“Online learning” is a broad category used to describe a number of different approaches to instruction and learning using web-based technologies. While online learning is a relatively young field of study, three themes are evident in the reviewed literature, including the existence of general best practices for managing and teaching online, the importance of communication and relationship building in online learning environments, and the nature of motivational factors that influence student success in online classrooms. While existing research addresses both adult and K-12 learners, with some of these studies focusing on learners in rural places, studies specifically addressing online learning in rural Alaskan schools is extremely limited. The exponential growth of online learning in rural Alaska supports the urgency of further study of best practices in course design, implementation, communication strategies, and motivational supports for the unique student populations in rural areas of the state.
The purpose of this mixed methods study will be to understand students’ experiences as online learners in classes taken to supplement their programs of study in traditional face-to-face school settings and to extract implications for rural Alaskan high schools using online learning to broaden students’ educational experiences. My specific research question is this: What conditions result in successful online learning experiences for rural Alaskan students?
Educators involved in the development of online learning programs, online course design, instruction in online learning environments, and supporting students who are taking online classes can benefit from recent studies related to distance education and online learning. A review of the literature revealed three significant themes related to best practices, communication and relationship building, and motivational factors in online learning.
Best practice recommendations in managing and teaching online are prolific in the literature. For the researcher, reader, educator, or learner who wants to learn how to build and support successful online instructional experiences for students, there is plenty to guide decision making in development of truly excellent and effective online learning for students. While today’s high school students may be considered digital natives, students still require clear and targeted support with technology and protocols during initial experiences with online learning (Malinovski, Vasileva, Vasileva-Stojanovska, & Trajkovik, 2014). “Learning to be an online learner” is quite different from learning to be a successful student in a traditional F2F classroom; thus structuring courses to include ample structures and supports to guide students through the learning experience and to teach and reinforce the routines of a successful online learner are critically important (Stodel, Thompson, and MacDonald, 2006; Kaler, 2011). Frequent, personalized interactions between instructor and student and prompt responses from teachers to students’ inquiries create greater buy-in from learners and result in greater feelings of satisfaction for teachers, as well (Hawkins, Barbour, & Graham, 2011). In addition, engaging a student’s family or at-home support is found to positively influence student success in online learning (Currie-Rubin & Smith, 2014).
Communication and relationship building in online learning environments is critically important to student success and satisfaction. Regardless of whether a student is taking a synchronous or asynchronous online course, there is a plethora of research supporting the importance of frequent, personalized, high-quality communication between and among participants in an online class. The importance of developing cognitive and social “presence” in an online learning environment, according to Stodel, Thompson, and MacDonald (2006), cannot be underestimated if the desire is for learners to feel both connected to a learning community and invested in meaningful learning (Barbour, Siko, Sumara, & Simuel-Everage, 2012; Barbour & Hill, 2011). While the research suggests the establishment of authentic relationships may be more difficult to develop in an online environment, the use of audio and video technologies can both enhance students’ feelings of connectedness and increase students’ abilities to communicate via media that contain “more interpersonal cues to enhance social presence” (Stodel, Thompson, & MacDonald (2006). Hawkins, Barbour, and Graham found that struggling students “miss having social interactions with a classroom teacher” in some online courses (2011); thus, ensuring that online classes include intentionally crafted components aimed at building community and supporting students’ interpersonal, social needs may be as important as providing quality content (Kaler, 2011; Barbour, Siko, Sumara, & Simuel-Everage, 2012). Harvey, Greer, Basham, and Hu (2014) found that students valued interaction and communication with their online teacher more than they valued interaction with their online classmates. Treating students as “uniquely valued individuals” can contribute to students’ success in the traditional F2F classroom (Hadre, Sullivan, & Roberts, 2008), and the literature supports the transferability of this to an online learning environment, as well. An even more significant theme, from my perspective, is the value of meaningful attention to students by teachers and the importance of quality interaction between teacher and students (Kaler, 2011; Currie-Rubin & Smith, 2014).
Motivational factors play a role in student success in online learning. Patterns related to discussion of motivational factors was an unexpected discovery in my literature review. A few studies provided interesting findings related to what motivates students to take online classes, and how those motivations impact student learning and success. “Positive motivation that is internalized and fully adopted by students enables them to self-regulate their own learning and development” (Hadre, Sullivan, & Roberts, 2008). While “positive motivation” in an online learning environment may manifest itself in ways that are slightly different from traditional F2F settings, educators who look to systems that work in traditional classroom environments may be better equipped to motivate online students (Barbour & Hill, 2011). Kaler (2011) and Malinovski, Vasileva, Vasileva-Stojanovska, and Trajkovik (2014) provide evidence that both intrinsic and extrinsic motivation influence students’ success, or lack thereof, in online learning experiences. Student success in online learning, according to Hawkins, Barbour, and Graham (2011), is largely dependent on “internal factors such as motivation, self-regulation, and perseverance,” which can be challenging for younger learners. “Learning on my own” and the ability to self-pace was found to be a significant reason students “like” or prefer online learning (Harvey, Greer, Basham, & Hu, 2014). An implication of this theme is to build in an interview or survey asking and addressing students' motivations prior to begin an online class. This information could be invaluable for teachers and site-based adult staff who are providing academic and motivational support for an online learner.
Synchronous and asynchronous online learning are approached by students differently and require different instructional considerations. When I began my initial note-taking of themes in the various texts, I expected to articulate a pattern that had something to do with the similarities and differences between online classrooms and traditional f2f classrooms. Instead, the theme that emerged was related to the differences between synchronous and asynchronous online learning experiences. "Online Learning" is a broad category used as a catch-all to describe any class taken via a computer. The importance of this theme in the literature lies in implications for design, student engagement, support needs, and instructors' approaches to facilitating a meaningful course for students. The research reveals a significant difference between students' perceptions and behaviors in synchronous and asynchronous online learning environments. The lessons are profound for instructors and support personnel. (Stodel et. al., 2006; Malinovski et. al., 2014; Barbour & Hill, 2011).
The researcher in a mixed methods approach “bases the inquiry on the assumption that collecting diverse types of data best provides a more complete understanding of a research problem than either quantitative or qualitative data alone” (Creswell, 2014, p. 19). An explanatory sequential mixed methods approach has been selected for this study. As noted in Creswell (2014), this particular approach is a form “in which the researcher first conducts quantitative research, analyzes the results and then builds on the results to explain them in more detail with qualitative research. It is considered explanatory because the initial quantitative data results are explained further with the qualitative data. It is considered sequential because the initial quantitative phase is followed by the qualitative phase” (p. 15-16).
A total of twenty high school students from three different high schools in a small, rural Alaskan school district will participate in the quantitative portion of this study. During the initial days of the data collection period, students will be invited to complete a survey with both open- and closed-ended questions about their experiences as online learners. Students will be asked to indicate their willingness to participate in interviews to further discuss topics addressed in the online survey. Follow-up open-ended interview questions will be asked of five students representing a cross-section of the district.
Materials and Procedure
The quantitative phase of the research will utilize an online survey delivered to students via Survey Monkey. Students will complete the survey, asking primarily closed-ended questions, during their assigned e-learning class period. The collection of qualitative data will occur via face-to-face interviews and online questionnaires. Interviews and questionnaires will pose open-ended questions meant to elicit additional information about students’ online learning experiences, as well as to elaborate on data gathered during the quantitative phase. Face-to-face interviews will be digitally recorded and transcribed for data analysis. The collection of quantitative data will occur during the first three days of the four-week data collection window; three days will be allowed for data analysis and the development of qualitative questions based on quantitative data findings. Data collection for the qualitative phase will occur over the course of five days, with one week allowed for data analysis and possible follow-up face-to-face interviews to elicit clarifications, elaboration, or details on the original interviews.
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Barbour, M., Siko, J., Sumara, J., & Simuel-Everage, K. (2012). Narratives from the Online Frontier: A K-12 Student's Experience in an Online Learning Environment. The Qualitative Report, 17(20), 1-19.
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Creswell, J. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (4th ed.). Los Angeles, CA: Sage Publishing.
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Hardre, P. L., Sullivan, D. W., & Roberts, N. (2008). Rural Teachers' Best Motivating Strategies: A Blending of Teachers' and Students' Perspectives.Rural Educator, 30(1), 19-31.
Harvey, D., Greer, D., Basham, J., & Hu, B. (2014). From the Student Perspective: Experiences of Middle and High School Students in Online Learning. American Journal Of Distance Education, 28(1), 14-26.
Hawkins, A., Barbour, M., & Graham, C. (2011). Strictly Business: Teacher Perceptions of Interaction in Virtual Schooling. Journal Of Distance Education, 25(2), 1-13.
Kaler, Collier. (2011). A Model of Successful Adaptation to Online Learning for College-Bound Native American HIgh School Students. University of Montana ScholarWorks. Theses, Dissertations, Professional Papers. Paper 272.
Malinovski, T., Vasileva, M., Vasileva-Stojanovska, T., & Trajkovik, V. (2014). Considering high school students’ experience in asynchronous and synchronous distance learning environments: QoE prediction model. The International Review Of Research In Open And Distance Learning, 15(4). Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/1808/3050
Stodel, E. J., Thompson, T., & MacDonald, C. J. (2006). Learners' Perspectives on What is Missing from Online Learning: Interpretations through the Community of Inquiry Framework.International Review Of Research In Open & Distance Learning,7(3), 1-24.