THE NATIONAL NURSING shortage makes attrition ATTRITION OF ON-LINE GRADUATE NURSING STUDENTS BEFORE AND AFTER PROGRAM STRUCTURAL CHANGES

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1 ATTRITION OF ON-LINE GRADUATE NURSING STUDENTS BEFORE AND AFTER PROGRAM STRUCTURAL CHANGES JAN RICE, PHD, RN, WILAIPORN ROJJANASRIRAT, PHD, RN, AND PAT TRACHSEL, PHD, RN This study assessed attrition rates and reasons for withdrawal among on-line graduate students before and after the implementation of program structural changes in A descriptive retrospective cohort study was conducted using the academic and advising records of 853 online graduate nursing students enrolled between 2005 and Three student cohorts were examined: (Cohort 1) students who entered and withdrew prior to 2008, (Cohort 2) students who entered before and withdrew after 2008, and (Cohort 3) students who entered and withdrew after The proportions of student attrition from each cohort were 43% (97 out of 225 students), 19% (52 out of 277 students), and 7.4% (26 out of 351 students), respectively. Results indicated that students' attrition rates in Cohorts 2 and 3 were significantly less than Cohort 1. Supported by Alexander Astin's input experience output model, 2 major themes emerged as reasons for withdrawal personal and academic. Findings from this study provided a critical view for further investigation and serve as an evaluation tool to identify trends and develop appropriate supportive interventions that facilitate positive student outcomes. Further research is warranted to investigate the effects of the program structural changes on students' attitudes and program satisfaction. (Index words: On-line; Graduate; Nursing; Attrition) J Prof Nurs 29: , Elsevier Inc. All rights reserved. THE NATIONAL NURSING shortage makes attrition a major concern for nurse educators and administrators of nursing programs (Fowler & Norrie, 2009). Although student attrition is one of the most important challenges of financial, educational, and workforce development for the health care fields, attrition data serve as only one measure of the quality and effectiveness of an academic program. Professional nursing accrediting bodies such as the National League for Nursing and the Commission on Collegiate Nursing Education require Associate Professor and Associate Dean of Graduate Program, Graceland University School of Nursing, Independence, MO. Associate Professor and Director of Research and Scholarship, Graceland University School of Nursing, Independence, MO. Professor, Graceland University School of Nursing, Independence, MO. Address correspondence to Dr. Rice: Graceland University School of Nursing, 1401 West Truman Road, Independence, MO jarice@graceland.edu /12/$ - see front matter reporting of degree completion rates and program satisfaction as indicators of program success. It is widely believed that student satisfaction with the nursing program and attrition rates are directly related. Systematic analysis of attrition data can provide valuable information to support a program's continuous quality improvement efforts. Student attrition rates and reasons for withdrawal have been reported for traditional onground undergraduate nursing programs. However, there is a paucity of data available related to attrition from online graduate nursing programs. This study was an attempt to report the change in attrition rates before and after the implementation of program structural changes in a private higher education institution. Program structural changes implemented in 2008 were specifically directed at influencing variables within the academic environment. Specifically, program changes were designed to (a) provide opportunities for integration into the academic environment; (b) provide access to the relationships, skills, and resources needed for student success in the program; (c) structure course Journal of Professional Nursing, Vol 29, No. 3 (May/June), 2013: pp Elsevier Inc. All rights reserved.

2 182 RICE ET AL delivery to enhance student engagement and support optimal learning in the on-line environment and; finally, (d) enhance student commitment to program completion. The primary goal of these changes was to impact the student's academic experience in ways to support a more positive outcome evidenced by both a decreased attrition rate and a decrease in academic reasons for withdrawal. The structural and process program changes implemented in January 2008 included the following: (a) a transition from monthly rolling enrollments to cohort admission three times a year, (b) a 3-day on-campus orientation program for new master of science in nursing (MSN) students focusing on skills and resources to support student success, (c) an expansion of 8-week session course offerings to 16-week trimester course offerings, and (d) the development of three program completion contract options that were discussed and signed by students at the new student orientation session. A variety of terms are found in the literature to describe students who leave a program of study prior to completion. Perry, Boman, Care, Edwards, and Park (2008) stated that although numerous studies have focused on persistence rates from various perspectives, there is a lack of clarity on terms and concepts and their relation to on-line educational practices. For the purposes of this study, the term attrition referred to students who had withdrawn from the on-line graduate nursing program after being formally accepted and actively enrolled in their first course. Program withdrawals are categorized as administrative withdrawal (failure to start or maintain active enrollment), academic withdrawal (dismissal because of two course failures), or studentinitiated withdrawal (students who leave for reasons unrelated to administrative or academic requirements). Background The growth of on-line graduate programs is unprecedented (Allen & Seaman, 2008). These programs offer the student greater convenience, flexibility, and the opportunity to complete clinical requirements in their own communities. Most graduate students have both professional and family responsibilities, and the on-line environment provides a viable option for completing a degree. Because of these benefits, on-line programs and institutions have realized increased enrollments and program inventories. Yet, the issue of low persistence/ high attrition rates raises concern for on-line graduate programs. National statistics are not available, but dropout rates ranging from 20 50% have been reported by The Chronicle for Higher Education (Frankola, 2001). The on-line student has different characteristics and needs than that of the traditional student. In addition, the on-line learning environment is considerably different than the on-campus setting. Recent studies of persistence and attrition rates continue to provide valuable information for higher education programs about why students choose to stay or leave a program of study. Rovai (2003) noted, however, that although many studies have focused on traditional on-campus programs, there is a dearth of literature concerning issues at the graduate level and issues of the on-line learner. In addition, there is a need to evaluate the effects of program design and processes intended to promote faculty student and student student interactions (Lovitts, 1996). Limited research related to the attrition or persistence of on-line graduate students was found. Multiple variables including demographic, academic, administrative, and personal have been examined in relation to student attrition rates. Overall, research results indicated that students were more likely to drop out early in a program (Willging & Johnson, 2004) and that students' reasons for leaving were multivariate and unique (Li & Killian, 1999; Willging & Johnson, 2004; Glogowska, Young, & Lockyer, 2007). Reasons for withdrawal were primarily categorized either as program related or as personal related. Program-related reasons included issues related to program administration and management such as student support services, available resources, instructional strategies, content delivery format, curriculum, and so forth. Personal reasons most often included issues related to family, health, financial status, commitment to academic pursuits, and career/work expectations (Perry et al., 2008; Rovai, 2003). Demographics were not predictive of attrition, and no evidence of students withdrawing related to lack of social integration or sense of learning community was found (Rovai, 2003). Willging and Johnson (2004) conducted an on-line survey to determine when and why students dropped out of an on-line program. Various factors were identified and compared between students who dropped out of an on-line program and those who persisted. Data revealed that most of the students dropped out after completing only a few courses, often because of frustration or inexperience with technology. Students who have completed several courses were less likely to drop out because of the time and effort invested in the program. In summary, there is a dearth of research available related to student attrition from on-line graduate nursing programs. Results have shown that demographic variables were not predictive of attrition and that reasons for leaving are multivariate and unique. Insights from available research provide a limited but critical view of the complex issues surrounding graduate student attrition and a better understanding of the on-line learning experience. Integration of information regarding students' reasons for leaving and the impact of changes in program structures and/or processes provide opportunities for further research, program improvement, and decreased rates of attrition. Theoretical Framework Alexander Astin (1984) outlined a rather precise input environment output (I-E-O) model for analyzing student data. The I refers to inputs (personal qualities students bring to the university experience), the E refers to the university environment (the student's actual campus experience), and the O refers to outputs (change or impact on the student talent development

3 ATTRITION OF ON-LINE GRADUATE NURSING STUDENTS 183 during the college experience). It is hypothesized that the relationship between student inputs and college environment occurs because students often choose their college environment based on certain student characteristics. For example, a highly prepared student with an excellent high school grade point average (GPA) and standardized test scores will often choose or be chosen by a more selective institution. Relationships between the college environment and student outcomes have reflected the impact of certain environmental structures and teaching practices on final student outcomes. Astin's I-E-O model has been modified to include intermediate outcomes that represent occurrences and participation in activities that the student has some control over, yet which occur following the initial exposure to the college environment. Intermediate outcomes may be considered environments or outcomes depending upon the research question being posed. The purpose of this study was to evaluate attrition rates and reasons for withdrawal among three cohorts of on-line graduate students before and after the implementation of program structural changes. Astin's model was utilized to provide a framework for understanding reasons for student-initiated withdrawals. Three research questions were addressed: (a) What are the differences in student attrition rates before and after implementation of on-line program changes?; (b) What are the reasons given for withdrawing from the on-line graduate program?; and (c) What are the differences in reasons for student withdrawal before and after program changes? Methods Human subject protection approval for this project was acquired through the university institutional review board (IRB). All data were de-identified, and students' names were removed from data files. All identifying information was handled strictly according to IRB policies and the Family Educational Rights and Privacy Act guidelines. Research Design A descriptive comparative study was conducted using student academic and advising records from the online graduate nursing program of a private midwestern university. Sample The sample consisted of academic and advising records of 853 students actively enrolled in the MSN program between January 2005 and December Registration records with available information on student program progression were included in the study. Data Collection Quantitative data were extracted from the university student academic and advising records. Academic records included documentation of student demographics and progression. Advising records included documentation of all communications between on-line students and program consultants. Program consultants are part of student support services and assist students with registration, enrollment, and withdrawal procedures. The records of students enrolled between January 2005 and December 2010 were examined. Three cohorts of students were compared: (Cohort 1) students who entered the program and withdrew before the program changed in January 2008, (Cohort 2) students who entered the program before and withdrew after the program changed in 2008, and (Cohort 3) students who entered the program after and withdrew after the program changed in Text-based data from the advising records of students who initiated withdrawal were used for content analysis. Selected data for analysis included academic and nonacademic variables. The nonacademic variables included demographic information such as age, gender, educational background, ethnicity, marital status, number of dependents, employment status, and residence (rural, suburban, or urban). Academic variables included the attrition variable, program completion status, specialty track chosen upon admission (family nurse practitioner [FNP], nurse educator, and nurse administrator), part-time or full-time student status, and length of stay in the nursing program. Qualitative data were obtained from the narrative notes and messages documenting communication between the student and an assigned program consultant. Approximately 246 documents from students who voluntarily withdrew from the on-line graduate nursing program were examined to identify information related to reasons for withdrawal. The length of the documents varied from a few sentences to several paragraphs. The qualitative data from the progression records were entered into an Excel spreadsheet for content analysis by the investigators. Data Analysis Quantitative and qualitative approaches were used to address three study research questions. Data were examined for missing data and outliers and were cleaned prior to the actual data analysis. Demographic data were analyzed using descriptive statistics such as frequencies and percentages. Differences in attrition rates among three cohorts were analyzed using a chi-square test. The level of significance of.05 was set for all statistical testing in this study. Qualitative data were extracted from the advising records. The content of this text-based data was analyzed using qualitative data analysis. Content analysis is a data reduction technique that involves examining the data for recurring patterns or themes defined as the classification of units of text into categories (Patton, 2002). Three investigators performed content analysis using a rigorous qualitative research process. Initially, all investigators read the narrative notes to acquire an overall sense of the descriptions. Data were then coded and sorted using category schemes. Emerging categories and themes were

4 184 RICE ET AL labeled and discussed among the investigators until consensus was reached to ensure credibility, consistency, and inclusiveness of the findings. This process included identification of possible relationships between themes and variations within themes and inspection of the findings for coherence (Patton, 2002). Procedures to ensure the trustworthiness of study findings used four criteria from Lincoln and Guba (1985): (a) credibility data saturation and triangulation of data and methods, (2) dependability coding checks within the research team for consistency, (3) confirmability reflexivity of the field notes and raw data, and (4) transferability detailing of data collection procedures and contexts. Results Quantitative Findings The sample was predominantly female (87%), Caucasian (71%), and married (43%). The mean age of the graduate students was 42 years (SD = 11). Seventy-two percent of the students were enrolled in the FNP program (Table 1). Of the 853 students, 175 withdrew from the program sometime between the 2005 spring semester and the end of the 2010 fall semester an overall attrition rate of 20.5% during the 6-year period. The mean students' length of stay in the on-line nursing program for students in the first, second, and third cohorts were 2.2, 3.1, and 1.4 years, respectively. The mean students' length of stay in the on-line nursing program was significantly shorter in Cohort 3 compared with Cohorts 1 and 2, F(2, 172) = 7.38, P =.001. Of the 175 students who withdrew, 104 withdrew that were related to academic reasons, and 71 withdrew that were related to personal reasons (Table 2). Table 3 illustrates that student withdrawals by cohort from 2005 to 2010 were 43% (97 out of 225 students), 19% (52 out of 277 students), and 7.4% (26 out of 351 students), respectively. Results of the chi-square test indicated that the attrition rate declined significantly in the second and third cohorts, χ 2 (2, N = 853) = , P b.00. Table 1. Sample Characteristics (N = 853) Demographics Frequency % Mean age = 42 (SD = 11) Female Male Married Single Caucasian Black 35 4 Asian 21 4 Nursing program tracks: FNP, FNPC 32 4 NE 11 1 HCAM Not specified Note. Some variables may not add up to 100% because of missing data. FNPC = family practitioner nurse certificate; NE = nurse educator; HCAM = Health Care Administration and Management. Qualitative Findings Two major themes related to program withdrawal emerged from the content analysis of academic and advising records personal reasons and academic reasons. Using Astin's I-E-O model, we defined personal reasons as factors related to personal qualities and/or circumstances (inputs), and academic reasons were defined as factors related to the structures or processes of the learning experience (environment). Subcategories of personal reasons for withdrawal included lack of time, motivation or commitment, family issues, financial problems, career choice, and other. Subcategories of academicrelated reasons for withdrawal from the program included learning preferences, program format, technology issues, process and/or procedural issues, academic performance, support, resources, and communication. Personal reasons noted for withdrawal included family illnesses, personal struggles such as divorce, and the lack of time to devote to studies. Examples of communications from students noting personal reasons for withdrawal included the following: My situation with my child who is ill is not improving, and as hard as this is for me, I will not be able to continue in the N.P. Program. My commitments to my family and work take priority. I lack the time it takes to commit to the Program and, I can't keep my GPA up. Due to unforeseen personal problems I will not be able to continue the Program [sic]. I deeply regret this decision...but, will not be able to devote the time and concentration necessary to complete this Program. This decision (to withdraw) comes after much consternation. I cannot devote the time necessary to be successful at this point. I cannot in good faith continue as my GPA has faulted, my motivation is low and I know my dedication isn't sufficient. Financial challenges were a frequently cited reason for withdrawal and were usually noted in combination with other personal reasons as illustrated in the following communications from students: I have not worked on completing the paperwork for the Spring[sic] practicum as I was not sure if I would be enrolling for classes in the Spring. Due to personal and financial reasons, I will not be enrolling in classes this Spring. I will have to wait to take the next class. I do not have the money right now to continue. I definitely want to continue in this Program [sic]. Academic reasons noted for withdrawal were most commonly related to learning preferences, program

5 ATTRITION OF ON-LINE GRADUATE NURSING STUDENTS 185 Table 2. Types of Withdrawal by Cohort Students retained Frequency (%) of withdrawals Cohort in the program Personal-related withdrawal Academic-related withdrawal Cohort (56.5%) 20 (9) 77 (34.5) Cohort (81.2%) 27 (9.7) 25 (9) Cohort (92.6%) 24 (6.8) 2 (0.6) Note. χ 2 (4, N = 853) = 156.4, P b.001. format, process and/or procedural issues, support, resources, and communication. Examples of communications from students noting academic environment reasons for withdrawal included the following: Online learning is not my style, and I plan to transfer to a different institution. I appreciate the semester I spent at the university, but I know that distant [sic] learning is not for me. Some students made comments related to the program format of an 8-week course and program requirement for the clinical practice. The 8 week structure is too rigorous for me, and I need to withdraw. I have had a problem with setting up contracts for my practicum, so I am not going to be able to enroll for this semester. On-line learning environmental factors including lack of social interaction and communications between students and instructor or support staff were also noted as reasons for leaving the program. I have felt a lack of support and communication from the instructor. I ed my Program Counselor but did not get a response to communication from her. Many students withdrew from the program without providing a reason. Records indicated that program consultants contacted students who requested via to be withdrawn from the program. However, the consultants did not always receive a response to their s or to the telephone calls. For example, one student who reported to her program consultant that life has been rough did not enroll in classes the following semester and did not respond to the consultant's messages. Discussion Astin's (1984) I-E-O model provided a concise framework for examining student variables that impact attrition that correlates to the outcome variable in the model. The two major themes of personal and academicrelated reasons for student withdrawal that emerged from this study are consistent with the variables identified in the model. Personal reasons for withdrawal correlated to the inputs variable, which is described as personal circumstances and characteristics that students bring to the university experience. Academic reasons for withdrawal correlated to the environment variable, which is described as the student's actual academic experience. Variables related to concepts in the Astin model were represented in the findings of this study. However, testing the relationship among variables in Astin's model was beyond the scope of the study. Findings indicated attrition rates for each cohort, and most importantly, the student attrition rates significantly decreased in Cohorts 2 and 3 following the implementation of program structural changes in 2008 (Table 3). In addition, major themes for why students chose to withdraw from the on-line graduate program were related to academic and personal reasons. These findings supported the findings of previous studies that identified variables related to why students withdraw (Perry et al., 2008; Willging & Johnson, 2004) and the variable identified in Astin's I-E-O model. Withdrawals because of personal reasons remained fairly consistent in all three cohorts. However, withdrawals because of academic reasons significantly decreased in Cohorts 2 and 3 (Table 2). In addition, academic reasons were more frequently cited as the reason for withdrawal in Cohort 1, whereas personal reasons were more frequently cited as the reason for withdrawal in Cohorts 2 and3. Students and institutions have little control over external factors and personal Table 3. Student Attrition Rates Cohort Total no. of students Withdrawal P Cohort 1 Entered program and withdrew before (43%) b.001 Cohort 2 Entered program before and withdrew after (19%) b.001 Cohort 3 Entered program and withdrew after (7.4%) b.001 **χ 2 (2, N = 853) = , P b.001.

6 186 RICE ET AL circumstances that impact attrition. It is acknowledged that changes in attrition rates before and after the program changes may have been caused by variables that could not be adequately controlled for, including changes in the economy and the labor market, and the transition toward the doctor of nursing practice as the entry level for advanced practice roles. While a correlation cannot be made between the decreased attrition rates and the program changes, data suggest that the significant decrease in academic-related reasons for withdrawal may have been influenced by the program changes directed at altering the academic environment. Implications This study confirms previous findings that the decision to withdraw from an on-line graduate program is a complex and multivariate phenomenon. Identification of predictors of success or for students at risk of withdrawal continues to be elusive. The lack of available data on attrition from on-line graduate programs makes it difficult to draw conclusions about data from individual programs. Each program is unique in its design and serves a unique student population. In addition, it is recognized that reasons given by students for leaving a program may not be accurate but may be masked by a need to save face and blame external factors beyond their control as reason for withdrawal. Further research investigating perceptions of program consultants and faculty for why students leave might provide some new insights. Looking at why students stay instead of why they leave may also provide a more accurate picture of the academic environment. Although the findings show the drastic decrease of the attrition rate from 43% to 7.3% in our on-line graduate nursing program, we were unable to specifically identify the effectiveness of specific components of the program structural changes on the attrition rate. It is recommended that future study focuses on the collection and analysis of data to measure program effectiveness, such as students' characteristics, learning styles, computer skills and experiences, learning resources, student satisfaction, and so forth. Further exploration of student's perceptions and actual feedback from each of the three cohorts would clarify important aspects that might have influenced their decision to leave the nursing program. Focus groups or individual telephone interviews should be used in future studies to gather more complete data to determine the effects of program structural changes. Further exploration of possible program changes should include these questions: What can we offer those on-line students who have personal or family problems? What are possible counseling services or other available on-line resources that students can reach before getting to the point of withdrawing? What are the possibilities of using a screening tool or preadmission interviews to raise the awareness of student learning styles and preferences? What strategies might students employ to balance the demands of on-line graduate study with lifestyle, family responsibilities, and work requirements? What are the financial expectations during the program, and what resources and options are available for graduate students at the university? Continued evaluation of program structures related to students' needs may benefit both the student and the institution. Conclusion Findings from this study provided a critical view for further investigation and serve as an evaluation tool to develop appropriate supportive interventions to facilitate students' learning outcomes and positive classroom experience. It is hoped that this study might serve as a model for future studies. In addition, findings from this study contributed additional information to the limited literature about attrition rates in graduate on-line programs. References Allen, I. E., & Seaman, J. (2008). Staying the course: Online education in the United States, Babson survey research group, the Sloan consortium. Retrieved February 2, 2010, from course-2.pdf. Astin, A. W. (1984). Student involvement: A developmental theory for higher education. Journal of College Student Personnel, 25, Fowler, J., & Norrie, P. (2009). Development of an attrition risk prediction tool. British Journal of Nursing, 18, Frankola, K. (2001). Why online learners drop. Workforce, 10, Glogowska, M., Young, P., & Lockyer, L. (2007). Should I stay or should I go? A study of factors influencing students' decisions on early leaving. Active Learning in Higher Education, 8, Li, G., & Killian, T. (1999). An examination of their characteristics and reasons for leaving. Students who left college: AIR Forum Papers (ERIC ED ). Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Beverly Hills, CA: Sage Publications, Inc. Lovitts, B. E. (1996). Who is responsible for graduate student attrition The individual or the institution? Toward an explanation of the high and persistent rate of attrition. Paper presented at the Annual Meeting of the American Education Research Association. New York, NT. Patton, M. Q. (2002). Qualitative evaluation and research methods (3rd ed.). ThousandOaks, CA: Sage Publications, Inc. Perry, B., Boman, J., Care, W. D., Edwards, M., & Park, C. (2008). What do students withdraw from online graduate nursing and health studies education? The Journal of EducatorsOnline, 5, Rovai, A. P. (2003). In search of higher persistence rates in distance education online programs. Internet and Higher Education, 6, Willging, P. A., & Johnson, S. C. (2004). Factors that influence students' decisions to drop out of online courses. Journal of Asynchronous Learning Networks, 8. Retrieved February 2, 2010, from jaln/v8n4/v8n4_willging.asp.