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Factors related to success and satisfaction in online learning.

Academic Exchange Quarterly

| September 22, 2002 | Beffa-Negrini, Patricia A.; Miller, Brian; Cohen, Nancy L. | COPYRIGHT 2002 Rapid Intellect Group, Inc. This material is published under license from the publisher through the Gale Group, Farmington Hills, Michigan.  All inquiries regarding rights should be directed to the Gale Group. (Hide copyright information)Copyright

Abstract

We investigated factors that may relate to positive outcomes in a web-based introductory nutrition course: age, gender, prior nutrition knowledge, nutrition attitude, attitude toward technology, satisfaction with the instructor, and satisfaction with peer interaction. Fifty-four students completed pre-post surveys of knowledge, attitudes, and course satisfaction. When adjusted for multiple variables, satisfaction with the instructor and prior nutrition knowledge related to achievement in nutrition knowledge from pre- to posttest. Age, satisfaction with the instructor, and prior nutrition knowledge predicted course grade. Satisfaction with the instructor and satisfaction with peer interaction related to self-reported learning. Satisfaction with peer interaction, satisfaction with the instructor, and attitude toward technology predicted course satisfaction. Satisfaction with the instructor and age related to a student's willingness to improve nutrition behavior. Satisfaction with the instructor predicted a student's perceived increase in computer competence. Findings provide evidence that student interaction with instructors and peers has important implications for success and satisfaction in online learning.

Introduction

Since the mid 1990s, online web-based instruction has continued to expand as a tool for increased student access to higher education while providing opportunities for active learning and interactive communication among participants (Cravener, 1999). From 1995 to 1998, the percentage of higher education institutions offering asynchronous Internet-based instruction has roughly tripled, from 22 to 60 percent, while the number of those using interactive video and one-way prerecorded video for distance education remained relatively static (USDE, 1999). Furthermore, many institutions plan to begin, or increase, offerings of web-based courses (USDE, 1999). Although computer-mediated distance education is widely popular and encourages collaborative learning among students, not all participants are successful (Cravener, 1999; Diekelmann, 2000). Check sheets for learners (Palloff & Pratt, 1999) and guides for instructors have been published (Harasim, Hiltz, Teles, & Turoff, 1996; Cornell & Martin, 1997; Reeves & Reeves, 1997; Gibbs, 1998; Bischoff, 2000; Collison, Elbaum, Haavind, & Tinker, 2000; Draves, 2000; Hanna, Glowacki-Dudka, & Conceicao-Runlee, 2000; Salmon, 2000) and may be helpful toward increasing student success. However, more rigorous investigations of outcomes in online distance education are needed (Merisotis & Phipps, 1999).

Much of the current research in online web-based instruction compares this method of delivery to the effectiveness of learning in the face-to-face environment (Cravener, 1999; Navarro & Shoemaker, 1999; Rosenlund, Damask-Bembenek, Hugie, & Matsumura, 1999; Yucha & Princen, 2000; Ostiguy & Haffer, 2001; Miller, Cohen & Beffa-Negrini, 2001). Diaz and Cartinal (1999) found online distance students to have more independent learning styles than learners in traditional settings, but they did not measure factors that predict student outcomes such as grades or course satisfaction. To date, there is a scarcity of published research related to student factors that predict success when studying online (Merisotis & Phipps, 1999). An investigation of a telecourse reported that successful students are older and female, have positive attitudes toward the course and instructor, completed higher numbers of college credits, perceived the course to have a difficulty no higher than expected, and have high grade point averages (GPAs) (Bink, Biner, Huffman, Geer, & Dean, 1995). However, we cannot assume that research on televised courses can be applied to web-based instruction. As technology evolves, it is important to re-examine factors affecting student success when learning at a distance. Videoconferencing, email only, or CD-ROM courses (Bink, Biner, Huffman, Geer, & Dean, 1995; Cookson, 1989; Miller, 1998; Roblyer, 1998; Edwards, Hugo, Cragg, & Peterson, 1999) may not be completely appropriate to compare with the asynchronous interactive courses available today. One must carefully consider, along with the course design, the technical design of the online course; student attitudes, perseverance and coping skills when working online; and the qualities of effective online instructors. Other factors to consider are the amount of interaction the students have with other participants (McIsaac, Blocher, Mahes, & Vrasidas, 1999), and the gender (Blocher, 1997) and age (Lively, 1997) of the student.

Theoretical or conceptual frameworks have been recommended to form the basis of research about online distance education (Merisotis & Phipps, 1999). Dunkin & Biddle (1974) proposed a model to guide the study of teaching and learning that involved four major variable types: presage, context, process, and product. Presage Variables are those that influence teachers and teaching behaviors. Context Variables relate to learner characteristics such as their personality traits and learning styles. Process Variables describe the interaction between instructor and student behaviors during the learning. Product Variables encompass knowledge and skills attained or attitudes changed as a result of teaching and learning. For distance education environments, one might expand Dunkin & Biddle's (1974) model to include other variables such as the technology used, instructional design (how the content is delivered to students), and interaction among peers in the course (McIsaac, Blocher, Mahes & Vrasidas, 1999). The following figure presents an expansion of Dunkin & Biddle's (1974) model, used as the conceptual framework for our research. See

The purpose of this paper was to investigate certain Context Variables (age, gender, prior nutrition knowledge, attitude toward nutrition, attitude toward technology) and Process Variables (participant's self-reported effort, amount of time spent learning, satisfaction with instructor behaviors, and satisfaction with the ...

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