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Purdue University Purdue e-Pubs Open Access Dissertations Theses and Dissertations Fall 2014 An exploratory factor analysis and reliability analysis of the student online learning readiness (SOLR) instrument Taeho Yu Purdue University Follow this and additional works at: https://docs.edu/open_access_dissertations Part of the Curriculum and Instruction Commons, and the Higher Education Commons Recommended Citation Yu, Taeho, "An exploratory factor analysis and reliability analysis of the student online learning readiness (SOLR) instrument" (2014). Open Access Dissertations.edu/open_access_dissertations/397 This document has been made available through Purdue e-Pubs, a service of the Purdue University Libraries. Please contact epubs@purdue.edu for additional information. *UDGXDWH6FKRRO)RUP30 5HYLVHG 0814  PURDUE UNIVERSITY GRADUATE SCHOOL Thesis/Dissertation Acceptance 7KLVLVWRFHUWLI\WKDWWKHWKHVLVGLVVHUWDWLRQSUHSDUHG %\ Taeho Yu (QWLWOHG AN EXPLORATORY FACTOR ANALYSIS AND RELIABILITY ANALYSIS OF THE STUDENT ONLINE LEARNING READINESS (SOLR) INSTRUMENT )RUWKHGHJUHHRI Doctor of Philosophy ,VDSSURYHGE\WKHILQDOH[DPLQLQJFRPPLWWHH Catherine E.

Newby Karen Swan Chantal Levesque-Bristol To the best of my knowledge and as understood by the student in the Thesis/Dissertation Agreement, Publication Delay, and Certification/Disclaimer (Graduate School Form 32), this thesis/dissertation adheres to the provisions of Purdue University’s “Policy on Integrity in Research” and the use of  copyrighted material. Richardson $SSURYHGE\0DMRU3URIHVVRU V BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB $SSURYHGE\ Phillip VanFossen 12/08/2014 +HDGRIWKHDepartment *UDGXDWH3URJUDP 'DWH AN EXPLORATORY FACTOR ANALYSIS AND RELIABILITY ANALYSIS OF THE STUDENT ONLINE LEARNING READINESS (SOLR) INSTRUMENT A Dissertation Submitted to the Faculty of Purdue University by Taeho Yu In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy December 2014 Purdue University West Lafayette, Indiana ii This is dedicated to my wife Yunjoung, my two sons Brian & Darren, and to my parents, for their great sacrifices, unconditional love, strong support, and consistent faith in me. iii ACKNOWLEDGEMENTS I would like to acknowledge and express my appreciation to Dr. Richardson, my dissertation committee chair and my best mentor in the world, for advising and guiding me with great generosity, kindness, patience, understanding, and thoughtful consideration.

She has contributed her tremendous time and efforts to help me to better develop my dissertation with her support. Richardson has been my role model as a mentor, an advisor, and a scholar. I have always tried to follow her path and will keep it continuously. In addition, I sincerely grateful to the other members of my committees: Dr.

Timothy Newby, Dr. Karen Swan, Dr. Chantal Levesque-Bristol, and Dr. iv TABLE OF CONTENTS Page LIST OF TABLES.

vii LIST OF FIGURES .3 Purpose of the Study .4 Significance of the Study. REVIEW OF THE LITERATURE .3 Benefits and Challenges of Online Learning .5 Student Retention and Online Learning .6 Review of Existing Student Readiness Instruments .10 Learning Outcomes and Learner Satisfaction .3 Exploratory Factor Analysis (EFA) for Validity. Preliminary Four-Factor Structure. Final Four-Factor Structure.4 Item Analysis for Reliability.

Implications for Research. Implications for Practice. 83 APPENDICES Appendix A: IRB Approval Letter. 98 Appendix B: Cover Letter for Student Online Learning Readiness (SOLR) instrument.

100 Appendix C: Initial Version of Student Online Learning Readiness (SOLR) instrument for EFA. 101 Appendix D: Final Version of Student Online Learning Readiness (SOLR) instrument. 107 vi Page VITA. 108 vii LIST OF TABLES Table.

Five Conditions for Student Retention. Forty One Factors of Student Retention in Online Learning. Summary of Strategies to Overcome Dropout Factors in Online Learning. Summary of Existing Student Readiness Instruments.

Numbers of Students and the List of Courses Participated in This Study. Demographic Information of the Students Participating in This Study. Social Competencies with Instructor Measurement in Online Learning. Social Competencies with Classmates Measurement in Online Learning.

Communication Competencies Measurement in Online Learning. Technical Competencies Measurement in Online Learning. Descriptive Statistics of Each Element of the Student Online Learning Readiness (SOLR) instrument. Eigenvalues, Total Variances Explained for a Preliminary Four-Factor Structure.

The items and preliminary four-factor structure of the Student Online Learning Readiness (SOLR) instrument. Eigenvalues, total variances explained for the final four-factor structure. Factor Correlation Matrix. Item-total Statistics.

The Items and Four-Factor Structure of the Student Online Learning Readiness (SOLR) Instrument after Factor Reduction Procedures. Cronbach’s Alpha for Each Element of the Student Online Learning Readiness (SOLR) instrument. 73 ix LIST OF FIGURES Figure. Online Enrollment as a Percent of Total Enrollment in the United States from 2002 to 2012.

Tinto’s Student Integration Model (SIM). Student Online Learning Readiness (SOLR) Model in Online Learning. Scree Plot for the Student Online Learning Readiness (SOLR) Instrument. 62 x ABSTRACT Yu, Taeho., Purdue University, December 2014.

An Exploratory Factor Analysis and Reliability Analysis of the Student Online Learning Readiness (SOLR) Instrument. Major Professor: Jennifer C. The purpose of this study was to develop an effective instrument to measure student readiness in online learning with reliable predictors of online learning success factors such as learning outcomes and learner satisfaction. The validity and reliability of the Student Online Learning Readiness (SOLR) instrument were tested using Exploratory Factor Analysis (EFA) and reliability analysis.

Twenty items from three competencies, i. social competencies, communication competencies, and technical competencies, were designated for the initial instrument based on the Student Online Learning Readiness (SOLR) Model as a new conceptual model. An exploratory factor analysis (EFA) revealed that four factor-structures of the instrument of student readiness in online learning explained 66.69% of the variance in the pattern of relationships among the items. All four factors had high reliabilities (all at or above Cronbach’s α >.

Twenty items remained in the final questionnaire after deleting one item which cross-loaded on multiple factors (social competencies with classmates: five items, social competencies with instructor: five items, communication competencies: four items, and technical competencies: six items). The four-factor structure of the Student Online Learning Readiness (SOLR) has been confirmed through this study. Educators can use the Student xi Online Learning Readiness (SOLR) instrument in order to discover a better understanding of the level of freshmen college students’ online learning readiness by measuring their social, communication, and technical competencies. In addition, this study was looking at two factors of social integration in Tinto’s SIM and has introduced the Student Online Learning Readiness (SOLR) conceptual model with the purpose to extend Tinto’s social integration to online learning environment.1 Introduction Online learning is becoming an increasingly large part of higher education (Anderson, 2014; Duck & Parente, 2014; Kim, 2011).1 million college and university students took at least one online course by the end of the fall 2012 semester in the United States (Allen & Seaman, 2014).

More than 71% of US colleges and universities offered online courses in 2012 (Allen & Seaman, 2013) and one-third of higher education students took at least one online course in 2012 (Allen & Seaman, 2014). According to the U. Department of Education Distance Learning Report (Bakia, Shear, Toyama, & Lasserter, 2012), the benefits of online learning are: a) to broaden access to the educational resources, b) to personalize learning, c) to provide flexibility in time and location for students, and d) to reduce school-based facilities’ costs. However, the benefits of online learning also bring some challenges into the field of education.

First, the retention rates in online learning courses are 10-25% less than those for traditional face-to-face classes (Ali & Leeds, 2009; Angelina, Williams, & Natvig, 2007; Holder, 2007; Lee & Choi, 2011; Poelhuber, Chomienne, & Karsenti, 2008) in higher education. In other words, over one half of distance students may dropout of their education as a result of online courses (Carr, 2000; Jun, 2005). Second, students who take online courses for the first time tend to feel lonely and socially isolated not only because 2 they are new to the online learning environment but also because they are not familiar with online learning communities (Cho, Shen, & Laffey, 2010; McInnerney & Roberts, 2004). This feeling of social isolation has a significant relationship with distance student attrition (Ali & Leeds, 2009; Link & Scholtz, 2000; Reio & Crim, 2006).

Third, online learning requires learners to assume a greater responsibility for their studies and requires that they have additional skills or competencies (Zawacki-Richter, 2004). For these reasons, it is important to offer distance learners support to help these individuals be successful in their online learning (Watulak, 2012; Zawacki-Richter, 2004). In this manner, it becomes possible to improve student retention rates in online learning in higher education (Ali & Leeds, 2009; Atchley, Wingenbach, & Akers, 2012; Ludwig- Hardman & Dunlap, 2003; Moore & Kearsley, 2005). Moreover, distance learners are more likely to have a lower sense of belonging than face-to-face students (Ma & Yuen, 2010).

According to Goodenow (1993), the concept of a “sense of belonging” at school refers to “the extent to which students feel personally accepted, respected, included, and supported by others in the school social environment” (p. 80), and the positive relationships among a sense of belonging, students’ motivation, and academic achievement were verifed by a series of previous research (Battistich, Solomon, Watson, & Schaps, 1997; Flook, Repetti, & Ullman, 2005; Furrer & Skinner, 2003; Osterman, 2000; Tinto, 1975; Tinto, 1988; Tinto, 1993; Tinto, 1997; Tinto, 1998). In line with the significance of a sense of belonging in an academic field, Tinto (1998) emphasized the positive effect of student-faculty interactions and student- student interactions on students’ sense of belonging. In addition, technological elements, such as computer skills or Internet connections, are important success factors for online 3 learning, including learning outcomes and learner satisfaction (Ben-Jacob, 2011; Herrera & Mendoza, 2011; Watulak, 2012).

For this reason, it is necessary to provide support for distance learners to enhance their social competencies with instructors and classmates as well as their communication competencies and technical competencies so that they can have a better learning experience. One preemptive way to accomplish this is by assisting students to more accurately gauge their readiness for online learning before they start a program. Some universities require their students to take an online learning readiness test before they take online courses in an effort to provide input about those specific skills or areas where the student may have general deficiencies for online learning. However, existing online learning readiness surveys may only be focused on a narrow range of aspects – such as access to technology, basic computer skills, Internet connections or basic learner characteristics rather than upon a more all-encompassing profile which could be studied to address the competencies necessary for one to be truly successful (Dray, Lowenthal, Miszkiewicz, Ruiz-Primo, & Marczynski, 2011).2 Background With respect to learner competencies, the terms “competency” and “competence” have been used as substitutes for one another in many studies.

However, these two terms are slightly different from each other. The International Board of Standards for Training, Performance and Instruction (IBSTPI) defined competency as “a knowledge, skill, or attitude that enables one to effectively perform the activities of a given occupation or function the standards expected in employment” (Spector, 2001, p. On the other 4 hand, according to Kerka (1998), “competence is individualized, emphasizes outcomes (what individuals know and can do), and allows flexible pathways for achieving the outcomes – making as clear as possible what is to be achieved and the standards for measuring achievement” (p. With the understanding of these terms, as so defined, the word “competency” will be used for the purpose of this study.

Competencies are an individual’s perception of his or her ability or capability. For this study social competencies are defined as skills, competencies, and the feeling of control essential for managing social situations and building and maintaining relationships (Myllylä & Torp, 2010). Communication competencies are defined as “the ability to demonstrate knowledge of the socially appropriate communicative behavior in a given situation” (p. Technical competencies are defined as “self-efficacy in technology” (Heo, 2011, p.

The effect of learners’ competencies on their academic achievement has been studied in the field of online education. First, the importance of social competencies for distance learners’ academic achievement has been supported (Chen et al., 2010; Parker et al.