Distance education is rapidly expanding in higher education. Between the fall of 1995 and the fall of 1997, the percentage of colleges and universities offering courses by distance education rose from 33% to 44% (National Center for Education Statistics, 2002). An additional 20% of colleges and universities planned to offer distance education courses in the near future. Of all possible distance education formats, the Internet has become the most widely used (National Center for Education Statistics, 2002). The popularity of Web-based courses among administrators, instructors, and students is due to factors related to cost, competition, access, and enhanced opportunities for learning (Martin, 1999; Warbington, 2001).
Nurse educators were quick to recognize the advantages of Web-based courses and have been early innovators in their use for both undergraduate and graduate courses. However, there are disadvantages. Problems associated with Web-based learning include technological difficulties, student support issues, and instructional design (MiUs, Fisher, & Stair, 2001). Of these, instructional design is critical. Because the way students interact in Web-based courses is fundamentally different from the way they interact in face-to-face courses, identifying the pedagogy of communication is a core design issue.
This study compared the effectiveness of different instructional communication methods in a Web-based course on students' cognitive learning, satisfaction, and motivation to complete the course.
Holmberg's (1977) theory of guided didactic conversation provided the framework for this study. Holmberg believed student enjoyment of learning is at the heart of success in distance education, and students enjoy a course when they are connected to the learning experience through conversations guided by the instructor. He described education as communication among students, between instructors and students, and between the subject matter and students. When communication is among students or between instructors and students, it is external conversation. Communication between the subject matter and students is internal conversation. Both are types of guided didactic conversation. When distance education courses are designed so internal and external conversations occur through the instructors' guidance, Holmberg's framework predicts increased cognitive learning, satisfaction, and motivation for students.
Investigators have studied concepts important to communication including student isolation, student and student-teacher relationships, and communication methods. Billings, Gönners, and Skiba (2001) found that nursing students in Web-based courses felt somewhat isolated from instructors and other students. Isolation was negatively correlated with satisfaction and socialization. Socialization was positively correlated with good teaching practices, including active learning, feedback on progress in the course, student-faculty interaction, and interaction with peers. Similarly, Boyle and Wambach (2001) found that graduate nursing students felt connected with faculty and other students in Web-based courses. Stocks and Freddolino (1998) reported that students in a Web-based course had more positive responses to questions regarding student-to-student and student-to-teacher interactions than students in a face-to-face class. Results of Powers and MitchelTs study (1997) indicated students perceived support from peers and had meaningful interactions with them. These researchers also found that students perceived student-teacher communication to be different in Web-based courses. Instructors were viewed less as "purveyors of information" and more as part of the community of learners. Despite geographical distance and lack of face-to-face contact, these students felt they were active participants in a community of learners. However, even when students are satisfied with interactions in Web-based courses, they report a preference for face-toface courses (Wills, Stommel, & Simxnons, 2001).
Whenever a new teaching method is introduced into an educational setting, instructors are interested in determining whether the innovation increases student learning, particularly compared to traditional methods. Most researchers report no differences in learning when distance education courses are compared to face-to-face courses (Dillon & Gabbani, 1998; Moore & Kearsley, 1996; Russell, 1999). Similarly, when examination scores were compared for students in face-to-face courses and those in Web-based courses, no differences were found (Bee & Usip, 1998; DiBartola, Miller, & Turley, 2001; GilUver, Randall, & Pok, 1998; Leasure, Davis, & Thievon, 2000; Sankaran, & Tung, 2001). However, these findings are mitigated by methodological weaknesses, including small samples, use of instruments lacking established reliability or validity, and non-experimental designs. However, if communication is important to learning and if it occurs differently in Webbased courses than in face-to-face courses, a comparison of different Web-based communication designs is warranted. Currently, no studies that have made this comparison exist in the literature.
Student satisfaction is a critical outcome variable for evaluating the effectiveness of Web-based courses. However, study findings related to satisfaction are mixed. Billings et al. (2001) found that satisfaction and convenience were positively correlated. They also found that students who lived more than 100 miles from campus and were age 40 or older were the most satisfied with Webbased courses. Woo and Kimmick (2000) reported no differences in satisfaction between graduate students taking a Web-based nursing research course and those taking a face-to-face class. In contrast, Hará and Kling (1999) identified several problems resulting in student dissatisfaction with Web-based education, including technological problems, minimal and slow instructor feedback, ambiguous Web site instructions, and unclear e-mail messages from the instructor.
Motivation to Complete the Course
Student attrition from distance education courses is a serious and recurring problem (Billings, 1987). The average completion rate for students in distance education courses is 57% (Distance Education and Training Council, 1998). Identifying causes of attrition in distance education has been difficult. Investigators postulate that characteristics of the program, instruction, and students contribute to student success or failure in distance education (Billings, 2000; Moore & Kearsley, 1996).
Schlosser and Anderson (1994) summarized findings from studies on the characteristics of students who are successful in distance education. They noted that instructor feedback early in a course positively affected student completion. However, telephone contact with instructors neither consistently mattered to students nor affected their completion rates. Students' gender, age, occupation, marital status, presence or absence of children, distance from campus, and learning style also had no effect on course completion. Being motivated, already having a college degree, having degree attainment as a goal, and having a high grade point average (GPA) positively affected student completion. Billings and Bachmeier (1994) found evidence that student contact with instructors reduced attrition in distance education courses. There was no consensus in the literature on findings related to the effectiveness of course materials used, the organization of materials, or type of media used on course completion rates (Billings & Bachmeier, 1994; Schlosser & Anderson, 1994).
Variables for this study included communication method and students' cognitive learning, satisfaction with the course, and motivation to complete the course. Following Holmberg's (1977) definitions, communication methods consisted of either internal only conversation or mixed conversation, which combined internal and external conversation. The internal only communication method was defined as online didactic materials, including pages of instruction, animation of course concepts, and practice questions. The mixed conversation communication method included the same online didactic materials and added frequent online communication among students or between the instructor and students using chat rooms, e-mail, and discussion forums. The hypotheses for this study were:
* Hypothesis 1: Students in a mixed conversation Web-based course will learn more than students in an internal only conversation Web-based course.
* Hypothesis 2: Students in a mixed conversation Webbased course will be more satisfied with the course than students in an internal only conversation Web-based course.
* Hypothesis 3: Students in a mixed conversation Web-based course will have higher course completion rates than students in an internal only conversation Webbased course.
A posttest only, control group experimental design was used for this study. Both experimental and control groups were exposed to a 6-week Web-based course on cardiac rhythm interpretation. Course content was divided into four study units. All students received the same content in the same sequence for all four units. However, the instructional design format varied.
The control group received the internal only conversation method, while the experimental group received the mixed conversation method. Students in the control group had exposure to course content, which contained pages of instruction, practice questions, a glossary, case studies, and self-tests. All of these activities were completed independently. The instructor received responses to a case study, answers for examinations, and responses to a semantic differential tool, and responded to students' questions about course content or technical problems. The instructor had no conversations with members of the control group other than to direct them to start the next unit.
Students in the experimental group had exposure to the same four units, including pages of instruction, practice questions, a glossary, and case studies. However, members of the experimental group worked together on case studies, rather than completing them independently. Students in the experimental group also used online chats to enhance their understanding of course concepts, rather than completing an independent self-test. The case studies and self-test questions were identical for both the experimental and control groups.
The instructor's role was more active in the experimental group. The instructor led chat sessions, responded to students in discussion forums, and provided online office hours, and communicated by e-mail when studente had questions. Students in both groups completed midterm and final examinations. All students had access to toll-free telephone technical assistance or free e-mail technical assistance and to an online tutorial located at the Web course site.
The target population for the study was students enrolled in undergraduate nursing programs in the United States who had completed courses in anatomy and physiology and who had access to e-mail and to the Internet using Netscape version 3.0 or higher or Internet Explorer version 4.0 or higher, and who reported competence in using e-mail and the Internet. Nursing students who were already RNs were excluded from the study because of the potential for previous exposure to the subject matter.
Power analysis indicated 32 students per group were necessary to permit confidence in the statistical findings (ot = .05, effect size = .33, power = .80). The effect size selected was based on two meta-analyses of student outcomes using computer-based instruction (Cohen & Dacanay, 1994; Liao, 1998). Because attrition rates for distance education courses are high and because the course was not-for-credit, which may have influenced students' motivation to complete the course, the samples necessary were increased to 87 students per group.
The setting for the study was a Web-based classroom located on the Internet at http://webct.usg.edu. The course was developed using WebCT, a software program for online course management. Students could participate in the study from any physical location as long as a computer connected to the Internet was available.
Four instruments were used to measure study variables. The first was a demographic form with items soliciting data related to students' age, gender, type of nursing program, cumulative grade point average, experience with e-mail and the Internet, and previous distance education experience.
The second instrument measured students' cognitive learning and consisted of two multiple-choice examinations. These investigator-developed examinations tested students' cognitive learning at the knowledge, comprehension, application, and analysis levels. Content specialists assessed examination validity through ratings of item-to-course objective congruence using the procedure described by Rovinelli and Hambelton (1976). Items were retained if an item-objective congruence index score was .75. Using this criterion, each examination consisted of 40 items. Reliability with Cronbach's alpha for the midterm examination was .71, and reliability for the final examination was .79.
The third instrument measured students* satisfaction with Web-based instruction using Alien's (1986) semantic differential scale, Attitude Tbward Computer-Assisted Instruction. The instrument contains 14 bipolar adjectives, each measured on a 7-point scale, and three factors (i.e., comfort, creativity, function). The comfort factor contained bipolar adjectives including pleasant-unpleasant, comfortable-uncomfortable, nonthreatening-threatening, and easy to control-overpowering. The creativity factor contained adjectives such as flexible-rigid, stimulatingboring, creative-unimaginative, and personal-impersonal. The function factor included adjectives such as usefuluseless, meaningful -meaningless, valuable-worthless, appropriate-inappropriate, and time saving-time consuming. Alien (1986) reported Cronbach's alpha for the entire scale as .85. Alpha coefficients for the three factors were .73 for comfort, .66 for creativity, and .78 for function. The fourth instrument measured the number of students who completed the course. Calculations for course completion, attrition, and non-starting were obtained using options available in WebCT.
Institutional review board approval was obtained prior to conducting the study. To enhance recruitment and retention in the study, students who successfully completed the course received 30 hours of continuing education credit from the Georgia Nurses Association. Recruitment procedures included developing a Web site to provide information about and advertise the research study, sending announcements to electronic discussion groups of which nursing faculty and students were members, sending e-mail messages to state student nurses' associations, and mailing letters to every accredited nursing program in the United States. Recruitment efforts were fruitful, and 388 nursing students comprised the sampling frame. From this list, 174 students were randomly selected and assigned to the control or experimental group.
Once selected, students were provided with a Web address and password into WebCT for their assigned group and were asked to complete the demographic information form. Students accessed the Web-based classroom from home, classrooms on college campuses, dormitories, and work. The classroom was active 24 hours per day, 7 days per week for access at students' convenience. A calendar of due dates was provided to keep students on track with course requirements. Content units and examinations were made available on specific dates so students read course materials; worked on case studies, exercises, or in chat rooms; and completed examinations in close time proximity to one another.
Students had 6 weeks to complete the course. Reminders were sent by e-mail to students who had not logged in within a 7-day period. At the end of 3 weeks, students completed the midterm examination. The semantic differential scale measuring student satisfaction was administered at the end of the third content unit. The final examination was completed at the end of the fourth and final content unit. Completion, attrition, and non-start rates were calculated after the final examination was completed.
Demographic characteristics for the sample (N = 174) are shown in Table 1. These undergraduate nursing students were predominantly White women. Black, Asian, Hispanic, Hawaiian, Native American, Iranian, and multiracial students participated in the study, but each of these ethnic groups represented 4% or less of the sample. The majority of students in the sample were younger than age 29 (mean = 28, SD = 8.3). Slightly more than half of the sample was single, and most of the students reported having no dependents (children or older adults) in the home. The majority of students (72%) worked part time or full time while enrolled in their nursing programs. Most of the students were enrolled in programs leading to a bachelor of science in nursing (75%) and were seniors (55%). Students' GPAs ranged from 2.0 to 4.0 (mean = 3.3, SD = .40). Almost one fourth of the sample (23%) reported having earned a previous bachelor or master's degree in another field of study.
The majority (73%) of students used computers located in their homes. The most frequently used Internet service providers were America Online, Yahoo, and Hotmail. Thirty-three percent of the sample had modems with data transfer speeds of 56 kbps, and 33% of the sample did not know the speed of their Internet connection. Nearly 75% of the sample reported their ability to use e-mail as excellent, and 60% reported their ability to use the Internet as excellent.
Thirty-three percent of the sample reported having taken a course previously by distance education. Of those, 93% reported completing the course. Thirty-three percent of students reported Web-based instruction as a method of distance education they had experienced in the past, but only 5% of students reported having used WebCT.
Findings for the Research Hypotheses
Seventy-five students completed the course. Forty students were in the experimental group, and 35 were in the control group. Descriptive data for study variables include possible score range, actual score range, means, and standard deviations (Table 2). The study hypotheses were only partially confirmed.
Demographic Characteristics (N= 174)
Demographic Characteristics (N = 174)
Hypothesis 1: Students in a mixed conversation Webbased course (experimental group) will learn more than students in an internal only conversation Web-based course (control group). Only students who completed both the midterm and final examinations were included in the analysis (Table 2). Means for the midterm examination were 84.78 (SD = 6.94) in the experimental group and 85.17 (SD == 7.17) in the control group. Means for the final examination were 83.05 (SD = 11.10) in the experimental group and 81.94 (SD = 9.78) in the control group.
An analysis of covariance was performed to test for differences in scores between the experimental and control groups. Grade point average was placed in the model as a covariate to control for differences attributable to GPA. No significant group differences were found between scores on the midterm examination (F = 1.115, df= 2, 73,p= .33) or on the final examination (F = .602, (df=2, 73, p = .55).
Hypothesis 2: Students in a mixed conversation Webbased course (experimental group) will be more satisfied with the course than students in an internal only conversation Web-based course (control group). Eighty-five percent of students in the experimental group and 80% of students in the control group completed the semantic differential scale (Table 2). The possible score range for the total scale was 14 to 98. A statistically significant difference (£ = 2.171, df= 60, p = .034) was found between students in the experimental group who had a mean of 85.74 (SD = 9.36) and students in the control group who had a mean of 80.29 (SD = 10.39). Possible score range for the creativity subscale was 4 to 28. A statistically significant difference (t = 2.852, df= 60, p = .006) also was found for creativity between the experimental group (mean = 23.29, SD = 3.21) and the control group (mean = 20.86, SO = 3.50). No significant differences were found for the subscales of comfort (t = 1.334, df= 60, p = .187) or function (t = 1.676, df= 60, p = .09).
Scores on Examinations and Satisfaction Scale
Hypothesis 3: Students in a mixed conversation Webbased course (experimental group) will have higher course completion rates than students in an internal only conversation Web-based course (control group). Motivation was measured by the number of students who completed, withdrew, or never started the course (Table 3).
Completion rates were 40% for the control group and 46% for the experimental group. No significant difference in completion rates were found between students in the experimental and control groups when analyzed with Pearson chi square (x2 = 1.832, df=3,p = .608).
Demographic characteristics were compared for students who completed, withdrew, or never started the course. Significant differences were found for GPA and outcome of previous distance education course. Grade point average was higher for students who completed the course than for students who withdrew from the course (F = 4.271, df= 2, 170, ? = .02). Students who never started the course had a higher incidence of not starting or withdrawing from previous distance education courses (?2 = 12.431, df = 2, ? = .002). Comparisons also were made regarding experience with distance education for students who completed, withdrew, or never started the course. No differences were found regarding experience with e-mail, the Internet, or distance education.
Withdrawal rates following completion of the midterm were equivalent for both the control and experimental groups (?2 = .357, df = 1, ? = .55), but midterm scores were different. Results using analysis of covariance showed the midterm scores (mean = 75, SD = 1.9) of the students who withdrew (n = 19) were significantly lower than the midterm scores (mean = 85, SD = .93) of the students who completed the course (n = 75) (F = 12.894, df= 2, 93, p = .00). The frequency of withdrawal of students in the experimental and control groups at different time points during the course are shown in Table 4.
Non-Start, Withdrawal, and Completion Rates for Experimental and Control Groups
The demographic characteristics of the nursing students in this study were similar to those of RNs in the United States regarding age, gender, and race (Health Resources and Services Administration, 2001). However, the sample was different regarding type of nursing program. Only 23% of students in this study were enrolled in associate degree programs, whereas nationally, 60% of students graduate from associate degree programs (Health Resources and Services Administration, 2001). It is possible that recruitment methods for this study were more visible and easily accessed by students in baccalaureate nursing programs or that these students had more opportunities and experience in using computers as a supportive learning resource.
The experimental intervention (i.e., type of conversation) used in the Web-based course did not affect cognitive learning. Although it is possible the mixed conversation communication method does not improve learning, alternative explanations should be considered. The instructional design for the mixed conversation and internal only conversation groups may have been too similar, resulting in similar learning outcomes. These nursing students also may represent a unique group whose computer skills and motivation to take a noncredit course reduced variation within the sample. In addition, it is possible that course content was eminently suitable to self-tutorial learning so supplementing support through mixed conversation made little difference.
Non-Start, Withdrawal, and Completion Rates for Experimental and Control Groups at Different Points in Time
Satisfaction With the Course
Students in both groups appeared satisfied with the course. However, differences between the groups were found. Satisfaction was higher for students in the experimental group who experienced the mixed conversation communication method. Students in this group found the course to be more "personal," "stimulating," "creative," and "flexible" than students in the control group. This finding supports the theoretical framework of this study in which mixed conversation was expected to yield feelings of personal relation between the instructor and students and among the students. Enjoyment of the learning experience was promoted.
Unsolicited feedback from the experimental group provided further evidence of their satisfaction with the course. Student comments included:
* I ant really learning a lot from this course.
* This course explains things so simply that anyone can understand it. It is fun.
After the course, several students e-mailed the instructor to say they accepted jobs in critical care and felt more prepared than other new graduates because of the Webbased course. Other students asked for letters of recommendation for jobs as cardiac monitor technicians or for help studying for advanced cardiac Ufe support courses. These are additional indicators of course satisfaction.
Motivation to Complete the Course
Motivation to complete the course was higher in the experimental group than the control group, although the difference was not statistically significant. Completion of the course by all student was 43%, which is lower than the national average of 57% for distance education courses (Distance Education and Training Council, 1998). Reasons cited by students for withdrawing were technical problems and inadequate time. Technical problems experienced by students were related to the inability of Web browsers to display course content after students were logged into WebCT. Although the course was hosted on a site with a conscientious administrator and toll-free telephone support and free e-mail support were available, some problems simply could not be resolved. Students who reported time constraints cited heavy school demands, work, graduation, family illness, or marriage as reasons for withdrawal.
A comparison of characteristics of the students who withdrew and the students who completed the course revealed no differences except for GPA and outcome of previous distance education courses. Students who withdrew from this course had significantly lower GPAs than those who completed the course. Students who never started the course had higher withdrawal rates from previous distance education courses than students who completed it. Students who withdrew at midpoint had significantly lower midterm examination scores than those who completed the course. In the authors' experience, withdrawal at midpoint usually indicates students are fearful of failing the course.
These findings support those of Billings (1987) who found that having a high GPA and not withdrawing from other distance education courses, along with having high SAT scores and perceived family support, predicted 44% of variance in course completion. The findings of this study also support those of Schlosser and Anderson (1994) who found that having a high GPA was positively related to course completion, but gender, age, occupation, marital status, and presence of children in the home had no effect on completion of distance education courses.
Limitations for this study include possible sampling bias. All students volunteered to participate in the study, and those who volunteered may have already been comfortable with Web-based instruction. Awarding continuing education credit may not have been an effective incentive for undergraduate students to participate in the study. Awarding academic credit may have reduced attrition over the course of the study.
IMPLICATIONS FOR NURSING EDUCATION
Findings from this study have implications for both nursing education and distance education, particularly when Web-based media are used. These implications relate to issues of theory development and course planning and implementation.
This study was based on guided didactic conversation as a theoretical framework. The framework emphasizes the relationship between personal communication and positive learning outcomes. Guided didactic conversation is intuitively appealing, and it was partially supported by the findings of this study. However, the framework is also narrow in scope and may need to be integrated with cognitive learning theory, learning style theory, and instructional design theory to provide more explanatory power. The complexity of student learning indicates a multifaceted theoretical approach may be necessary. This integrated theoretical approach should strengthen researchers' ability to determine the relevant factors affecting learning outcomes and provide more guidance for nurse educators in constructing Web-based courses.
Practical implications also are implicit in the study. Student satisfaction is critical to any educational experience, and findings from this study demonstrate student satisfaction with Web-based instruction is positively affected by interactions with instructors and other students. This finding is particularly important because satisfaction with faculty and with interactions among nursing students contributes significantly to students' overall satisfaction with nursing programs (Liegler, 1997).
The need for a reliable instructional infrastructure for Web-based courses and technical support for students cannot be overstated. The loss of students from this course due to technical problems was frustrating to the instructor and students. Such attrition could be devastating to nursing programs offering online courses or entire programs online for academic credit. The technical criteria established for entry into this study were detailed and specific, but did not effectively screen students who subsequently encountered technical problems. Nurse educators planning to offer Web-based courses would be well advised to construct and evaluate a test course site prior to soliciting enrollment. A fairly high degree of computer literacy and even more specific and restrictive computer requirements also would reduce technical difficulties. In addition, either a face-to-face or videotaped orientation to the Web-based environment would reduce student frustration, provide an opportunity for students to meet technical support personnel, and provide students with a feeling of connection to the course.
Web-based courses are not for everyone, and it is prudent to counsel students when they consider taking Webbased courses. Students who have low GPAs or who have withdrawn from previous distance education courses should consider taking courses in a face-to-face setting, rather than an online environment. In addition, students should be informed about the required level of computer proficiency, software and hardware, and time expectations for learning and applying course content.
Increasing numbers of nursing programs are using the Internet to either enhance face-to-face courses or to offer courses entirely online. This trend is likely to continue as nurse educators and nursing students become more comfortable with this instructional medium and as the need for nurses and nurse educators increase. However, this instructional resource should be used judiciously because of the scarcity of empirical data to identify appropriate educational strategies for use in Web-based courses. More research is needed to determine the best strategies to enhance outcomes. Development of Web-based courses must be directed at designing educational strategies to achieve specific course outcomes, enhance student satisfaction, and motivate and excite students about learning.
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Demographic Characteristics (N= 174)
Demographic Characteristics (N = 174)
Scores on Examinations and Satisfaction Scale
Non-Start, Withdrawal, and Completion Rates for Experimental and Control Groups
Non-Start, Withdrawal, and Completion Rates for Experimental and Control Groups at Different Points in Time