Success Predictors in Graduate Online Learning

Success Predictors in Graduate Online Learning

Doris Gomez (Regent University, USA) and Mihai C. Bocarnea (Regent University, USA)
Copyright: © 2009 |Pages: 9
DOI: 10.4018/978-1-60566-198-8.ch289
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Abstract

Student attrition, although some to be expected, comes at a high cost. Failure to complete studies is recognized as a personal loss for the individual, an economic loss for the universities, and an intellectual loss for society. As educational institutions increasingly develop and support online education programs to serve the instructional needs of adult population in a growing and ever changing global economy, student attrition becomes an even more significant issue. While national statistics for completion rates of distance education students are not easily available, dropout rates are believed to be 10-20% higher than for in-person learning (Carr 2000; Frankola 2001). Some scholars have indicated that, depending on the program, dropout rates for distance education are much higher, in the 30-50% range (Moore & Kearsley, 1996; Lorenzetti 2002). Whatever the attrition rate is, the reality is that too many students do not persist in their endeavor to achieve a degree in higher education although they made a conscious decision to enroll in higher education and took the steps needed to attend graduate school. While extensive research efforts have been used to develop and improve theoretical models of student retention or persistence, a concern of many administrators remains the ability to predict as early as possible the likelihood of a student dropping out of school. In light of research findings that the strongest predictor of graduation is a student’s conformity with the characteristics of those who have graduated from the same institution or program previously (Ash, 2004; Mansour, 1994), the purpose of this chapter is to determine the profile of students who are being retained and those who drop-out, by employing data obtained as early as possible in the application and matriculation process.
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Introduction

Student attrition, although some to be expected, comes at a high cost. Failure to complete studies is recognized as a personal loss for the individual, an economic loss for the universities, and an intellectual loss for society. As educational institutions increasingly develop and support online education programs to serve the instructional needs of adult population in a growing and ever changing global economy, student attrition becomes an even more significant issue. While national statistics for completion rates of distance education students are not easily available, dropout rates are believed to be 10-20% higher than for in-person learning (Carr 2000; Frankola 2001). Some scholars have indicated that, depending on the program, dropout rates for distance education are much higher, in the 30-50% range (Moore & Kearsley, 1996; Lorenzetti 2002). Whatever the attrition rate is, the reality is that too many students do not persist in their endeavor to achieve a degree in higher education although they made a conscious decision to enroll in higher education and took the steps needed to attend graduate school. While extensive research efforts have been used to develop and improve theoretical models of student retention or persistence, a concern of many administrators remains the ability to predict as early as possible the likelihood of a student dropping out of school. In light of research findings that the strongest predictor of graduation is a student’s conformity with the characteristics of those who have graduated from the same institution or program previously (Ash, 2004; Mansour, 1994), the purpose of this chapter is to determine the profile of students who are being retained and those who drop-out, by employing data obtained as early as possible in the application and matriculation process.

Key Terms in this Chapter

Application Summary Score: The Application Summary Score, developed by the school under investigation, is composite of the following sections, which will be reviewed and scored by three independent reviewers for each applicant to the doctoral program in leadership studies: Undergraduate GPA, Graduate GPA, Level of Difficulty of Masters Program, Other Degree GPA, GRE Scores, MAT Scores, GMAT Scores, TOEFL Scores for International Students, Writing Sample Content Quality, Writing Sample Technical Quality, Goal Clarity, Professional Experience, Quality of Leadership Experience, Quantity of Leadership Experience and Recommendations. Each section is scored by each reviewer on a range from 0 to 3, resulting in three application summary score for each applicant. The range of the Application Summary Score is as follows: (0-1.99) reject, (2.00-2.09) accept space available, (2.10 – 3.00) accept.

Student Retention: In this study, measured by matriculation in the doctoral program culminating in graduation from the program and being awarded the doctoral degree. It is coded 1 for persistence (i.e., students are awarded the doctoral degree) and coded 0 for non-persistence (i.e., students left before being awarded the doctoral degree).

Myers-Briggs Type Indicator: Katherine Briggs and her daughter Isabel Briggs Myers (1897-1979) developed the Myers-Briggs Type Indicator (MBTI). The instrument classifies individuals on four dimensions, the first three being identical to Jung’s theory. Jung postulated that everyone has a basic attitude to the world, which indicates the directions in which energies or interests flow: (a) to the outer world of people and events (extroversion, E) or (b) to the inner world of ideas (introversion, I) Either type processes information through the senses (S) or by intuition (N) and makes decisions on the basis of this information either by logical, impersonal analysis (thinking, T) or on the basis of personal, subjective values (feeling, F). Through sensation (S) we establish what is present, with its meaning determined through thinking (T). Feeling (F) tells us its value, with possibilities delineated by intuition (N). The fourth dimension added by Myers and Briggs is called judgment (J) and perception (P). Judging (J) types prefer to seek system, order, organization, and tend to be dependable, responsible, and decisive. Perceptive (P) types tend to be more receptive and curious about their environment and events. Some people like to gather more and more information and adapt to situations as they arise (P), while others prefer to lead a more structured, ordered existence, making lists, and trying to control events (J). Factor analysis, and further empirical validation, has supported sixteen possible results for combining the outcomes of the four dimensions (EI, SN, TF, and JP).

Online Learning: Online learning encompasses many models and delivery modalities. In this study, online learning will refer to a model in which there is limited face-to-face interaction, communication is primarily asynchronous, no videos are required, all classroom activities take place online, and three short on campus residencies during the first three years of enrollment are mandatory. Occasionally, telephone communication may be involved. Online learning, in this study, does not include the traditional form of distance education or correspondence courses via mail, nor does it cover instruction via CD-ROM or CD-RIM interactive. The model is based upon the use of the Internet to access specific software that allows students and instructors entry into fora and online classrooms. This model is used in numerous university degree programs, certificate studies, and corporate training and educational development.

Watson-Glaser Critical Thinking Assessment: Watson and Glaser’s definition and instrument for measuring critical thinking is the oldest and most widely used instrument measuring critical thinking in research literature. In fact, the very concept of critical thinking in education flows from a combination of viewpoints emanating from the pioneer work of Glaser and his view of dispositions, logic, and skills. Glaser suggested that critical thinking involves five steps: (1) recognizing and defining a problem; (2) clarifying the problem by collecting necessary facts or information and recognizing assumptions being made; (3) formulating possible explanations; (4) selecting one or more possible hypotheses for testing and verification and (5) making final conclusions. This definition provides the theoretical foundation for the Watson-Glaser Critical Thinking Assessment (WGCTA), which is an 80-item, multiple-choice test with five subtests. Numerous researchers have used the WGCTA to examine the relationship between critical thinking and academic performance.

Leadership Practices Inventory: Through in-depth analysis of the times when leaders perform at their best, Kouzes and Posner identified five practices most common in extraordinary leaders. When leaders are at their personal best they (1) challenge the process; (2) inspire a shared vision; (3) enable others to act; (4) model the way; and (5) encourage the heart. The Leadership Practices Inventory (LPI), a self-rating tool, was developed to measure the extent to which a leader practices these five behaviors. and is considered a very useful tool for assessing an individual’s leadership behaviors. The instrument has been utilized extensively in studies related to job satisfaction, commitment, productivity, and leader comparisons. Researchers that focused on the aforementioned five leadership practices by conducting research using the operational definition of effective leadership behavior established by Kouzes and Posner confirmed the process of determining leader’s effectiveness by their successful use of the five leadership practices.

Predictive Models of Retention: Refer to the development of instruments that will allow institutions of higher education to predict retention or attrition and assist at-risk students on a more individualized basis. Predictive modeling provides the ability to develop profiles of students who are likely to drop out could allow higher education administrators to implement intervention strategies.

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