Barriers to Completion of a Nurse-Midwifery Distance Education Program |
Katherine Camacho Carr, Judith T. Fullerton, Richard Severino, M. Kate McHugh
VOL. 11, No. 1, 111-131
A survey of 59 student drop-outs and 68 successful graduates (controls) was conducted to identify demographic factors, personal and program characteristics, and academic habits that lead to student success or withdrawal from a two-year distance education program in nurse-midwifery. The findings of the study indicate that, despite remarkable similarity in personal characteristics, other demographic variables, and equal academic achievement at entry into the Community-based Nurse-Midwifery Education Program (CNEP), there were several important differences between the two study groups that contributed to academic success or lack of it. The greatest differences that were identified from these data were related to the academic habits of the two respondent groups and the ways in which these groups related to the program and its faculty.
A forward stepping logistic regression approach revealed that none of the demographic variables were found to be predictive of dropping out. However, three variables from among those describing academic habits did contribute significantly to a logistic regression model for predicting the odds of dropping out (p
Un sondage a été effectué auprès de 59 décrocheurs et 60 finissants reçus (groupes de contrôle) d'un cours à distance de deux ans d'infirmière sage-femme, pour connaître les facteurs démographiques et personnels, ainsi que les caractéristiques du cours et les habitudes scolaires des étudiants, qui favorisaient la réussite ou le décrochage scolaire. Selon les résultats de cette étude, malgré une ressemblance étonnante entre les facteurs personnels, d'autres variables démographiques et les réalisations scolaires équivalentes au moment de l'inscription au programme communautaire à distance d'infirmière sage-femme (CNEP), on a pu dégager entre les deux groupes étudiés plusieurs différences importantes responsables de la réussite ou de l'échec scolaire. Ainsi, les données recueillies ont permis de constater que ces grandes différences résident essentiellement dans les habitudes scolaires des répondants des deux groupes et dans les relations entre les étudiants et les cours enseignés et entre les étudiants et les professeurs.
À partir de la méthode de régression progressive logistique utilisée, aucune des variables démographiques n'est responsable du décrochage. Cependant, selon un modèle de régression logistique, trois des variables relatives aux habitude scolaires peuvent permettre de prédire dans une grande mesure les possibilités de décrochage (p.
The Frontier School of Midwifery and Family Nursing (FSMFN) was established in 1939 as the second school of nurse-midwifery in the United States. Over 700 family nurse-midwives have graduated from this program. In the late 1980s, the FSMFN revised its educational mission and strategy to focus on the development of opportunities for qualified nurses who were placebound adults with family and work responsibilities and to prepare practitioners for service within a growing network of freestanding birth centres. The Community-based Nurse-Midwifery Education Program (CNEP) was begun in the summer of 1989 through the efforts of the FSMFN, the Maternity Center Association, the National Association of Childbearing Centers (NACC), and Case Western Reserve University (CWRU) Frances Payne Bolton School of Nursing, with partial funding from the Pew Foundation.
The CNEP curriculum design is based on the construct of distance education, including self-directed modular academic learning activities with telecommunications support and supervised clinical practica arranged in or near the home community. Students also attend several on-campus intensives, but they do not relocate for the majority of the two-year program. Students may also elect to complete the MSN at CWRU by taking several courses also offered as intensives on campus in Cleveland, Ohio. In six years of operation (1989-1995), CNEP had admitted fourteen classes, ranging in size from 25 to 114. Over 300 nurses graduated over that time period and successfully completed the national certification examination in nurse-midwifery. Graduate surveys indicated that more than 30% of the graduates served in rural/frontier communities, and almost all served vulnerable populations.
The study was designed to examine the various individual and program factors that lead to successful completion of this new educational pathway and to identify areas for program improvement that might lead to completion for those who drop out. The study focused on those few individuals (approximately 10%) who did not complete the educational program and withdrew or were asked to leave for academic or other reasons.
Distance education utilizing written learning materials, telecommunications, and computer-mediated instruction is a recent innovation. Few studies have been conducted that focus on the personal and academic characteristics of successful or unsuccessful students within the new educational design. Several of these studies have also examined the characteristics of the academic institution.
A study conducted in Venezuela (Siquera de Freitas & Lynch, 1986) investigated the reasons for the high attrition in an introductory course offered to postsecondary students. Course instruction was televised to several regional centres. Video materials were supplemented by self-paced learning activity modules. Few demographic differences were found that were predictive of not completing this course. Those who were not successful were more likely to be older students. Students who did not successfully complete this course entered the course with academic preparation similar to successful students. However, they were less likely to use the academic resources available in the distance education centres, devoted less time to study of course materials, pursued other professional work or study simultaneously with course enrolment, and perceived the course work and materials to be more difficult when compared to those who were successful. Four factors were found that significantly predicted 43% of the variance in successful completion of the course. These four factors included satisfaction with the mode of learning, frequency of use of distance education centre resources, the balance of work and study, and the student’s positive view of learning activities.
The particular impact of distance education on women was explored by Pym (1992) in a study of Canadian nursing students enrolled in a televised course. She noted that women continued to function in traditional homemaker and parental roles during their course work and that problems seemed to exist when the additional role of student threatened to disrupt “the existing order.” She found that strong academic and social support were important facilitators of success in this program.
Pym also noted that the degree of comfort with communications (non-computer) technology was associated with success. Cragg (1994) studied graduate nurses enrolled in a computer-mediated conference course. She found that the degree of frustration experienced by students was directly related to satisfaction and success. She recommended that a strong technical support and advisory system was essential if computer-mediated distance learning was to be a successful teaching-learning mode.
Roberts (1984) also reports ways and means of reducing early student drop-out rates. He points out that the student is at greatest risk of dropping out in the first term or semester of study. He also reviews the work of three theorists (Otto Peters, Borje Holmberg, and David Stewart) related to student drop-out from distance education. Peters’s theory stresses the industrial-ization and mass production approach of distance education, which puts the student at risk of being isolated and disconnected from the school. Student support systems are seen as the primary prevention for attrition. Holmberg argues that distance learning is self-study but not private study, and he encourages the use of real and simulated forms of didactic conversations to prevent student drop-out. Stewart is also concerned about interaction and communication between the student and the system. Stewart stresses the importance of immediate feedback to the student and the presence of an intermediary or advisor to provide help and advice. Based on this review of the three theorists, Roberts recommends a balance of activities be included in distance education programs that include independent activities and those that are interactive.
Wilkinson and Sherman (1989) discuss procrastination, or the needless postponement of task completion, as a reason for student attrition from distance education. Interviews with faculty revealed several interventions that faculty believed would prevent attrition, including giving students a realistic picture of course/program demands, providing a structure for progress, reduction of other responsibilities that may take priority over coursework, and the recognition of procrastination as a potential negative impact.
In her master’s thesis, Brindley (1987) studied attrition and completion in distance education from the student’s perspective. Specifically, she asked 40 randomly selected students what incidents hindered or facilitated persistence in their course of study at Athabasca University, an open distance education university serving students across Canada. She identified 13 categories of student experiences that influenced attrition, including background and defining characteristics, such as age and gender; academic variables, such as study habits and course availability; environmental variables, such as finances, hours of employment, outside encouragement, and family responsibilities; and psychological variables, such as perceived utility of studies, satisfaction, goal commitment, and stress. The study concludes that retention strategies for distance education revolve around changing students’ experiences or the way in which they perceive or respond to them.
Kember (1989) proposed a conceptual model of drop-out from distance education. This model identifies the attrition process as a complex interaction of family background, individual attributes, prior educational attainment, goal commitment, and institutional commitment as predictor variables. Academic performance, the social system within the school, and academic and social integration are identified as mediating variables. These factors lead to the individual’s evaluation of the cost and benefit of continuing to progress in the academic program or of withdrawing from participation. This conceptual model provided the framework for instrument development for the present study.
A non-equivalent control group design was selected.
The study posed two questions. Question 1: Would those who dropped out of the distance education program differ from those who successfully completed the program on any personal, demographic, or academic variable? Question 2: Could drop-out be accurately predicted from data available in early phases of admission or enrolment?
A researcher-designed instrument was developed based on Tinto’s theoretical framework of attrition, as adapted for distance learning by David Kember. The instrument was designed to include variables that reflected each of the essential elements of Kember’s model.
Two pilot studies were conducted to obtain evidence of content validity and reliability for the instrument. CNEP faculty members and one former student reviewed the instrument to affirm content validity. Test-retest reliability was determined by administering the final version of this form to a second former student on two occasions, one week apart, and reaching perfect agreement in the responses that were provided for each of the elements of the instrument.
The population of students who had withdrawn, failed, or had been asked to leave the CNEP program from 1989 through October 1994 equalled 59 individuals (drop-outs). This entire population was selected for study. Data were retrieved from the CNEP Student Management System (SMS). A random sample of control participants was also selected using the SMS. Every third student name was selected from the chronological graduate data file. The final sample included 68 students (controls). Responses were received from 25 of the 59 drop-out sample and from 52 of the 68 control sample. Eight packets of study materials sent to drop-outs were returned for unknown addresses. Therefore, the response rates were calculated as 49% (drop-outs) and 76.4% (controls). These response rates were considered adequate for purposes of this study.
This study was reviewed and approved for distribution by the CNEP Research Review Committee in accord with the research policy of the sponsoring institution, The Frontier School of Midwifery and Family Nursing. Data were collected between January and April, 1995. Study materials included a letter of introduction, an assurance that anonymity would be protected, the study instrument, and a self-addressed, stamped envelope for return of study materials. Follow-up postcards were mailed to nonrespondents one month after the initial mailing in the effort to increase the response rate. Informed consent for participation in this study was assumed by voluntary completion and return of the study materials.
Data were abstracted and entered into the computer by a single individual and reviewed by a co-investigator for logic and accuracy. Data were analyzed using SPSS on a VAX mainframe and SPSS 6.1 for Windows on a personal computer. Frequency tables were generated for categorical variables, and differences between groups were tested for using Chi-square and Fisher’s Exact Tests. For ordinal variables, medians and other percentiles were computed, and differences between the two groups were tested using the Mann-Whitney U (nonparametric) tests. Independent sample two sided t-tests were computed for continuous variables. A forward stepwise logistic regression analysis, using demographic and academic variables, was performed to model the probability of dropping out of the CNEP program. The level of significance was set at 0.05 for all statistical tests.
The study groups were more alike than different on the major demographic factors that were assessed. There was a single male participant in the drop-out population, and he was also a respondent in the study. Data are presented in Table 1.
One notable difference between groups was in the age distribution of their children. Members of the drop-out group had more younger children (ages 1-5) and more adult children (age greater than 19), while members of the control children had more youngsters (ages 6-12) and adolescents.
Approximately two-thirds of study participants in each group were residents of urban areas. The suburban (15%), rural (10%), and frontier areas (4%) were, however, also approximately equally represented.
The drop-out sample was more representative of the southern geographic region of the U.S. The control group respondents contained almost twice the number of residents from the Midwestern region.
Attrition from the program was greatest (42.4%) among residents of the southern region. The northeast region (24%) was the next highest in attrition.
The groups were largely similar in total family income. Approximately one-fourth of study participants in each group had incomes greater than $75,000 U.S. prior to enrolment in the program. The family income during the period of CNEP enrolment did not differ greatly from levels noted at entry to the program.
A substantial number of individuals were working between 40 and 50 hours per week (56% of drop-outs and 34.6% of controls). A few members of each group were working more than 50 hours in each work week. Participants continued to work during their CNEP enrolment. However, twice the number of control group participants changed their work hours when compared to drop-outs. This difference was statistically significantly different (p
There was remarkable similarity between the two groups with respect to prior educational attainment. The majority held the baccalaureate degree in nursing. Approximately one-third of members in each group held a master’s degree.
The mean undergraduate grade point average was high overall (drop-outs = 3.44; controls = 3.49, p = .515, NS). The mean number of years between last formal education and entry to CNEP was greater for the control group (drop-outs = 5.72; controls = 6.25), but this difference was not significant (p = .615, NS).
All of the participants reported having maternal child health (MCH) nursing or midwifery experience prior to enrolment in CNEP. The majority in both groups reported that this experience included labour and delivery nursing. Other MCH nursing, public health, or lay midwifery experience accounted for a great proportion of the work experience other than labour and delivery nursing. A few members of each group reported working in the nurse-practitioner role.
One in five of the CNEP drop-outs and one half of the control group proceeded to complete an academic degree, several through partici-pation in the master’s degree academic option associated with the CNEP program. In addition four drop-outs completed another nurse-midwifery education program.
The majority of study participants remained in their current marital or partnered relationships during their CNEP years. When this status did change, it was more likely to occur at the time of enrolment. One in five in each group changed their place of residence. A very few (four drop-outs and two controls) were pregnant during the program.
Approximately one in three participants in each group reported that they had experienced a physical health challenge during their enrolment in the program. The majority of them, however, reported that they did not require medical treatment, follow-up, medication, surgery, or hospitalization. One in three respondents in each group reported that a member of their family had experienced a serious health problem that required hospitalization and/or intensive treatment. However, 56% of the drop-out group and 75% of the control group respondents indicated that they had experienced a psychological challenge. The individuals in the drop-out group responded significantly differently to this psychological challenge when compared to members of the control group. Fewer drop-outs reported coping by their own means (drop-outs = 34%; controls = 63.5%, p = .02). Drop-outs took more medications (drop-outs = 16%; controls = 7.7%). One person in the drop-out group required psychiatric hospitalization. One in five in each group reported that they had sought counselling.
Serious financial difficulties were reported by twice as many members of the drop-out group (48% vs. 25.5%). The drop-outs were also significantly far more likely to report that a member of their extended family experienced financial difficulty (drop-outs = 32%; controls = 5.8%; p
Members of both groups had family or social responsibilities in addition to their academic work. A few in each group provided elder care (drop-outs = 16%; controls = 15.4%). The majority of respondents had childcare responsibilities (drop-outs = 64%; controls = 76.9%). Approximately one third of members of each group were involved in professional organ-izational activities.
Individuals from both groups reported a broad variety of sources of social support. The majority of members acknowledged the support of their partner or spouse (drop-outs = 76%; controls = 82.7%). On the other hand, children were equally less supportive (drop-outs = 32%; controls = 40.4%). Other important contributions to the support network were offered by parents, friends, and co-workers. Some support was received for members of each group from other relatives, neighbours, and church members.
Loans and personal funds were the most often cited sources of support for respondents. Twice as many members of the drop-out group reported self-pay responsibilities (64% versus 27%). Employer-paid arrangements were cited by members of both groups and accounted for full support of some of these students.
The two groups approached course work very differently. Study participants were asked to describe their approach to CNEP coursework. Definitions of the response options were not provided; therefore, the option selected by the respondent represented a self-assessment. Successful students approached coursework more vigorously, studied more hours weekly, and were significantly more likely to join study groups or have a study partner. These data are presented in Table 2.
The groups were very similar in their level of computer literacy at the start of CNEP, which required participation in the school’s electronic bulletin board system (BBS). Approximately half of each group were new learners, and approximately equal proportions (1 in 3 in each group) were functional with word processing. Few in either group were functional with the use of communication software.
Two of every three members in each group reported that they did use the computer BBS. Members of the drop-out group reported earlier use of the system (prior to and at the first group orientation session); however, by the time the first course level had been completed (an average of 6 months into the program), the majority of users in each group were using the system. Nevertheless, drop-outs used the system far less frequently, citing a lack of understanding of how to use it as a major barrier. The mean number of times per month that an individual in the drop-out group might log on to the system was 4.28; this figure was 16.3 for members of the control group, with a range of 1 to 16 (drop-out) and 1 to 30 (control). The number of courses completed by the majority of members of the drop-out group ranged from one to six. Seven of the drop-outs had not completed even one course. Nevertheless, the majority of the members of the drop-out group believed that attainment of the nurse-midwifery certificate was a realistic goal. Only two members of the control group did not believe this goal to be realistic.
The great majority of the drop-outs (76%) indicated that they did not feel that they were a member of the school community compared to 28.8% of controls. The majority of the drop-outs provided a self-assessment of their personal academic performance as satisfactory or very satisfactory (72%). One in four drop-outs declined to provide this assessment. Members of the control group also rated their performance as satisfactory or very satisfactory (96.2%).
Participants were asked to provide three ratings that addressed the quality and quantity of their interactions with faculty. The first rating concerned the perception of the adequacy of this interaction. Members of the control group were more likely to rate the interaction as at least adequate (63.5%), whereas members of the drop-out group were more likely to rate the interaction as less than adequate (66.6%).
The second rating concerned the perceived quality of this interaction. Members of the control group were more likely to rate the quality of this interaction as at least satisfactory (73%), whereas members of the drop-out group were more likely to rate the quality of this interaction as less than satisfactory (50%).
The final rating addressed satisfaction with turn-around time for grading and feedback on learning activities and exams. Almost half of the members of both groups expressed dissatisfaction with the amount of time that was required to receive this feedback.
Members of the drop-out group were far more likely not to seek advice from any individual. When respondents did seek advice, members of the drop-out group were more likely to be less satisfied with the response that they received than members of the control group; however, the majority of respondents (over 50% in each group) were at least satisfied with the response.
Participants were asked to provide three ratings that addressed the impact of CNEP enrolment on their personal, work, and family life (Table 3). The majority of respondents in both groups stated that enrolment had a negative or very negative impact in all three areas.
Using a forward stepping logistic regression approach (Kleinbaum, 1994), none of the demographic variables were found to be predictive of dropping out. Three variables from among those describing academic habits did contribute significantly to a logistic regression model for predicting the odds of dropping out (p
Having a study buddy had the greatest effect on the predicted probability of dropping out, although it was second of the three variables to enter the equation (Table 4). When the other two variables were held constant, the odds of dropping out were nine times greater for a student who had no study buddy compared to the student who had a study partner. The odds of dropping out are reduced dramatically for a student who approaches the coursework “vigorously or compulsively” and greatly reduced for the student who sets aside more than 20 hours a week for CNEP studies. As depicted in Table 4, holding study buddy status and approach to studies fixed, the adjusted odds ratio of dropping out is .1169 (approximately 1 to 8) for a student who sets aside more than 20 hours per week for studies.
The sensitivity (the probability that someone predicted to be a drop-out actually did drop out) and specificity (the probability that someone predicted to complete the program actually completed it) of this prediction model are .88 and .87 respectively. The predictive values positive (the probability that a student predicted to drop out will in fact drop out) and negative (the probability that a student predicted to complete the program does in fact complete it) are .76 and .94 respectively. The predictive values, which take into account the prevalence of dropping out, are generally more important in determining the usefulness of a prediction model or test. Here, the prevalence was estimated using the proportion of dropouts in the sample. The predictive value negative was of more concern to the CNEP program because the objective was to minimize the probability of being in error when deciding that a student is not at risk for dropping out. As the prevalence increases, the predictive value negative decreases. Based on the sensitivity and specificity of this prediction model, even with a prevalence of .5 (or a 50% drop out rate) the predictive value negative will be .88, and if the prevalence was as low as .2, the predictive value negative would be .97.
Table 5 presents the barriers to distance learning in nurse-midwifery education that were cited by respondents. These barriers are presented in three ways. The total number of times that any single barrier was cited is depicted in descending order of citation. The number of times that any single barrier was cited by a member of either group is also noted. In addition, the number of times that any single barrier was ranked as the most important barrier is presented by group.
The barrier most often cited overall was family responsibilities. It was followed closely by work responsibilities and financial barriers. These barriers were cited almost twice as often as any other barrier. These rankings were similar when these data were reviewed by group. The drop-out group cited work, family, and financial barriers in that order. The controls cited family, financial, and work barriers in order.
Life events were ranked first more often by members of the drop-out group. The reality of starting over as a student/beginning practitioner and personality difficulties with clinical preceptors and/or faculty were cited more often by members of the control group.
Other factors cited by respondents included lack of student and faculty interaction, academic issues (grading, feedback times), academic challenges (strict time challenges, academic ability), and personal life events. Difficulties with clinical sites (location, volume) were cited by some members of the control group.
The findings of this study indicate that, despite remarkable similarity in personal characteristics and equal academic achievement at entry into the CNEP program, there were several important differences between the two study groups that contributed to academic success or lack of it. Age distribution of children differed; drops-outs had children of both younger and older ages. This finding could represent a difference between groups in child care responsibilities. While one group had to negotiate for the care of younger children, the other group had to address the various needs of school-age children and their activities.
Students in both groups reported middle or upper middle class income levels. However, the vast majority of respondents were contributing to that income by full-time employment and continued to do so during their enrolment. Working had adverse effects, particularly for drop-outs. Several significant life events occurred for students enrolled in the program. Contrary to what had been thought to be true of students, in fact, there were few who changed marital status, experienced a pregnancy, or had a serious physical illness. The majority of respondents in both groups did, however, experience psychological distress, some requiring counselling, medication, or intensive therapy. Those who successfully completed the academic program were also those who were more likely to find successful self-care coping mechanisms.
These demographic findings are similar to those reported in the literature. Studies of health professional students enrolled in both distance education and traditional academic settings (Siquera de Freitas & Lynch, 1986; Goodman, Blake, & Lott, 1990; Lazin & Neumann, 1991) indicate that demographic characteristics were less predictive of continuation in an educational program than was the degree of social support that was received during the program of studies.
The greatest differences that were identified from these data were related to the academic characteristics of the two respondent groups and the ways in which these groups related to the program and its faculty. Again, these findings are similar to literature reports that identify academic variables as the strongest predictors of academic success.
Members of the drop-out group were less aggressive in their study habits, less likely to use the resources of a study partner, less likely to allocate sufficient time for their studies, and less likely to use the modes of communication that were available. An elective or continuing education course could be developed to assist students to develop sound study habits. Enrolment in such a course could be included in the individual learning plan for students experiencing academic difficulties.
Nevertheless, students in both groups rated their personal academic performance as at least satisfactory, which, for members of the drop-out group, may have been less than insightful. Students indicated that it took too much time to receive feedback on their academic coursework. This feeling may have contributed to some of the discrepancy between self-perceived and actual performance and supports the premise presented by Sewart (1992) that students need immediate feedback from the program. Even though both groups were equally capable of using the computer at the time of CNEP enrolment, members of the drop-out group were far less likely to use it (including the BBS) as a learning and networking resource. Several barriers to the use of the BBS were cited by members of both groups, including a lack of understanding of how to use the technology. Introductory and continuing education courses on computer-related topics and a source of technical advisory assistance would seem to be important.
Students were dissatisfied with each of the three elements of student/ faculty interaction that were reviewed. They rated interactions as less than adequate in amount and quality, and, as previously noted, they were also less than satisfied with the turnaround time for grading and feedback on learning activities and exams. Drop-outs, in particular, clearly described themselves as not using the resources available (BBS, study partners, networking when on campus) and as not feeling a personal identification with the school. This finding supports the theories of Holmberg (1988) and Peters (1971), who both emphasize the importance of balancing self-learning with interactive activities. Shoemaker (1995) pointed out the importance of faculty who act as cultural brokers bridging the off-campus student with the school. Students are more likely to be successful if they feel a strong identification with the academic program and receive early and continuous academic counselling and support.
The feelings of distancing from program and faculty that were expressed by members of both groups but, in particular, by those who dropped out of the program could be addressed by increasing the amount and the quality of student to student and student to faculty interactions early in the program when the vast majority of attrition occurred. Community building activities would be particularly relevant to foster a sense of bonding with the school.
This study focused on the population of drop-outs and a randomly selected control group, sampled from a student population that was nationally distributed. The limitations of the study were the low response rate from the drop-outs (49%) and the almost all female respondents. Findings may not be applicable to male distance learners, who may face a different set of barriers. Nevertheless, the findings may have some applicability to other distance education programs utilizing telecommunications/computerized distributed learning with a geographically diverse student body, particularly female distance learners. This generalizeability increases the significance of the contribution of this study to the literature of distance education.
This study was designed to integrate what was previously known with what is being learned about barriers to distance education. Students enrolled in programs that use computer-assisted or computer-mediated technology accept a new challenge in addition to those identified for students enrolled in more traditional distance education programs. Results of this study confirm that distance education must be viewed as an integrated, not isolated, academic endeavour. Students enrolled in these programs should be strongly encouraged to set aside adequate time to dedicate to their studies and to make best use of the additional avenues of communication available to them to establish and maintain the academic and social networks that have been identified as essential to academic success in distance-learning. The recommendations derived from this study are highlighted in Appendix A.
Study Recommendations to Prevent Drop-out from Distance Education Programs
This research was partially supported by the Bureau of Primary Health Care, Rural Health Outreach Grant number CSD000153.
Katherine Carr, Ph.D., CNM, FACNM
902 17th Ave. East
Seattle, WA 98112-3924
Phone: (206) 323-8968
Fax:(206) 860-3930
Internet e-mail: Kcarr@mail.halcyon.com
Brindley, J. (1987). Attrition and completion in distance education: The student’s perspective. Unpublished master’s thesis, University of British Columbia, Vancouver, B.C.
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Lazin, R., & Neumann, L. (1991). Student characteristics as predictors of drop-out from medical school: Admissions to Beer-Sheva over a decade. Medical Education, 25, 396-404.
Peters, O. (1971). Theoretical aspects of correspondence in instruction. The changing world of correspondence study: International readings. University Park: Pennsylvania State University Press.
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Roberts, D. (1984). Ways and means of reducing early student drop-out rates. Distance Education, 5(1), 203-214.
Sewart, D. (1992). Student support systems in distance education. Paper presented at the 16th World Conference of the International Council for Distance Education, Bangkok, Thailand, November 8-13, 1992.
Shoemaker, D. (1995) The culture broker in post-RN education: A view from the distance. Nursing Outlook 1995, 43, 129-133.
Siqueira de Freitas, K., & Lynch, P. (1986). Factors affecting student success at the National Open University of Venezuela. Distance Education, 7(2), 191-200.
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Katherine Camacho Carr, PhD, CNM, FACNM received the master of science and certificate in nurse-midwifery from University of Illinois, Chicago and the PhD in nursing science from the University of Washington, Seattle. She currently serves as Director of Special Projects, Institute of Midwifery, Women & Health. She was formerly the Director of Development & Research for the Frontier School of Midwifery and Family Nursing, Community-Based Nurse-Midwifery Education Program.
Judith Fullerton, PhD, CNM, FACNM, received the master of science and certficate in nurse-midwifery from Columbia University, New York City, and the PhD in health education/administration from Temple University, Philadelphia, PA. She currently serves as Associate Dean for the Graduate Nursing Program, University of Texas Health Science Center, San Antonio.
Richard Severino, MS, received the BS in applied mathematics and the MS in statistics from San Diego State University, San Diego, CA. Mr. Severino is currently a research statistician at the Queen’s Medical Center, Honolulu, HI, and a member of the American College of Nurse-Midwives Certification Council Research Committee.
M. Kate McHugh, MSN, CNM, received the master of science and certificate in nurse-midwifery from St. Louis University and currently serves as the Director for the Institute of Midwifery, Women & Health. She was formerly the Program Director for the Frontier School of Midwifery and Family Nursing, Community-Based Nurse-Midwifery Education Program.
ISSN: 0830-0445