1 Motives for Enrolling in Online Leadership Courses: Insights for Superintendents as Employers and as Financiers Theodore J. Kowalski, Professor & Kuntz Endowed Chair, University of Dayton David Dolph, Chair, Department of Educational Leadership, University of Dayton I. Phillip Young, Chair, Department of Educational Leadership, University of South Carolina Robert Mengerink, Superintendent, Cuyahoga County (OH) Educational Service Center Paper presented at the National Conference on Education American Association of School Administrators Nashville, Tennessee, February 15, 2014 For further information: Professor T. J. Kowalski
2 Increasingly, superintendents and principals are asking questions about the quality and effectiveness of distance learning and about the motives of those who take graduate courses in this format. Their inquisitiveness is driven by a responsibility to evaluate post-baccalaureate education completed by current and prospective employees. In some districts, this duty extends to recommending tuition reimbursement for teachers, administrators, and other professional employees. Apprehensions about online courses are not unusual. Across all types of organizations, many employers have expressed negative dispositions toward and distrust of online courses and degrees (Carnevale, 2007; Columbaro & Monaghan, 2009). Although the effectiveness of online and in-class courses has been examined for more than 2 decades, much of this research was conducted outside the education profession and educational administration specifically. Commonly, the studies focused on student satisfaction or comparisons of cognitive outcomes as measured by posttests and grades. As a result, relatively little is known about motives that influence educator decisions to take online graduate courses in school administration. In light of this fact, this study had three primary purposes. 1. To determine the extent to which students enrolled in or planned to enroll in online courses 2. To identify the importance of common motives for enrolling in online courses 3. To examine levels of association between the levels of importance placed on motives and each of two demographic variables (teaching experience and teaching assignment). The research was conducted with students enrolled in a master s degree program in educational administration at a private research university. Findings indicated (a) variations in enrollment choices, variations in the importance placed on four motives, and a statistically significant association between teaching experience and two of the motives. Theoretical Framework The National Center for Education Statistics (The Condition of Education, 2011) reported the number of students enrolled in at least one distance education course increased from 1.1 million in 2002 to 12.2 million in This number is forecasted to exceed 20 million by Consequently, distance learning is expected to account for an even higher percentage of higher
3 education courses in the future. The study of distance education is complicated by several factors including provider differences, especially in mission (not-for-profit versus for-profit universities), program scope (e.g., faculty, degrees), and accreditation. As an example, employers are most likely to have a negative view of online courses and degrees from unaccredited, for-profit institutions (Carnevale, 2007). Understandably, the rapid increase of distance learning has raised questions about the comparability of traditional and online instruction, both in terms of instructional quality and learning outcomes. According to Baker (2003), instructional differences have generally related to three factors: instructor-student interaction (e.g., the extent to which learning is observed or measured in real time), learner interaction (e.g., the extent to which ideas and information are exchanged between and among students), and attendance (e.g., the extent to which students are motivated and accept responsibility for learning). Although differences have been identified in each of these areas, findings do not establish that one instructional format is de facto superior, either in terms of instructional quality or learning outcomes. Nevertheless, two concerns about online courses for school administrators persist. First, instructional quality studies almost always have been based on student perceptions of institutional variables (e.g., Maquire, 2005) and student variables (e.g., Yang & Cornelious, 2005). Yang and Darrington (2010) reported that the most important factors affecting student ratings of instructional quality were peer interactions, instructor feedback, and course structure. Second, the use of distance education to prepare practitioners in an applied science continues to be criticized because learning experiences occur in relative isolation (Beam, 2010). Noting that the development of district and school administrators is fundamentally and irrevocably an interpersonal, relation process, Fusarelli (2004) argued that pre-service and continuing education should not take place via a disembodied and depersonalized delivery system. With respect to student learning outcomes, comparative research literature, including metaanalyses (e.g., Dell, Low & Wilker, 2010; Shachar & Neumann, 2003), also have been unconvincing even though findings have usually been based on valid metrics, such as comparisons of student test scores. Shachar (2008) contends inconclusiveness is largely attributable to differences in treatments, settings, measurement instruments, and research methods. Thus, some scholars continue to question whether the two formats are actually comparable with respect to knowledge acquisition.
4 More recently, researchers have focused more directly on motives for encouraging, approving, and engaging in distance learning. Generally, this line of research has had three foci: social-political, institutional, and student. From a social-political standpoint, the growth of online courses is attributable to externally set agendas, such as state legislation providing approval and incentives for the expansion of this process (Calvert, 2005). Institutionally, many universities decided to offer online degrees and courses because of increased competition for students and dwindling organizational resources (Margolis, 2000; Navarro, 2000). Basically, experiences in educational administration have been the same; that is, both efficiency and market competition have influenced institutional decisions to offer online courses (Kowalski, 2006). Research on student motives for engaging in distance learning has been conducted in several academic disciplines, but most notably in business administration. Scholars examining this issue (e.g., Braun, 2008; Klesius, Homan, & Thompson, 1997) have found convenience, flexibility, and cost savings to be the most common reasons why student have enrolled in online courses. A review of research conducted by Thomerson and Smith (1996) found among many students convenience even trumped satisfaction; that is, students continued to enroll in online courses even when they were dissatisfied with previous experiences. Extant literature also posits that student learning style affects student choices and learning outcomes. Although the concept of learning style is somewhat vague, Grasha (1996) simply describes it as an individual's preferred way of learning. For example, an introverted person may prefer to learn in isolation. Even though a nexus between student learning style and learning outcomes has been reported in several studies (e.g., Aragon, Johnson & Shaik, 2002; Boyd, 2004; Meyer, 2003), the extent to which individual preference for an instructional mode influences enrollment decisions and learning outcomes is largely unknown (Battalio, 2009). Despite agreement that learning preferences are relevant, the extent of their effect on selecting and successfully completing online classes is unanswered (Santo, 2006). Methods and Findings The defined population in this study consisted of 202 full-time and part-time students enrolled in a master s degree program in educational administration at a private research university. The 30-semester hour program consisted of 9 required, 3-semester hour courses and an internship. The institution was selected because students had the option of completing each
5 course in a traditional or online format, the tuition for both instructional modes was the same, and the percentage of online courses had been increasing steadily for the past 5 years. Data were collected via electronic survey and analyzed by the authors during the fall semester, Respondents were assured of confidentiality. The study was guided by three questions: 1. To what extent did the students take or plan to take online courses? 2. What level of importance did students ascribe to four possible motives for selecting online courses (convenience, cost savings, flexibility, and instructional preference)? 3. To what extent was perceived importance of each of the four motives associated with each of two demographic variables: level of teaching experience and level of assignment (elementary or secondary)? The first two research questions were answered by calculating descriptive statistics. The third research question was answered by calculating Pearson correlation coefficients (r). Surveys were completed and returned by 91 students, a return rate of 45%. Since the students were at various stages of the master s degree program, they were asked to indicate how many courses they either had completed or planned to complete via distance learning. The results are shown in Table 1. As these data reveal, the percentage of students who took or planned to take at least half of the required courses online was only 26.6%. Based on a review of extant literature, four possible motives for taking online courses were identified and listed in the survey. Respondents were asked to designate the importance of each motive in relation to online course selection. The outcomes are contained in Table 2.
6 Table 1 Number of Online Courses Number of Online Courses (either completed or to be completed) Frequency Percentage or or or or Total 90* *One student did not answer the question. Table 2 Importance of Possible Motives Motive Level of importance in relation to online course selection Major Moderate Minor None Convenience 59% 14% 11% 16% Flexibility 46% 22% 14% 18% Cost savings 13% 11% 23% 53% Instructional preference 5% 18% 14% 63% Cost savings in this study were related primarily to mileage, parking, and meals because the university had the same tuition for in-class and on-line courses. Based on a combination of the major and moderate response categories, convenience and flexibility clearly were identified as being highly important whereas cost savings and instructional preference were far less important. Data analyses, disaggregated by the percentage of responses, veal that two of the possible four motives for taking online classes were much more important. Combining the major
7 and moderate response categories, the ranking of importance among the possible motives is as follows: Convenience, 73% Flexibility, 68% Cost savings, 24% Instructional preference, 23% Data also were collected for two demographic variables: level of respondent teaching experience (in years) and level of assignment (not employed in education, assigned to an elementary school, assigned to a secondary school, or an assignment spanning both elementary and secondary schools). The average (mean) level of teaching experience was 5.47 years and the standard deviation was With respect to level of assignment, 18.4% were not currently employed in education; 30.3% were employed in elementary schools; 44.7% were employed in secondary schools; 6.6% were employed in positions spanning both elementary and secondary schools. Pearson correlations were calculated to determine levels of association between each motive and each of the two demographic variables. The coefficients are contained in Table 3. Table 3 Associations between Motive Importance and Demographic Variables Importance of motive Respondent Demographic Characteristics Teaching experience Level of assignment Cost savings Convenience.19*.11 Flexibility.29*.04 Instructional preference Note: * = p.05 Only two of the eight correlation coefficients were statistically significant even though the levels of association were not especially high. Students with higher levels of teaching experience (i.e., more than 5 years) indicated that convenience and flexibility were more important than did other respondents.
8 Discussion Findings in this study reveal that most students opted to complete less than half of their required courses via distance learning. This outcome was unexpected since the percentage of online courses in the master s degree had steadily increased over the past 5 years. This finding should be considered in light of two possibilities: a high percentage of the non-responders were students who opted to take most or all of their courses online; students may change their position on taking online classes as they progress through the program. Thus, responders who were in the early stages of the program may actually take more online courses than they anticipate. Findings regarding convenience, flexibility, and cost savings as enrollment motives are generally congruent with a number of earlier studies based on different samples and contexts, such as those conducted by Braun (2008), Klesius, Homan, & Thompson (1997), and Thomerson & Smith (1996). Although some authors have reported a notable association between learning styles and learning outcomes in online courses (e.g., Aragon, Johnson & Shaik, 2002; Boyd, 2004; Meyer, 2003), there is little empirical evidence supporting the contention that instructional preferences influence enrollment decisions (Battalio, 2009). Clearly then, the motives of the educators comprising the defined population in this study were basically consistent with the motives of graduate students in other disciplines. For reasons explained earlier, superintendents and principals are understandably concerned about the quality and effectiveness of online courses. To date, meta-analyses of distance learning research reveals that in-class and online courses are comparable in terms of student learning. Yet, astute administrators recognize that effective continuing education extends beyond the cognitive domain. As superintendents and principals evaluate continuing education, they should be guided by the following realities. There are vast differences among and even within institutions offering online and inclass courses. These differences include institutional motives, instructional rigor, and resources. Thus, investments in continuing education need to be judged independently. Given the nature of school administration, the psychomotor (skills), affective (dispositions), and social (interactive) learning domains are critical. Having students learn in relative isolation raises critical questions that remain unanswered.
9 As demonstrated in this study, student motives for enrolling in online courses differ quantitatively and qualitatively. In many states, principals are now required to facilitate the development of individualized staff development programs for teachers. In this vein, determining teacher motives becomes a logical step to ensuring that the content and instructional approach in graduate courses address real teacher needs. Additional research on selecting online courses in educational administration can and should be conducted within states, university programs, and school districts. Such studies should also examine instructional rigor and learning outcomes not only in the cognitive domain, but also in the psychomotor, affective, and social domains. In the context of individualized continuing education, greater attention to how employees learn is unavoidable. References Aragon, S. R., Johnson, S. D., & Shaik, N. (2002). The influence of learning style preferences on student success in online versus face-to-face environments. American Journal of Distance Education, 16(4), Baker, R. K. (2003). A framework for design and evaluation of internet-based distance learning courses phase one-framework justification, design and evaluation. Online Journal of Distance Learning, 6(2). Battalio, J. (2009). Success in distance education: Do learning styles and multiple formats matter? American Journal of Distance Education, 23(2), Beam, K. (2010). On-line doctorates for administrators. School Administrator, 67(8), Boyd, D. (2004). The characteristics of successful online students. New Horizons in Adult Education, 18(2), Braun, T. (2008). Making a choice: The perceptions and attitudes of online graduate students. Journal of Technology and Teacher Education, 16(1), Calvert, J. (2005). Distance education at the crossroads. Distance Education, 26(2), Carnevale, D. (2007, January 5). Employers often distrust online degrees. Chronicle of Higher Education, A27-A28. Columbaro, N. & Monaghan, C. H. (2009). A land mine for distance education: Employers' views of online degrees. Distance Education Report, 13(15), 1-7.
10 Condition of Education (2011). Distance education in higher education. Washington, DC: U.S. Department of Education, National Center for Education Statistics. Dell, C.A., Low, C. & Wilker, J. F. (2010). Comparing student achievement in online and faceto-face class formats. The Journal of Online Learning & Teaching, 6(1), Fusarelli, L. (2004, January 14). The new consumerism in educational leadership. Education Week, 23(18), 9. Grasha, A. F, (1996). Teaching with style: A practical guide to enhancing learning by understanding teaching and learning styles. Pittsburgh: Alliance Publishers. Klesius, J., Homan, S., & Thompson, T. (1997). Distance education compared to traditional instruction: The students' view. International Journal of Instructional Media, 24(3), Kowalski, T. J. (2006). Part-time faculty and distance education: Quandaries in educational administration s swamp. In F. Dembowski (Ed.), Unbridled spirit: Best practices in educational administration: The 2006 yearbook of the National Council of Professors of Educational Administration (pp ). Lancaster, PA: DEStech Publications. Maguire, L. L. (2005). Faculty participation in online distance education: Barriers and motivators. Online Journal of DE Administration, 8(1). Retrieved from Margolis, M. (2000). Using the Internet for teaching and research: A political evaluation. In R. A. Cole (Ed.), Issues in Web-based pedagogy: A critical primer (pp. 9-22). Westport, CT: Greenwood Press. Meyer, K. (2003). The Web s impact on student learning. T.H.E. Journal, 30(5), Navarro, P. (2000). The promise and potential pitfalls of cyberlearning. In R. A. Cole (Ed.), Issues in Web-based pedagogy: A critical primer (pp ). Westport, CT: Greenwood Press. Santo, S. A. (2006). Relationships between learning styles and online learning: Myth or reality? Performance Improvement Quarterly, 19(3), Shachar, M. (2008). Meta-analysis: The preferred method of choice for the assessment of distance learning quality. International Review of Research in Open & Distance Learning, 9(3), 1-15.
11 Shachar, M., & Neumann, Y. (2003). Differences between traditional and distance education academic performances: A meta-analytic approach. International Review of Research in Open and Distance Learning, 4(2), Thomerson, D., & Smith, C. (1996). Student perceptions of affective experiences encountered in distance learning courses. American Journal of Distance Education, 10(3), Yang, Y., & Cornelious, L. F. (2005). Preparing instructors for quality online instruction. Online Journal of Distance Learning Administration, 8(1). Retrieved from Yang, Y., & Durrington, V. (2010). Investigation of students perceptions of online course quality. International Journal of ELearning, 6(3),
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