How Classroom Environment and Student Engagement Affect Learning in Internet-based MBA Courses.

While the number of college courses being delivered via the Internet is increasing rapidly, our knowledge of what makes these courses effective learning experiences for students is still limited. Therefore, I conducted a study that examined the effects of technological, pedagogical, and student

characteristics on student learning in Internet-based MBA courses. Of these characteristics, I found that only those reflecting instructor efforts to create an interactive classroom environment were significantly associated with student learning. Other characteristics such as the perceived ease of use of the course software package, the perceived flexibility of the online classroom environment, and the amount of time students spent logged onto the course Website were not significantly associated with student learning. These findings suggest that while some level of technological sophistication may be important, teaching expertise may be the primary criterion for teaching success in the online classroom environment. The refore, instructors may need to spend more time developing and cultivating instructional skills such as simultaneously working with several smaller groups of students, developing interesting discussion questions, and fostering intimacy. To support this faculty development, business schools will likely need to make substantial infrastructural investments to ensure that their online course offerings are pedagogically and technologically conducive to student learning.

Keywords: Internet-based courses, computer-mediated interaction, distance learning, pedagogy and technology

WHILE DISTANCE EDUCATION has traditionally been conducted by such means as correspondence or voice or video transmission (Gibson & Gibson, 1995), distance education is increasingly conducted via the Internet. Internet-based courses are classes that are delivered primarily or exclusively via the use of e-mail and/or Web pages. While Internet-based courses are presently a single pedagogical approach within the field of distance education, the movement toward delivery of distance education via the Internet is accelerating rapidly. While fewer than 100 colleges and/or universities offered Internet-based courses as recently as 1993 (Hankin, 1999), presently about two-thirds of the 3,200 accredited 4-year colleges and graduate schools in the US now offer courses via the Internet (Clarke, 1999). Business schools have taken the lead in extending this emerging trend to graduate degree programs. At least 25 AACSB-accredited US schools now provide entirely online MBA programs, with many others offering MBA courses via t he Internet (www. academyonline.com, 2000). The acceleration of this trend is due to a variety of factors such as technological advances in both course software and computing capacity, competitive pressures from external stakeholders and alternative sources of education (Moore, 1997; Rahm & Reed, 1997), positive experiences of early adopters (Greco, 1999), and declining MBA enrollments (MacLellan & Dobson, 1997).

In spite of this growth, there still are concerns about Internet-based courses and programs. Some of these concerns are the intensive commitment of time and labor to both develop and take the courses, lack of face-to-face interaction, and questions about their quality relative to traditional classroom-based courses (Dumont, 1996; Grossman, 1999). Combine these concerns with the limited research on Internet-based courses in graduate business education (Arbaugh, 2000a; Ellram & Easton, 1999), and the contention that we may be racing to adopt educational techniques without fully understanding them may be justified (Grossman, 1999).

These concerns prompt at least two questions for graduate business educators: (1) Can graduate business students learn effectively via the Internet? and (2) What factors are most likely to influence student learning in Internet-based MBA courses? Since most of the research to this point on Internet-based courses in business education has been either macro-theoretical approaches to delivery (Leidner & Jarvenpaa, 1995), anecdotal examples (Ellram & Easton, 1999; Taylor, 1996), or atheoretical empirical studies (Arbaugh, 2000b; Hiltz & Wellman, 1997), additional theory-driven empirical research is needed so that criteria for developing Internet-based courses where students can learn effectively are established. Initial efforts to examine this question have focused on comparing student performance in online and traditional classroom settings (Arbaugh, 2000b; Hiltz & Wellman, 1997). The plethora of studies suggesting no significant difference between other types of distance learning and classroom learning have fa iled to convince many educators of the effectiveness of distance education, so most likely the same will be true for Internet-based courses (Russell, 1997). Also, these previous studies have tended to focus on examination performance, which is subject to problems such as how to compare exam performance across different courses and different subject matter and the possibility that examination scores may be influenced more by student compliance than by student learning (Gorham, 1988).

This article provides some preliminary answers to the two research questions raised earlier. I examined the level of perceived learning in Internet-based MBA courses and some variables that may influence it using a sample of Internet-based MBA courses at the University of Wisconsin Oshkosh. To identify these variables, I examined the research literatures of technology adoption, computer-mediated communication, and general distance education. From these literatures, I identified four general factors that may influence student learning in Internet-based courses: (1) the perceived usefulness and ease of use of the course Website; (2) the level of educational flexibility for students and faculty as a result of the asynchronous nature of these courses; (3) the ease of and emphasis on interaction as teaching pedagogy; and (4) student experience with and engagement in Internet-based courses. Of these factors, I found that while students may be able to learn effectively in an Internet-based course, only variables as sociated with classroom interaction were significantly associated with this learning. These findings suggest that graduate business teachers and programs should give attention to cultivating their skill in facilitating and generating student interaction along with developing the technological skill necessary to teach Internet-based courses.

The remainder of this article is divided into three sections. First, the information technology and distance education literatures are reviewed to develop a theoretical foundation for the study. Then, I discuss the results of a study of a multi-course, multi-discipline, multi-instructor study at my university. Last, some implications from the findings are developed to assist researchers, educators, and business schools in future attempts to study and develop Internet-based courses and programs.

Some Theoretical Underpinnings of Online Learning

The literature provides several dimensions along which to frame the study of distance learning.

The Technology Acceptance Model (TAM)

Given the role that technology plays in Internet-based education and the relative newness of this method of course delivery, the Technology Acceptance Model (TAM) seems particularly helpful for predicting whether and why learning takes place in Internet-based courses. The two prominent variables in this model are the perceived usefulness of a technology and the perceived ease of use of a technology (Davis, 1989; Davis, Bagozzi, & Warshaw, 1989). Perceived usefulness has been defined as an indicator of the extent to which a person believes that using a particular technology will enhance their performance, and therefore represents an indicator of an individual's extrinsic motivation to use a technology. Conversely, perceived ease of use refers to the degree to which a person believes that the use of a particular technology will be free of effort, and is therefore an indicator of an individual's intrinsic motivation to use a technology (Atkinson & Kydd, 1997; Davis, 1989). Therefore, according to this model, bel iefs that a new application of technology is useful and easy to use influence the users' attitudes toward the technology and thereby their decision to use the technology. This model has become well accepted in the information technology literature and has been found as a valid predictor of usage of computer software (Bagozzi, Davis, & Warshaw, 1992), e-mail (Gefen & Straub, 1997) and the Web (Atkinson & Kydd, 1997).

In the context of Internet-based courses, this model suggests that higher levels of perceived usefulness and the ease of use of the delivery medium (course Website, software, and the like) will enhance students' attitudes toward their course experience, extrinsically motivate their performance in the course and, therefore, further engage them in the learning process.

The Role of Flexibility In Internet-based Education

Since Internet-based courses depend on computers (Leidner & Jarvenpaa, 1995), the literature on computer-mediated communications (CMC) would seem to be a useful source of information for possible predictors of learning. An emerging perspective within CMC research, developed in part from social information processing theory (Chidambaram, 1996; Walther, 1992), suggests that rather than inhibiting interaction and social bonding as commonly assumed, the flexibility inherent in CMC vehicles such as Internet-based courses may help groups to reach levels of relational intimacy comparable those in to face-to-face groups, albeit over a longer time period. According to this perspective, flexibility in the course comes as a result of the medium's being both place- and time-independent, allowing course conversations to continue over time with periodic interruptions for reflection and personal processing (Dede, 1990; Harasim, 1990). As a result, the Internet-based classroom can become a "virtual learning space" where dyna mic interaction supported by collaborative learning structures produces enhanced conceptual thinking based on the cultivation of multiple points of view (Leidner & Jarvenpaa, 1995; Brandon & Hollingshead, 1999).

The time- and place-independence available through CMC media allows students to have a high degree of flexibility in when and where they participate in Internet-based courses. This flexibility is particularly attractive for graduate management education. The typical consumers of graduate business education, managers or aspiring managers, have had to manage increasing levels of conflict among their jobs, family, and work-related travel throughout the 1990s (Dumont, 1996; Greco, 1999).

Interaction In Internet-based Courses

In the context of distance education, interaction has been defined in terms of four dimensions: (1) learner-to-instructor; (2) learner-to-learner; (3) learner-to-content; and (4) learner-to-interface (Hillman, Willis, & Gunawardena; 1994; Moore, 1989). The criticality of the role of these dimensions of interaction in the learning process has been emphasized in initial research on Internet-based courses. Theoretical work by Leidner and Jarvenpaa (1995) implies that a collaborative learning model would best suit an Internet-based MBA course because of the asynchronous nature of the medium and the relatively high level of prior business experience of the students. Initial evidence suggests that the "verbal" behavior of both the students and the instructor is critical for a successful Internet-based MBA course (Arbaugh, 2000b; Hiltz & Wellman, 1997). Prior studies of computer-mediated communications in general, and Internet-based courses in particular suggest greater volume and more equal student participation in electronically-generated class discussions than in traditional classrooms (Bailey & Cotlar, 1994; Strauss, 1996). However, this learner-to-learner interaction tends to be less efficient because the lack of face-to-face interaction makes it more difficult initially to exchange information and develop social ties (Flaherty, Pearce, & Rubin, 1998; Warkentin, Sayeed, & Hightower, 1997). However, once participants become comfortable with communicating via computer, information exchange and social ties develop due to a shift in the participants' perception of the communication medium and perceived higher quality outcomes of their work compared to the exclusive use of face-to-face discussions (Chidambaram, 1996; Gallupe, Dennis, Cooper, Valacich, Bastianutti, & Nunamaker, 1992).

In spite of the possible difficulty associated with interaction in Internet-based courses, information technology and communication theorists suggest that fitting the medium to the appropriate learning model can help to enhance interaction within the Internet-based course. Other researchers have suggested that instructors need to learn a different set of teaching skills for transitioning into this role of discussion facilitator and manager (Brandon & Hollingshead, 1999), which includes, in part, intentional efforts to achieve verbal immediacy (Freitas, Myers, & Avtgis, 1998; Gorham, 1988) and use of a more conversational style in online comments to help enhance student participation and discussion (Ahearn, Peck, & Laycock, 1992). These findings suggest that instructors need to emphasize each of the three dimensions of interaction within their Internet-based courses and develop methods to facilitate them.

Student Engagement In Internet-based Courses

Prior studies have shown that computing experience is a strong predictor of attitudes toward computers, computer usage (Dyck & Smither, 1994; Whitley, 1997), and Internet usage (Atkinson & Kydd, 1997). In order to gain this experience, users have to spend time engaging computers in a variety of tasks or other activities. Similarly, the amount of experience gained in working with Internet-based courses is expected to enhance their attitudes toward these courses and their performance skill. In an Internet-based course environment, this experience has been associated with logging on to a course's Website more frequently, spending more time logged onto a course's Website, and more likely taking additional courses via the medium in the future (Hiltz, 1994; Ridley & Sammour, 1994). This implies that students who spend more time on the Internet-based course are more likely to be satisfied with the experience and take more ownership of the learning process, thereby increasing their own learning.

Research Method

To answer the research questions presented above, I conducted a survey (Fraenkel & Wallen, 1990).

Survey Sample

The sample was the entire population of class sections conducted using Lotus LearningSpace course software in the MBA program of the University of Wisconsin Oshkosh in 1999. This population was less than 10 percent of the MBA class sections offered by this university during the period of the study. The students in these courses were enrolled in the university's traditional MBA program and were also taking regular classroom courses. The courses in the study were Investment Management (MBA elective course), Organizational Foundations (MBA foundations course), Organizational Leadership and Change, Process and Quality Improvement, and two sections of Professional Skills (all MBA management core courses).

Each course in the study was administered via its respective Website using Lotus LearningSpace software. The five sectors of this software package and their roles are described in Table 1. Students completed the survey either in class or on their own from the course Website in less than fifteen minutes. Any non-responding students were mailed a copy of the survey that they could complete at their convenience. The student response rate was 71.5 percent (97 of 128).

Measurement of Variables

I used several items to measure each of the variables included in the study. Unless otherwise mentioned, each was measured using seven-point Likert-type scales. Student learning was measured using Alavi's (1994) six-item scale. This scale has been a highly reliable measure of student learning in previous studies of distance education courses (Alavi, 1994; Alavi, Yoo, & Vogel, 1997). The scale was also reliable in this study. A factor analysis revealed that these items loaded onto a single common factor with all items loading at .81 or higher and a coefficient alpha of .92.

To measure the variables in the TAM (perceived usefulness and perceived ease of use of a technology), I modified previously used scales by having them refer specifically to the LearningSpace software package. These scales are four items for each of the two variables and have been used extensively in prior studies (Atkinson & Kydd, 1997; Davis, 1989; Davis et al., 1989; Gefen & Straub, 1997). In this study, factor analysis of these items produced two factors that were consistent with findings of previous TAM studies. The lowest factor loadings were .87 for perceived usefulness and .76 for perceived ease of use, with coefficient aiphas of .94 and .88 respectively.

Perceived flexibility was measured with an eight-item scale used in recent studies of Internet-based courses (Arbaugh, 2000a) focusing on the course's format and their ability to arrange their involvement in the course around work, family, and travel. Factor analysis of these items identified two variables: (1) course flexibility, or the ability to arrange the work of the individual course around other activities; and (2) program flexibility, or the ability to arrange the course to serve a student's needs to complete the entire degree program. Five items were loaded on course flexibility, with the lowest loading item at .62 and the other four at .70 or higher. Four items were loaded on program flexibility, with a minimum loading of .51. Coefficient alphas were .87 for course flexibility and .81 for program flexibility. These factors and their respective loadings are consistent with the findings of previous studies.

I measured interaction with eleven items that assessed learner-interface, learner-learner and learner-instructor interaction (Hillman et al., 1994; Thach & Murphy, 1995). The factor analysis of these items identified three variables: (1) Instructor emphasis on interaction, which focused on the instructor's efforts to generate interaction and the outcomes of those interactions (five items loading at .55 or higher, coefficient alpha = .82); (2) ease of interaction, which focused on the lack of difficulty of participating in and following class discussions (three items loading at .77 or higher, coefficient alpha = .84); and (3) classroom dynamics (four items loading at .55 or higher, coefficient alpha = .69). These results were consistent with those of previous studies using the variables.

To measure student engagement in Internet-based courses, I calculated the amount of time students spent on the course Website by multiplying average number of days per week a student spent online by the average number of minutes per online session.

To insure that the relationships between these variables were as direct as possible, I also used gender, student age, and the number of Internet-based courses the student had taken prior to participating in this study as control variables.

Results

Table 2 presents the descriptive statistics for the study. Note that perceived learning had the highest mean and the narrowest range of the variables measured using the survey (mean = 5.37, S.D. = 1.18 on a seven-point scale) which suggests that students in the study generally had a fairly high level of perceived learning.

Table 3 presents the results of a hierarchical regression analysis of these variables. The first-step regression model revealed moderate relationships between age and perceived learning and gender and perceived learning, suggesting that older students and women may have had stronger learning experiences in the online environment (see Table 3). However, these effects became non-significant in the full model. In the full model, the only variables that are significantly associated with learning are the three variables for interaction: instructor emphasis on interaction, ease of interaction, and classroom dynamics (see Table 3). Considering that the learner-intefface dimension of interaction remained constant since all courses used the same course software, these results suggest that instructors play a significant role in enhancing learning in Internet-based courses through their efforts to generate and facilitate interaction.

Discussion

This study tested variables that have been developed in the information technology and distance education literatures for their association with student learning in Internet-based courses. The two clear findings were that students report relatively high levels of perceived learning, and elements of an interactive teaching style were strongly associated with that learning. These findings provide support for findings from initial research that suggest that an interactive teaching style may be the best pedagogical approach to Internet-based courses (Arbaugh, 2000a; Harasim, 1990; Leidner & Jarvenpaa, 1995).

Considering how well established the constructs of the TAM and computer usage are in the technology adoption literature, that fact that neither perceived usefulness, perceived ease of use of the technology, nor student engagement of the course Website were associated with student learning is noteworthy. One possible explanation is that these variables may predict whether an Internet-based course was a satisfying experience, but learning comes through other activities such as reading classroom materials, discussion and reflection. Given the significant association of the classroom dynamics factor with learning, technology is only noticed as a factor if it is perceived as detrimental to the learning experience.

Several limitations make this study's findings tentative. The first is the sample size. The sample size reflects the emergence of the delivery medium, in that a limited number of courses with relatively small enrollments were available to sample (Dumont, 1996). As more business schools offer degree programs online, opportunities will increase to conduct studies with samples large enough to detect smaller effect sizes. Other limitations may impact the generalizability of the study's findings. Since all the class sections used Lotus LearningSpace course software, the findings may not be generalizable to courses using other software packages. This suggests that similar studies should be conducted using other course software packages. Also, the students in these courses were enrolled in the university's regular MBA program and were taking these courses along with courses in physical classrooms. This may prevent the study's findings from being applicable to programs that are offered completely online and do not a llow students to take courses in both formats. Lastly, since there were no classroom-based control groups, it can't be said with certainty that these findings are unique to the Internet-based environment.

Implications and Areas for Future Research

In spite of the study's limitations, it provides some interesting implications and challenges for a variety of audiences. For instance, the primary implication for business educators is that teachers matter in the online educational environment. Instructors have from substantial to complete control over ease of interaction, emphasis on interaction, and classroom dynamics. This suggests that instructors need to develop and cultivate instructional skills such as dividing a class into effective smaller groups of students, developing interesting discussion questions, and fostering intimacy in the online environment. This also could mean that the idea of using online courses as a cost reduction tool for delivering MBA programs may be unfounded.

The fact that perceived ease of use of the course software was not associated with learning suggests that, at least for now, pedagogical approaches may be more important than the technology in determining the effectiveness of these courses. However, this doesn't mean that technology issues can be ignored. The instructor's familiarity and ability to use course software packages and items such as audio, video, and Web links will allow him/her to create a comfortable virtual classroom where students find it easier to interact because of reduced navigational challenges of the course Websites.

The results of the study also carry implications for researchers. In addition to addressing concerns related to the limitations of this study, several opportunities emerge for researchers of Internet-based management education to advance theoretical and empirical work. Researchers can build on this study by incorporating additional independent variables. Based on the role that characteristics of interaction and learning played in this study, an expansion of virtual classroom characteristics could be a good starting point. Educational communication researchers have called for additional study of the effects of instructor immediacy in Internet-based learning environments (Freitas et al., 1998). The study of instructor immediacy could provide additional insights into the nature of virtual classroom interaction and how instructors may generate it more effectively. Other instructor-based variables could include instructor attitudes toward the course and technology (Webster & Hackley, 1997), instructor experience, and skill level with the medium.

While the study found that an interactive style was associated with student learning in online courses, much more work on identifying specific effective interactive behaviors needs to be done. More refined measures of activities such as small group formation and selection (Chidambaram, 1996; Warkentin et al., 1997), conversational style (Ahearn et al., 1992), encouragement of sharing of student experiences, and discussion synthesis (Althaus, 1997) could help refine the behaviors that make these courses attractive and valuable.

Finally, the findings hold several implications for graduate business education programs. One of the biggest challenges may be acquiring and using resources to operate both physical and online degree programs simultaneously, particularly when initial indications are that the students who take these courses represent different markets (Greco, 1999). If faculty do matter as much as the findings of this study suggest, then business schools need to make substantial investments in faculty technological and pedagogical development to teach in the virtual environment. However, training faculty to teach effectively in both virtual and classroom environments, maintaining dedicated equipment and ensuring adequate technical support likely will be both time-consuming and expensive. One possible solution to this challenge may be to charge a premium for the flexibility of taking Internet-based courses. However, such premiums will require MBA programs to know their market well to ensure that they gauge the price elasticity of their courses accurately.

This study examined factors that may influence student learning in Internet-based courses and found that pedagogical rather than technological factors were most strongly associated with learning. In the midst of cries that Internet-based technologies could signal the downfall of academic business schools (Moore, 1997), these findings provide grounds for optimism. However, the optimism must be tempered with the realization that these pedagogical skills must continually improve through personal and professional investment by both faculties and business schools so that they can continue to survive and thrive in this changing environment.

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