Editorís Note: This is well-documented research of an important area of concern within the Online Learning Division of Education. Boredom may be a student excuse but a valid one to be considered as evaluation of teaching, whether face-to-face or at a distance. What is essential is recognition of and support of students to positively engage in distance learning- i.e. positive motivation.
Impact of learner engagement on attrition rates
and student success in online learning
Christine E. Schaeffer & George D. Konetes
Attrition rates, learner engagement issues, and concerns relating to student success are growing pains currently plaguing online learning. Defining these issues, the factors behind them and developing potential solutions are concurrent priorities in education theory and application. This article serves to examine the condition of these concerns, the recent developments that have emerged through research, and to provide a critical perspective as to the online learners' progress and course. Improving learner engagement in online courses positively impacts retention rates and student success, however the methods for engaging students are diverse and the level of effectiveness for each method may vary from learner to learner.
Keywords: Online learning, distance education, distance learning, attrition, dropouts, engagement, online community, social networking, learner centered, social presence
Concerns Within Online Learning
Across the country, many secondary schools look towards online programs to supplement existing curriculum as these programs provide high-achieving students the opportunity to enroll in courses not typically available at their physical school. Additionally some secondary schools view online programs as a learning option for at-risk, disengaged teens. Educators struggle to agree that disengagement is even a crisis, let alone something for which districts and individual schools need to extend additional resources to support at-risk students. While online courses and programs sound like an easy and appealing solution, online program attrition rates are consistently higher than attrition rates of traditional on-site delivery methods. Therefore, placing at-risk students into online programs may not be the solution for these disengaged youth. Online coursework requires personal qualities that at-risk students often do not possess or need assistance in cultivating.
A large proportion of the secondary education students in the United States may be considered "at-risk," as they report themselves to be disengaged from their educational experience. In March 2009, a Gallup Student Poll surveying over 70,000 secondary school students from across the United States found that 50% report feeling "not engaged" or "actively disengaged," and 50% of the respondents feel "stuck" or "discouraged" with their educational experience (Lopez, 2009). Disengagement is an indicator that a student may be considered "at-risk" (Bridgeland, Dilulio, & Balfanz, 2009). Educators define "at-risk" students as those at-risk of leaving an academic setting by dropping out, aging out, or expulsion for behavioral reasons (Watson & Gemin, 2008).
Causes of Attrition
Dissatisfaction and isolation among learners are major concerns and causes for high attrition rates in online learning programs, and may be solved in part by redefining and reapplying the concept of community. There is a rapid increase in the number of students enrolled in online learning based courses (Bambara, Harbour, Davies, & Athey, 2009). However, high attrition rates have become a problem that persists despite the overall growth of the field (Van Tryon & Bishop, 2009). These dropout rates were found to range between 15 and 50% greater than those of traditional classroom face-to-face learning courses (Bambara, et al., 2009). Dissatisfaction with online learning is seen as one of the key issues which contribute to these abnormally high rates of student attrition (Lin, Lin, & Laffey, 2008).
Overall dissatisfaction with the learning environment has been traced to various causes, feelings of learner isolation ranking chief among them (Joyce & Brown, 2009). Learner disconnection and lack of immediacy are continually reported as major causes for student dropouts as well as lack of overall satisfaction in online learning based programs (Van Tryon & Bishop, 2009). Developing a sense of community in order to foster connectivity and interaction within online courses is challenging because the concept of community is often viewed as location specific. Changing these preconceptions and encouraging the growth of the notion of community from that of a geographic specific idea to a relationship-based model is important for the success of isolated learners and for online learning as a whole (Joyce & Brown, 2009).
Who is to Blame?
Educators do not appear to agree on a cause of or resolution for the disengagement and dropout problem plaguing the country. Bridgeland, Dilulio, and Balfanz (2009) surveyed high school teachers and principals across the nation about their perceptions of the current state of student engagement and retention. The researchers also included a small sample of recent high school dropouts to garner their input and reactions. Two-thirds of the former students report that they did not work as hard as they could have, because they felt the educational system did not place stringent enough demands on them. They report being bored. Interestingly, 42% of the responding teachers report that boredom is an excuse, and less than half (32%) report that they do not expect all students to meet high academic standards and be prepared for college. In contrast, 70% of the principals believe there is validation to the dropouts' responses, and 87% report there is work to be done to engage students.
Recognizing Traits of Success
Several states and individual school districts are looking towards online options to support and reengage the at-risk student population, but this may not be an adequate solution to the problem. Research exists to demonstrate student success in such online programs (Watson & Gemin, 2008), but additional points must be considered. Demographics and family background impact initial commitment to education and personal goals, which then impacts a student's integration into the academic community and overall degree persistence (Morris, Wu, & Finnegan, 2005; Tinto, 1975, 1993). While this research focuses on traditional-age undergraduate college students, and researchers caution the correlation of higher education findings to K-12 students without validation (Barbour, 2007; Cavanaugh, Gillan, Kromrey, Hess, & Blomeyer, 2004; Ronsisvalle & Watkins, 2005), a significant body of scholarly research currently does not exist pertaining to secondary school student success or attrition in online programs. From the research that does exist, it appears that student qualities necessary for success in online education are consistent across both secondary and higher education settings.
A review of relevant high school and higher education-related literature demonstrates that successful online students are typically goal-oriented (Roblyer & Marshall, 2002-2003) with higher cumulative grade point averages (Diaz, 2002; Dupin-Bryant, 2004; Wojciechowski & Palmer, 2005). In addition, they demonstrate greater determination (Morris, Finnegan, & Wu, 2005) and motivation (McLester, 2002; Morris, Finnegan, et al., 2005; Muller, 2008; Roblyer & Marshall, 2002-2003). Finally, successful online students appear to be actively engaged in the academic experience before enrolling in an online course or program (Morris, Finnegan, et al., 2005), willing to take risks (Roblyer & Marshall, 2002-2003), and able to interact comfortably with basic technology (Dupin-Bryant, 2004; McLester, 2002; Roblyer & Marshall, 2002-2003; Romi, Hansenson, & Hansenson, 2002). In general, students must be ready and prepared to successfully complete an online course or program (Harrell, 2008).
Impact of Engagement on Online Student Retention and Success
College and university administration recognize the impact of student retention on institutional success. Engagement serves as a foundation to successful student retention initiatives. The more engaged a student is, the more likely he or she will remain enrolled in a particular course or in the institution as a whole (Tinto, 1975). Relevant literature, as demonstrated in this essay, suggests that a key element of engagement, particularly in online coursework, is professors' instructional approaches. Therefore, shifting from face-to-face to online learning environments may challenge instructors to rethink their teaching methodologies. Additionally, institutions must consider the type and range of services offered to online students to support their overall college experience.
Incorporating Learner-Centered Instructional Methodologies
A constructivist approach forms the basis of learner-centered instructional methodologies that are relevant and meaningful for students. Constructivist instructors guide learning but do not direct it, for faculties involve students in shaping the learning objectives (Diaz & Bontenbal, 2001). Furthermore, students construct knowledge from relating new information to old knowledge. Therefore, good teaching and engaged learning is contextualized for learners so that it is relevant and appropriate (Adams, 2007).
A learner-centered approach requires flexibility on behalf of course instructors. As the role of instructors in online courses continue to evolve (Beldarrain, 2006), the varied demographics of students enrolled in online courses suggest that these instructors adjust instructional strategies to best meet the needs of their students (Angelino, Williams, & Natvig, 2007; Diaz & Bontenbal, 2001; Reigeluth, 1999). This is not to imply that faculty adjust overall course objectives or expected learning outcomes. Instead, faculty may fine-tune the course learning strategies to meet the objectives and outcomes (Angelino, et al., 2007). Faculty should consider interaction between the faculty and students and students overall while modifying instructional strategies, as instructor responsiveness impacts retention (Herbert, 2006).
Central to constructivist learning methodologies is faculty-to-student and student-to-student interaction. These methodologies require significant interaction between faculty and students and amongst students themselves (Diaz & Bontenbal, 2001). Developing strong and supportive relationships within the course or program increases student comfort with the instructor, each other, the course, and the online learning environment overall (Angelino, et al., 2007).
Offering Effective Online Student Services
The need for student engagement carries beyond academic coursework. Hughes (2004) suggests that institutions offer services to support online learners and mirror those services available to on-site face-to-face students. Online students require services similar to face-to-face students such as academic support and tutoring, career services, club, and extra-curricular lectures and activities (LaPadula, 2003). These services should be student-centered and interactive (Four principles of effective online student services; Hughes, 2004; Lorenzetti, 2006). Moreover, many students crave interactive and responsive services (Four principles of effective online student services; Hughes, 2004).
Developing a Sense of Online Community
Developing online communities which increase social connectedness and presence may help alleviate learner isolation and lessen both dissatisfaction and attrition rates. Social aspects are believed to be a more significant factor contributing to dissatisfaction with online learning than problems with the actual process of learning (Lin, et al., 2008). Developing a sense of community and learner connectedness with other students as well as the instructor has been seen to increase student motivation and overall educational value (Shen, Nuankhieo, Huang, Amelung, & Laffey, 2008). This social connectedness helps to alleviate the anxieties and stresses that lead to student attrition (Van Tryon & Bishop, 2009). Student interaction is a vital component in building a greater sense of community in online courses (Lin, et al., 2008).
Increasing levels and channels of student communications and relations has been explored by a number of avenues using online social networking sites like Facebook and Myspace in order to augment the levels of social presence in a group of learners. These endeavors have been more successful when proper guidance and instruction are given and practiced in regards to using the mediums for proper course-defined procedures and networking (Joyce & Brown, 2009). In addition, the creation of online groups for the purpose of collaboration and knowledge sharing has been studied. Success in these specific instances has hinged on establishing trust among group members; however groups that fail to establish trust experience dissatisfaction and higher levels of attrition (Thoms, Garrett, Herrera, & Ryan, 2008).
Many of the techniques used to foster increased levels of connectedness and social presence involve proactive student participation. However little has been mentioned to address reaching and assisting students who are not generally socially proactive in the context of online learning. According to Van Tryon & Bishop (2009), in face-to-face learning environments there exists the host of nonverbal cues and factors which build immediacy and social presence even amongst students who are generally quiet and non-participatory. Also an instructor can use such information to creatively draw inactive students into classroom events and increase their level of participation. Thus the socially inactive student benefits twofold as physical presence and nonverbal cues benefit immediacy and the instructor may be able to use this superficial immediacy to draw the learner into deeper social involvement. Learners who are not socially proactive however may not derive much benefit from measures taken to increase social collaboration in online learning environments. Thus measures should be taken in order to develop and explore existing theoretical conceptions for advancing community and social presence in online learning. However additional measures should also be taken to account for the learners who may not neatly fit into existing theoretical frameworks.
Without movement towards more individualized and personalized student support and services, online program retention will continue to lag behind physical classroom programs. Independent Schools in Texas and The Florida Virtual School demonstrate this movement by successfully utilizing online programs driven by individualized attention and services to support at-risk secondary students (Watson & Gemin, 2008). Even with added support and individualized attention, educators are still not convinced that all students, especially at-risk students, have the necessary skills to succeed in an online environment (Ronsisvalle & Watkins, 2005; Wojciechowski & Palmer, 2005). Commonly understood characteristics of at-risk students do not come close to meeting the necessary qualities of successful online students as defined in the preceding paragraphs. Therefore, educators may be setting these already risky students up for failure by placing them in an online environment and expecting them to excel.
Instructors must be cognizant of the students enrolled their courses. Some students, especially younger and less experienced students, may not initially realize the responsibilities related to online learning. Therefore faculty may want to consider additional or increased and poignant interaction with students who demographically appear to be at risk of withdrawing or failing. Further, in order to meet the needs of the varied students within one online class, instructors may need to rethink their instructional approach and consider integrating multiple approaches.
Similar to academic coursework, student service professionals must rethink and retool online services to ensure they meet the needs of the targeted population of students. Simply listing a tutoring center's hours and expecting students to come to campus to utilize these services will no longer suffice. If students enrolled in a distance education program are truly studying at a distance, their ability to utilize on-campus services is limited. Therefore students require online services mirroring those services offered to on-campus students, yet offered in cyberspace.
Increased retention in online courses requires colleges and universities as a whole to examine instructional strategies and student services. The integration of learner-centered instructional methodologies and the deployment of student-centered services developed specifically to meet the needs of online learners require increased interaction between faculty and students, university professional staff and students, and among students themselves.
Developing socially-situated online interactive learning communities will likely lead to increased student engagement and reduced student attrition in online programs. It falls to us as researchers to determine the validity of this assertion.
Special thanks to Ms. Jennifer Tissue for assistance with proofreading and formatting.
Adams, Nan B. (2007). Toward a model for knowledge development in virtual environments: Strategies for student ownership. International Journal of Social Sciences, 2(2). Retrieved from Academic OneFile March 13, 2010.
Angelino, L. M., Williams, F. K., & Natvig, D. (2007). Strategies to engage online students and reduce attrition rates. Journal of Education Online, 4(2), 1-14.
Bambara, C., Harbour, C., Davies, T., & Athey, S. (2009). Delicate Engagement: The Lived Experience of Community College Students Enrolled in High-Risk Online Courses. Community College Review, 36(3), 219.
Barbour, M. (2007). Principles of effective web-based content for secondary school students: Teacher and developer perceptions. Journal of Distance Education, 21(3).
Beldarrain, Y. (2006). Distance education trends: Integrating new technologies to foster student interaction and collaboration. Distance Education, 27(2), 139-153.
Bridgeland, J. M., Dilulio, J. J., & Balfanz, R. (2009). On the front lines of school: Perspectives of teachers and principals on the high school dropout problem: Civic Enterprises.
Cavanaugh, C. S., Gillan, K. J., Kromrey, J., Hess, M., & Blomeyer, R. (2004). The effects of distance education on K-12 student outcomes: A meta-analysis. Naperville: Learning Point Associates.
Diaz, D. P., & Bontenbal, K. F. (2001). Learner preferences: Developing a learner-centered environment in the online or mediated classroom. Education at a Distance, 15(8).
Diaz, D. (2002). Online drop rates revisited. The Technology Source, http://technologysource.org/article/online_drop_rates_revisited/.
Dupin-Bryant, R. A. (2004). Pre-entry variables related to retention in online distance education. The American Journal of Distance Education, 18(4), 199-206. Retrieved March 10, 2010 from http://www.usdla.org/html/journal/AUG01_issue/article03.html.
Four principles of effective online student services. (2006). Recruitment & Retention in Higher Education, 20(3), 8.
Harrell, I. L. (2008). Increasing the success of online student. Inquiry, 13(1), 36-44.
Herbert, M. (2006). Staying the course: A study in online student satisfaction and retention. Online Journal of Distance Learning Administration, 9(4).
Hughes, J. A. (2004). Supporting the online learner. In T. Anderson and F. Elloumi (Eds.), Theory and Practice of Online Learning (pp. 367-384). Canada: Athabasca University.
Joyce, K., & Brown, A. (2009). Enhancing Social Presence in Online Learning: Mediation Strategies Applied to Social Networking Tools. Online Journal of Distance Learning Administration, 12(4).
LaPadula, M. (2003). A comprehensive look at online student support services for distance learners. The American Journal of Distance Education, 17(2), 119-128.
Lin, Y., Lin, G., & Laffey, J. (2008). Building a social and motivational framework for understanding satisfaction in online learning. Journal of Educational Computing Research, 38(1), 1-27.
Lopez, S. J. (2009). Gallup student poll national report GALLUP Student Poll. Washington, D.C.: GALLUP Poll.
Lorenzetti, J. P. (2006). Developing effective online student services. Distance Education Report, 10(4), 5-6.
McLester, S. (2002). Virtual learning takes a front row seat. Technology and Learning, 24-36.
Morris, L. V., Finnegan, C., & Wu, S. (2005). Tracking student behavior, persistence, and achievement in online courses. Internet and Higher Education, 8, 221-231. doi: 10.1016/j.iheduc.2005.06.009
Morris, L. V., Wu, S., & Finnegan, C. (2005). Predicting retention in online general education courses. The American Journal of Distance Education, 19(1), 23-36.
Muller, T. (2008). Persistence of women in online degree-completion programs. International Review of Research in Open and Distance-Learning, 9(2), 1-18.
Reigeluth, C. M. (1999). What is instructional design theory? In C. M. Reigeluth (Ed.), Instructional Design Theories and Models: A New Paradigm of Instructional Theory (Vol. 2, pp. 5-29). Mahwah: Lawrence Erlbaum Associates.
Roblyer, M. D., & Marshall, J. C. (2002-2003). Predicting success of virtual high school students: preliminary results from an educational success prediction instrument. Journal of Research on Technology in Education, 35(2), 241-255.
Romi, S., Hansenson, G., & Hansenson, A. (2002). E-learning: A comparison between expected and observed attitudes of normative and dropout adolescents. Education Media International, 47-54. doi: 10.1080/0952398021013122 2
Ronsisvalle, T., & Watkins, R. (2005). Student success in online K-12 education. The Quarterly Review of Distance Education, 6(2), 117-224.
Shen, D., Nuankhieo, P., Huang, X., Amelung, C., & Laffey, J. (2008). Using social network analysis to understand sense of community in an online learning environment. Journal of Educational Computing Research, 39(1), 17-36.
Thoms, B., Garrett, N., Herrera, J., & Ryan, T. (2008). Understanding the Roles of Knowledge Sharing and Trust in Online Learning Communities.
Tinto, V. (1975). Dropout from higher education: A theoretical synthesis of recent research. Review of Educational Research, 45(1), 89-125.
Tinto, V. (1993). Leaving College: Rethinking the Causes and Cures of Attrition (2nd edition ed.). Chicago: Chicago University Press.
Van Tryon, P., & Bishop, M. (2009). Theoretical foundations for enhancing social connectedness in online learning environments. Distance Education, 30(3), 291-315.
Watson, J., & Gemin, B. (2008). Using online learning for at-risk students and credit recovery Promising Practices in Online Education: North American Council for Online Learning.
Wojciechowski, A., & Palmer, L. B. (2005). Individual student characteristics: Can any be predictors of success in online classes? Online Journal of Distance Learning Administration, 8(2), http://www.westga.edu/~distance/ojdla/summer82/wojciechowski82.htm.
About the Authors
Christine E. Schaeffer is currently a Graduate Assistant at Indiana University of Pennsylvania (IUP) in the department of Communications Media. She is also a Doctoral Candidate in the Ph.D. in Communications Media and Instructional Technology program at IUP. Her research interests include distance education, online social media, and higher education administration and leadership.
George D. Konetes is currently a Teaching Associate at the Indiana University of Pennsylvania (IUP) in the Department of Communications Media. He is also a Doctoral Candidate in the Ph.D. in Communications Media and Instructional Technology program at IUP. His research interests include distance education, virtual teams, virtual simulations, and social aspects of text messaging.