A Factor Analysis of the Distance Education Surveys "Is Online Learning Right for Me?" and "What Technical Skills Do I Need?"

By Hall, Michael C. | Quarterly Review of Distance Education, Winter 2009 | Go to article overview

A Factor Analysis of the Distance Education Surveys "Is Online Learning Right for Me?" and "What Technical Skills Do I Need?"


Hall, Michael C., Quarterly Review of Distance Education


INTRODUCTION

There is a general consensus that the number of students receiving an education through distance education has continued to grow steadily (Instructional Technology Council, 2007; National Center for Education Statistics, 2004; Saba, 2005). However, some students have found the distance education environment less attractive than the on-campus environment (Lorenzetti, 2005a). This may have contributed to the lower retention rates reported for distance education students (Carr, 2000; Nash, 2005; O'Brien & Reneer, 2002; Scalese, 2001). The lower retention rates for distance education students has led several researchers to discuss the need for preassessments to identify students who might have difficulties in a distance learning environment (Biner, Bink, Huffman, & Dean, 1995; Buchanan, 1999; Lorenzetti, 2005b; Maki & Maki, 2003; Restauri, 2004; Valasek, 2001). However, commonly used readiness questionnaires given to students prior to the start of a course may not be useful in selecting students who will do well in and be satisfied with technology-mediated courses (Maki & Maki).

A study was conducted by Hall (2008) to determine the predictive validity of two survey instruments, "Is Online Learning Right for Me?" and "What Technical Skills Do I Need?" The survey "Is Online Learning Right for Me?" was developed by the Northern Virginia Community College Extended Learning Institute. The survey "What Technical Skills Do I Need?" was developed by Palm Beach Community College. Both surveys are 15-question, forced response, self-scoring guides that have face validity for individual traits and skills believed to contribute to potential success in an Internet-based course (Buchanan, 1999; Noah, 2001). Each response is assigned a numerical value. A total score is calculated by summing the individual question scores. The survey is designed such that the higher the total score, the greater the presumption for success in a distance education course. Copies of the survey items responses are provided in Tables 1 and 2. An abbreviated list of colleges and universities using one or both of these surveys include Ivy Tech Community College, Colorado Community College, Palm Beach Community College, University of Minnesota, Wisconsin Technical College, and the University of Maine.

In the predictive validity study by Hall (2008) copies of the surveys were distributed to 340 students enrolled in traditional on-campus courses enrolled on three different regional campuses of a Midwestern community college. Copies of the surveys were placed on web servers for 289 students enrolled in web-based distance education classes at the same community college campuses. Multiple regression models were constructed using the two scores from the survey instruments and categorical variables representing the type of course as the independent variables. The final semester grade percentage was used as the dependent variable. A total of 228 traditional on-campus students and 83 distance learning students completed the two surveys and received a final grade percentage in their courses.

The multiple regression model developed from the on-campus student data predicted 7% of the observed variance in final grade percentages. All of the observed variance was explained by the type of course (business, computer information services, criminal justice, or early childhood development) taken by the student.

The multiple regression model constructed from data obtained from the distance education students predicted 20% of the observed variance in the final semester grade percentage. However, Hall (2008) observed that scores from the two survey instruments accounted for only 8% of the total variance in the final semester grade percentage. Hall concluded that the two web-based surveys had little predictive validity.

DATA ANALYSIS

The data used for the factor analysis were the survey answers obtained in the Hall, 2008 study of community college on-campus and distance education students.

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