LEARNING AT THE SPEED OF LIGHT: DEEP LEARNING AND ACCELERATED ONLINE GRADUATE COURSES by Anastasia M. Trekles ROD SIMS, PhD, Faculty Mentor and Chair KIMBERLY RYNEARSON, PhD, Committee Member CHARLOTTE REDDEN, PhD, Committee Member Feranda Williamson, PhD, Dean, School of Education A Dissertation Presented in Partial Fulfillment Of the Requirements for the Degree Doctor of Philosophy Capella University April 2013 © Anastasia Trekles, 2013 Abstract An increasing number of university programs, particularly at the graduate level, are moving to an accelerated, time-compressed model for online degree offerings. However, the literature revealed that research in distance education effectiveness is still confounded by many variables, including course design and student approach to learning. Particularly in graduate-level coursework, it is essential that students gain deep, expert- level understanding within their given fields, but how accelerated programs can best serve this need has remained largely unexplored. The purpose of this investigative, embedded single-case study was to explore instructional design strategies and characteristics of online, asynchronous accelerated courses and students’ choices of deep or surface learning approaches within this environment. Through qualitative exploration of data from the Revised Study Process Questionnaire, student interviews, and course design analysis of an online, accelerated master's program in educational administration, it was found that these adult learners overall approached learning quite deeply. As an implication for program and instructional designers, course activities that were engaging, hands-on, practical, and collaborative were found to encourage students to adopt deeper approaches more often. When courses were consistent and user-friendly, students were able to adopt routines that allowed them to complete coursework in the limited time that they had, given their many professional and personal obligations. However, when due dates were changed frequently, or when too many exams or less clear and engaging projects were given over those that were more complex and authentic, students tended to adopt more surface approaches to learning. Dedication Many people stood behind me to help make this work possible, including my parents, Bob and Wendy, and many beloved colleagues including Helen, Pam, Bob, Lynn, Emily, and Brandi. Without the many people in my life who have supported me during my doctoral journey, this work may never have come to fruition, so I thank all of them deeply for their support. iii Acknowledgments I would like to thank my mentor, Dr. Rod Sims, for his kind and gentle support throughout my research, as well as my committee members, Dr. Kim Rynearson and Dr. Charlotte Redden for their advice and insightful, thought-provoking observations. I would also like to acknowledge the helpful advice received from a number of outside mentors, including Dr. Edward Vockell, Dr. Emily Hixon, Dr. Dean Larson, Dr. Diana Underwood, and Dr. Gayle Millsaps. iv Table of Contents Abstract ............................................................................................................................. ii Dedication ......................................................................................................................... iii Acknowledgments ............................................................................................................. iv List of Tables ................................................................................................................... ix List of Figures .................................................................................................................. x CHAPTER 1 INTRODUCTION .................................................................................................. 1 CHAPTER 2 LITERATURE REVIEW ..................................................................................... 26 CHAPTER 3 METHODOLOGY ............................................................................................... 53 CHAPTER 4 DATA ANALYSIS AND RESULTS ................................................................... 98 CHAPTER 5 CONCLUSIONS AND DISCUSSION .............................................................. 163 REFERENCES ............................................................................................................... 187 APPENDIX A. THE REVISED TWO-FACTOR STUDY PROCESS QUESTIONNAIRE (R-SPQ-2F) ........................................................................ 195 APPENDIX B. MERRILL’S EFFECTIVE, EFFICIENT, AND ENGAGING DESIGN RUBRIC AND THE SOLO TAXONOMY ....................................................... 198 v List of Tables Table 1. Illustration of the R-SPQ-2F Statements and Their Categorization as Either Surface or Deep and Related to Either Motive or Strategy ........................ 70 Table 2. Table for Collecting Data Related to Accelerated Online Course ILOs Based on the SOLO Taxonomy ............................................................................ 79 Table 3. Overall Surface and Deep Approach Scores with Overall Motivation and Strategy Subscale Score ...................................................................................... 109 Table 4. Surface Motivation Statements with Overall Means per Statement ................. 111 Table 5. Surface Strategy Statements with Overall Means per Statement ..................... 112 Table 6. Deep Motivation Statements with Overall Means per Statement ..................... 113 Table 7. Deep Strategy Statements with Overall Means per Statement ......................... 114 Table 8. All Participants' Surface Motivation (SM), Surface Strategy (SS), Deep Motivation (DM), and Deep Strategy (DS) Scores and Means on R-SPQ-2F ... 116 Table 9. Illustration Displaying Course Objectives for All Analyzed Courses based on the SOLO Taxonomy ..................................................................................... 146 Table 10. Illustration Displaying Summary of First Principles Presence in Each Course ................................................................................................................. 157 vi List of Figures Figure 1. Comparison of SOLO Taxonomy (Biggs & Collis, 1982; Biggs & Tang, 2007) to Revised Bloom’s Taxonomy (L. Anderson & Krathwohl, 2001; Krathwohl, 2002) with sample learning outcome verbs and indication of when schemata become more developed and curriculum moves from quantitative to qualitative phase, beginning at the Relational/Analyzing level (Biggs & Tang, 2007; Bransford et al., 2000). ......................................................................................... 33 Figure 2. Themes revealed by R-SPQ-2F analysis. ........................................................ 118 Figure 3. Themes revealed by interview analysis. ......................................................... 142 Figure 4. Model of interrelationships between themes found in the study and surface motive, surface strategy, deep motive, and deep strategy. .................................. 168 vii CHAPTER 1. INTRODUCTION Introduction to the Problem Distance education is one of the most prevalent and important trends in education today. At all levels, learners expect to be able to work on assignments and projects anytime, anywhere, and far beyond the walls of a traditional classroom (L. Johnson, Smith, Willis, Levine, & Haywood, 2011; Picciano & Seaman, 2008). L. Johnson et al. (2011) noted that new technologies such as tablet computers have allowed this trend to expand exponentially toward ever more innovative and sophisticated mobile learning opportunities. Taking education “on the road” has become commonplace, as illustrated by the growth in online versus traditional enrollment at a rate of nearly ten to one since 2003 (Allen & Seaman, 2010). Many prospective distance learners have also sought out accelerated or intensive academic programs for degree completion, which require far less completion time than traditional programs (C. Johnson, 2009). Millions of people are now learning online and at faster rates than ever before, but are they learning as well, or better, than they have in more traditional settings? As a science of the development of learning experiences, instructional design theories and models have had an extensive impact on the distance education sphere. Merrill (2002) noted that the large array of theories that have been proposed over the years all have value, and that many share core concepts related to the methods and strategies used to design instruction, assessment, and supporting media. One of the 1 primary concepts that instructional design theories share is the goal of helping learners achieve the objectives set before them effectively, in any learning endeavor. In other words, regardless of the instructional context or setting, instructional design principles apply anytime there is a desire to increase learners’ knowledge. This concept is at the heart of the instructional designer’s specialization and core competencies. Within distance education settings, however, observing whether learners are meeting given objectives is no simple proposition. When students engage in online coursework, are they completing it to the instructor’s specifications merely to achieve a grade or particular extrinsic goal? Or, are they truly engaging deeply in the content and gaining intrinsically valuable knowledge? Research shows that graduate education has the ability to enhance critical and higher-order thinking about specialized topics, and those pursuing advanced degrees typically seek such qualities (Clotfelter, Ladd, & Vigdor, 2007; Wier, Stone, & Hunton, 2005). Yet, the movement toward accelerated coursework allows students to transcend both time and place, allowing learners the freedom to work more quickly toward their desired goals (Pastore, 2010; Seamon, 2004). However, regardless of the instructional design of such coursework, deep learning of program objectives and the approaches learners take to get there may be difficult to assess properly, as learners may not be given enough time to adequately internalize course materials. Upon consulting the literature on instructional design, distance education, deep learning, and accelerated coursework, it is clear that more investigation is needed to fully understand the complex interplay that occurs between learners, materials, and time in online graduate programs (Biggs and Tang, 2007; C. Johnson, 2009; Seamon, 2004; 2