence structure, and wording from [41] questionnaire in each item as possible. The following example illustrates the conversion of one questionnaire/survey item: 

Original: Incorporating BL has deepened my interest in the subject matter of this course.

Modified: Incorporating this method of delivery has deepened my interest in the subject matter of this course.

All 24 statements and five questions on both versions were described exactly the same with the exception of a few noun phrases catered to the specific target population. For instance:

Student version: Incorporating this method of delivery has deepened my interest in the subject matter of this course.

Faculty version: Incorporating this method of delivery has deepened my students’ interest in the subject matter of this course.

For each of the 24 statements, respondents were directed to rank in order of preference with 1 being the most preferred and 3 being the least preferred delivery method among the face-to-face, hybrid, and online options. As for the five demographic questions at the end, respondents were asked to identify their age, gender, role (i.e., student or faculty), academic area, and experience in taking (or teaching) a course in any of the delivery methods, with the option of “prefer not to answer” for each of the questions.

3.2. Data Collection

An email explaining the purpose of the study and inviting respondents to participate in the modified Delivery Methods of Instruction Survey was sent to all graduate students at a regional university in the southeastern United States during the 2020 COVID-19 pandemic. At the same time, another email with the same information was sent to all faculty at the same university, inviting those who had taught graduate level courses to participate in the survey. A follow-up email was sent to the identified populations respectively one month after the original email distribution. The entire data collection period was two months.

3.3. Subjects

Approximately 900 graduate students were invited to participate in the study, with 121 student responses recorded, but only 53 completed at least 80% of the survey, resulting in a 6% response rate. The survey was also distributed to the faculty, with 107 responses, 40 complete at 80% or more. It was evident that some people started the survey but stopped when they realized that they had not experienced all three delivery methods. After reviewing for completeness and usability of the responses, a total of 93 usable surveys for the study.

4. Data Analysis and Results

4.1. Overall Sample

Because substantial changes were made to the measurement scale of the instrument, an exploratory factor analysis using principal component analysis with Varimax (orthogonal) rotation and Kaiser Normalization was conducted on the 24 items on the modified Delivery Methods of Instruction Survey for each delivery method individually. Initial analysis yielded four factors, explaining 73.8% of the variance, however one factor contained only one item (i.e., The activities taught using this method of delivery are of long duration.) and another item (i.e., I felt my knowledge regarding using Moodle is limited compared to my colleagues/peers.) had a loading below .4 on each factor. Both were removed and the analysis was repeated on the remaining 22 items, yielding three factors and explaining 73.8% of the variance. Factor 1 was labeled “learning experience” (explaining 40.4% of the variance), factor 2 was “self-efficacy as student/faculty” (21.1% of the variance), and factor 3 was “ease of use” (12.3% of the variance). Table 1 shows the items loaded to the same primary factor with similar (within .05) values for the face-to-face, hybrid, and online delivery methods. Because of the strength of the loadings, it was determined that the factor analysis was acceptable [42,43]. Incomplete responses that were still included in the analysis were then examined to ensure that the missing data were not concentrated in any specific area. Table 2 shows the means and standard deviations of the responses for each factor, separated by students and faculty.

Table 1. Factor Loadings and Commonalities for the Modified Delivery Methods of Instruction Survey

Table 2. Means and Standard Deviations for Each Factor by Group

Internal reliability (Cronbach’s alpha) was then calculated for the entire instrument and for each factor according to each delivery method. As Table 3 shows, each delivery method had an overall reliability above .94 and most of the factors were above .8. Ease of use for hybrid and online delivery methods had internal reliabilities of .652 and .783, respectively.

Table 3. Cronbach’s Alpha for the Instrument by Each Delivery Method

4.2. Student Sample

Fifty-three students completed at least 80% of the survey. Most of the students were in their 20’s (n = 27), with 10 in their 30’s, 11 in their 40’s, three aged 50 or older, and two declining to answer. The students also mostly identified as female (n = 28), with 13 males and two declining to answer.

A repeated measures ANOVA was conducted on each factor, using the average ranking across the items in the scale as the dependent variable, to determine if there was a difference in each delivery method. A Greenhouse-Geisser correction was used in each case because the assumption of sphericity was not met. For the first factor, learning experience, analysis determined that there was a significant difference in their preferred method of delivery (F(1.338, 69.574) = 12.406, p = .00). Post hoc tests using the Bonferroni correction showed that students had no significant difference between face-to-face and hybrid but preferred both over online delivery. Analysis on self-efficacy as student/faculty, the second factor, and ease of use, the third factor, determined that there was not a significant difference in their preferred method of delivery (self-efficacy as student/faculty: F(1.454, 74.114) = 2.645, p = .10; ease of use: F(1.411, 73.397) = .273, p = .68). Figure 1 shows the students’ preferences for each factor.

Figure 1. Student Delivery Method Preferences

4.3. Faculty Sample

Faculty demographics were more evenly distributed than the students. Nine of the faculty were in their 30’s, six in their 40’s, 15 aged 50 or older, and 10 declining to answer. Sixteen identified as female, 15 as male, and nine declined to answer.

A repeated measures ANOVA was also conducted on each factor, with the average ranking across the items in the scale as the dependent variable, to determine if there was a difference in each delivery method, with a Greenhouse-Geisser correction because the assumption of sphericity was not met. For learning experience, analysis determined that there was a significant difference in their preferred method of delivery (F(1.713, 66.813) = 40.842, p = .00). Post hoc tests using the Bonferroni correction showed that faculty preferences were for face-to-face, then hybrid, then online delivery. Analysis on self-efficacy as student/faculty also showed a significant difference (F(1.724, 67.255) = 12.496, p = .00), with face-to-face being preferred over both hybrid and online delivery, which were not significantly different from each other. A significant difference was also determined for ease of use (F(1.671, 65.162) = 8.892, p = .00), with face-to-face also being preferred over both hybrid and online delivery, which were not significantly different from each other. Figure 2 shows the faculty preferences for each factor.

Figure 2. Faculty Delivery Method Preferences

4.4. Differences between Students and Faculty

To determine if students and faculty differed in how they rated each delivery method, a repeated measures ANOVA was conducted on each factor. As before, the average ranking across the items in the scale was used as the dependent variable. A Greenhouse-Geisser correction was used in each case because the assumption of sphericity was not met.

For the first factor, learning experience, analysis determined that there was an interaction effect between students and faculty and their preferred method of delivery (F(1.508, 137.271) = 3.681, p = .04). Post hoc tests using the Bonferroni correction showed that faculty preferred face-to-face, followed by hybrid, followed by online delivery, while students had no significant difference between face-to-face and hybrid but preferred both over online delivery (see Figure 3).

Figure 3. Delivery Method Preferences for Learning Experience

Analysis on self-efficacy as student/faculty, the second factor, also determined that there was an interaction effect between students and faculty and their preferred method of delivery (F(1.545, 140.553) = 11.080, p = .00). Post hoc tests using the Bonferroni correction showed that faculty preferred face-to-face over both hybrid and online delivery, which had no significant difference between them, and students had no significant differences between any of the delivery methods (see Figure 4).

Figure 4. Delivery Method Preferences for Self-efficacy as Student/Faculty

For ease of use, the third factor, analysis determined that there was no interaction effect between students and faculty and their preferred method of delivery (F(1.520, 138.348) = 3.184, p = .06), but there was an overall difference between the methods of delivery (F(1.520, 138.348) = 6.204, p = .01). Further analysis of students and faculty separately revealed faculty had a significant difference in their preferred method of instruction (F(1.671, 65.162) = 8.892, p = .00), with face-to-face preferred over both hybrid and online, which had no significant difference between them, and students had no significant difference in delivery method (F(1.411, 73.397) = .273, p = .68) (see Figure 5).

Figure 5. Delivery Method Preferences for Ease of Use

5. Discussion

This study examined students’ preferences and faculty’s perceptions of face-to-face, hybrid, and online course delivery methods at a southeastern United States university in the Spring 2020 when higher education institutions had to shift traditional course delivery methods to online formats. Two versions of the Delivery Methods of Instruction Survey were modified from [41] work and used to collect data. The 24 original items were factor analyzed using principal component analysis with Varimax (orthogonal) rotation and Kaiser Normalization. Two items were dropped after the initial factor analysis. The same principal component analysis procedure was conducted again with the remaining 22 items and yielded three new factors: learning experience, self-efficacy as student/faculty, and ease of use. The overall sample showed interaction effects between students and faculty on the learning experience and self-efficacy as student/faculty. However, no interaction effect was found for ease of use.

The student sample under study showed that they preferred the learning experience in face-to-face and hybrid courses over online learning. This significant finding echoed what [20] concluded that face-to-face and hybrid classes built a greater sense of community and connectedness than in the online classes. It suggests that, when it comes to learning, students still prefer the face-to-face interactions with their teachers and classmates in the same physical space. It was a relief to know that the in-person communication was still valued by the students [4]. Moreover, there was no significant preference over the three delivery methods in terms of self-efficacy as a student. According to [9], self-efficacy is a psychological factor affecting one’s performance and success with minimal assistance from other people. Apparently, either of the delivery methods had a significant impact on what the students had to do in order to be efficient and responsible for their own learning. Lastly, there was also no significant preference over the three delivery methods regarding the ease of use to access class materials and follow along with the instructors. In other words, the students in the present study believed that they would spend just as much time in one type of delivery methods over the other ones. Future practice should consider incorporating the face-to-face component in the learning environment, on-ground and in-person or synchronously in a virtual space, to help students have better experience. Since there was no preference over the three delivery methods, faculty should strive to ensure that students can be successful on their own in the learning process with little to zero difficulty in accessing course content regardless of the delivery formats.

As for faculty, they preferred face-to-face, followed by hybrid, followed by online delivery in the learning experience factor, and they preferred face-to-face over hybrid and online delivery in the self-efficacy as faculty and ease of use factors. The fact that the sampled faculty indicated face-to-face delivery over the other two methods might have something to do with their lack of competence and confidence in the non-traditional delivery methods. Not all faculty possessed the skills necessary to transfer their courses to hybrid or online formats. This perceived lack of technical and pedagogical skills could be a confounding factor in the faculty’s preference for face-to-face instruction. Based on these findings, faculty may need to become better equipped to teach utilizing the two non-traditional methods of delivery in order to enhance teaching and learning for their students. As higher education evolves, administration needs to recognize this need and support their faculty by providing the training and support required to effectively make the shift [44,45]. Ultimately, quality instruction and student learning should occur regardless of course delivery methods.

Limitations to this study must be acknowledged to ensure fair interpretation and application of results. First, the instrument used to collect data for the present student was true perception measures, so findings are based on participants’ self-reports. The participants might not be able to assess themselves accurately because the wording of the statements might be confusing or present different meanings from one person to another. Besides, the statements were subject to all of the biases whether the participants could relate to the different delivery methods or not. There might be some other factors affecting their experiences to the three delivery methods that the survey was not able to reflect on. Second, the participants in this study were limited to the graduate students and faculty at a southeastern university in the United States. Sampling bias should be acknowledged; the participants who completed the survey were the sort of people who would complete a survey. The results presented in this study indicated a bias where the perceptions of the people who rarely complete a survey was underrepresented. Moreover, while participation was not limited to any academic discipline, the sample was inclusive of a single institution that offered degrees in applied and natural sciences, business, education, engineering and science, and liberal arts, which narrowed results and generalizability. Other institutions that offer degree programs other than those mentioned earlier may produce different results. Finally, the study was conducted during the COVID-19 pandemic, and the researchers acknowledge that participants’ perceptions about course delivery could have been impacted by the pandemic’s unanticipated implications. The fact that the faculty and students were informed to teach and learn virtually within a few days’ notice might have a negative (or positive) impact on how they rated the delivery methods of instruction to the 24 statements on the survey.

Future research should include the replication of this study under what would be considered normal circumstances. Recognizing the limitation on perception posed by the COVID-19 pandemic, repeating this study for comparative purposes of the “during pandemic” versus post-pandemic results is a logical next step. A comparison of the two studies’ results could support or defy the limitation we have presented about the pandemic’s impact on participants’ responses. Future research could also survey students’ actual learning experience in the three delivery methods and examine the association with their preferences over the methods. This follow-up study would help explain whether cost, socializing/networking, flexibility with other life obligations, learner personality, access to the instructor, and other factors have the impact on students’ preference over the three delivery methods [2,33,34,35,36,37,38,39]. Another future research on the comparison between effectiveness of the three delivery methods could help formalize a clearer trend regarding student performance in each method of delivery [20,24,25,26,27,28,29,30,32]. Suggested by [2], teaching style, course design, and frequency and quality of feedback provided by instructors could be influential factors in learning effectiveness.

6. Conclusions

When it came to the learning experience, graduate students had no preference between face-to-face and hybrid classes but preferred either one over online instruction. Graduate students had no preference in delivery method for ease of use or self-efficacy as a learner.

Faculty preferred the face-to-face method across all three emerging factors. Not all faculty possessed the skills necessary to transfer from face-to-face to hybrid or online. As higher education evolves, faculty need to become better equipped to utilize the other two methods of delivery.

Collection was limited to students and faculty at one southeastern United States university. While not limited to any academic discipline, the sample is inclusive of a single institution which narrows results and generalizability. Repeating this study for comparative purposes of the “during pandemic” versus post-pandemic results and with faculty at additional institutions are the logical next steps. A comparison of other students’ results could support or defy the limitation presented about the pandemic’s impact on participants’ responses.

References

[1]   | Moore, M. G. (1989). Editorial: Three types of interactions. American Journal of Distance Education, 3(2), 1-7.
[2]   | Ni, A. Y. (2013). Comparing the effectiveness of classroom and online learning: Teaching research methods. Journal of Public Affairs Education, 19(2), 199-215.
[3]   | Lone Eagle Consulting. (n.d.). Lesson two: Comparing traditional and online classrooms. Retrieved from http://lone-eagles.com/curr2.htm.
[4]   | Washington, L. D., Penny, G. R., & Jones, D. (2020). Perceptions of community college students and instructors on traditional and technology-based learning in a hybrid learning environment. Journal of Instructional Pedagogies, 23, 1-11.
[5]   | Mather, M., & Sarkans, A. (2018). Student perceptions of online and face-to-face learning. International Journal of Curriculum and Instruction, 10(2), 61-76.
[6]   | Xu, D., & Jaggars, S. S. (2013). Adaptability to online learning: Differences across types of students and academic subject areas. Retrieved from http://ccrc.tc.columbia.edu/media/k2/attachments/adaptability-to-online-learning.pdf.

[7]  
Boelens, R., Van Laer, S., De Wever, B., & Elen, J. (2015). Blended learning in adult education: Towards a definition of blended learning (Project Report). Retrieved from Adult Leaners Online! website: http://www.iwt-alo.be/wp-content/uploads/2015/08/01-Project-report-Blended-learning-in-adult-education-towards-a-definition-of-blended-learning.pdf.

[8]   | Bergmann, J., & Sams, A. (2012). Flip your classroom: Reach every student in every class every day. International Society for Technology in Education.
[9]   | Li, L., & Yang, S. (2021). Exploring the influence of teacher-student interaction on university students’ self-efficacy in the flipped classroom. Journal of Education and Learning, 10(2), 84-90.
[10]   | O’Flaherty, J., & Phillips, C. (2015). The use of flipped classrooms in higher education: A scoping review. The Internet and Higher Education, 25, 85-95.
[11]   | Fink, L. D. (2013). Creating significant learning experiences: An integrated approach to designing college courses. Jossey-Bass.
[12]   | Galway, L. P., & Cameron, E. (2020). Flipping online learning in public health graduate education. Pedagogy in Health Promotion, 6(3), 212-221.
[13]   | He, K. K. (2014). On the future development of flipped classroom in China: From the nature of flipped classroom. E-education Research, 7, 5-16.
[14]   | Thorne, K. (2003). Blended learning: How to integrate online and traditional learning. Kogan Page.
[15]   | Akcayir, G., & Akcayir, M. (2018). The flipped classroom: A review of its advantages and challenges. Computers & Education, 126, 334-345.
[16]   | Al-Samarraie, H., Shamsuddin, A., & Alzahrani, A. I. (2020). A flipped classroom model in higher education: A review of the evidence across disciplines. Education Technology Research and Development, 68(3), 1017-1051.
[17]   | Cothrel, J., & Williams, R. L. (1999). On-line communities: Helping them form and grow. Journal of Knowledge Management, 3(1), 54-60.
[18]   | Allen, T. (2000). Creating community in your classroom. The Education Digest, 65(7), 23-27.
[19]   | Palloff, R. M., & Pratt, K. (1999). Building learning communities in cyberspace. Jossey-Bass.
[20]   | Ritter, C., Polnick, B., Fink, II, R., & Oescher, J. (2010). Classroom learning communities in educational leadership: A comparison study of three delivery options. Internet and Higher Education, 13, 96-100.
[21]   | Ritter, C., & Polnick, B. (2008). Connections: An essential element of online learning communities. International Journal of Educational Leadership Preparation, 3(3), 1-5.
[22]   | Rovai, A. (2001). Building classroom community at a distance: A case study. Educational Technology Research and Development Journal, 49(4), 39-50.
[23]   | Collins, M. P., & Berge, Z. L. (1996). Facilitating interaction in computer mediated online courses. Proceedings of the FSU/AECT Conference on Distance Learning, Tallahassee, FL.
[24]   | Coates, D., Humphreys, B., Kane, J., & Vachris, M. (2004). No significant distance between face-to-face and online instruction: Evidence from principles of economics. Economics of Education Review, 23, 533-546.
[25]   | Farinella, J. (2007). Professor and student performance in online vs. traditional introductory finance courses. Journal of Economics and Finance Education, 6, 40-47.
[26]   | Gratton-Lavoie, C., & Stanley, D. (2009). Teaching and learning principles of microeconomics online: An empirical assessment. Journal of Economic Education, 40(1), 3-25.
[27]   | Trawick, M. W., Lile, S. E., & Howsen, R. M. (2010). Predicting Performance for online students: Is it better to be home alone? Journal of Applied Economics and Policy, 29, 34-46.
[28]   | Biner, P. M., Welsh, K. D., Barone, N. M., Summers, M., & Dean, R. S. (1997). The impact of remote-site group size on student satisfaction and relative performance in interactive telecourses. American Journal of Distance Education, 11(1), 23-33.
[29]   | Butchey, D., Dandapani, K., & Lawrence, E. (2018). Lessons learned from the MBA program for a successful online MSF program. Journal of Financial Education, 44(1), 127-145.
[30]   | Johnson, S. D., Aragon, S. R., Shaik, N., & Palma-Rivas, N. (2000). Comparative analysis of learner satisfaction and learning outcomes in online and face-to-face learning environments. Journal of Interactive Learning Research, 11(1), 29-49.
[31]   | Milz, S. (2020). Assessing student performance between face-to-face and online course formats in a college-level communications course. The Canadian Journal for the Scholarship of Teaching and Learning, 11(2).
[32]   | Melton, B., Graf, H., & Chopak-Foss, J. (2009). Achievement and satisfaction in blended learning versus traditional general health course designs. International Journal for the Scholarship of Teaching and Learning, 3(1), 1-13.
[33]   | Citera, M. (1988). Distributed teamwork: The impact of communication media on influence and decision quality. Journal of the American Society for Information Science, 49(9), 792-800.
[34]   | McConnell, D. (2000). Implementing computer supported cooperative learning. Kogan Pag.
[35]   | Warschauer, M. (1997). Computer-mediated collaborative learning: Theory and practice. Modern Language Journal, 8(4), 470-481.
[36]   | Karayan, S., & Crowe, J. (1997). Student perspectives of electronic discussion groups. THE Journal: Technology Horizons in Education, 24(9), 69-71.
[37]   | Smith, L. (2001). Content and delivery: A comparison and contrast of electronic and traditional MBA marking planning courses. Journal of Marketing Education, 21(1), 35-44.
[38]   | Maki, R. H., Make, W. S., Patterson, M., & Whittaker, P. D. (2000). Evaluation of a web-based introductory psychology course: Learning and satisfaction in on-line versus lecture courses. Behavior Research Methods, Instruments and Computers, 32, 230-239.
[39]   | Lynn, V. A., Bose, A., & Boehmer, S. J. (2010). Librarian instruction-delivery modality preferences for professional continuing education. Journal of the Medical Library Association, 98(1), 57-64.
[40]   | Berić-Stojšić, B., Patel, N., Blake, J., & Johnson, D. (2020). Flipped classroom teaching and learning pedagogy in the program planning, implementation, and evaluation graduate course: Students’ experiences. Pedagogy in Health Promotion, 6(3), 222-228.
[41]   | Shantakumari, N., & Sajith, P. (2015). Blended learning: The student viewpoint. Annals of Medical and Health Sciences Research, 5(5), 323-328.
[42]   | Beavers, A. S., Lounsbury, J. W., Richards, J. K., Huck, S. W., Skolits, G. J., & Esquivel, S. L. (2013). Practical considerations for using exploratory factor analysis in educational research. Practical Assessment, Research & Evaluation, 18(6), 1-13.
[43]   | de Winter, J. C. F, Dodou, D., & Wieringa, P. A. (2009). Exploratory factor analysis with small sample sizes. Multivariate Behavioral Research, 44(2), 147-181.
[44]   | Hartshorne, R., Baumgartner, E., Kaplan-Rakowski, R., Mouza, C., & Ferdig, R. E. (2020). Special issue editorial: Preservice and inservice professional development during the COVID-19 pandemic. Journal of Technology and Teacher Education, 28(2), 137-147.
[45]   | Philipsen, B., Tondeur, J., Roblin, N. P., Vanslambrouck, S., & Zhu, C. (2019). Improving teacher professional development for online and blended learning: A systematic meta-aggregative review. Education Tech Research Development, 67, 1145-1174.