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Pursuing Doctoral Degree in the Computer-Mediated Asynchronous Learning Environment

Pursuing Doctoral Degree in the Computer-Mediated Asynchronous Learning Environment. Nataliya V. Ivankova, PhD University of Alabama-Birmingham Sheldon L. Stick, PhD University of Nebraska-Lincoln. Research Problem.

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Pursuing Doctoral Degree in the Computer-Mediated Asynchronous Learning Environment

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  1. Pursuing Doctoral Degree in the Computer-Mediated Asynchronous Learning Environment Nataliya V. Ivankova, PhD University of Alabama-Birmingham Sheldon L. Stick, PhD University of Nebraska-Lincoln

  2. Research Problem • High drop-out rate (45–50%) for students in conventional doctoral programs, much higher for those pursuing doctoral degrees via distance education; • Growing number of institutions offering graduate degrees via distributed means; • No research on doctoral student persistence in computer-mediated asynchronous learning (CMAL) environment.

  3. ELHE-DE Program • Educational Administration Distributed Doctoral Program in Educational Leadership in Higher Education (ELHE-DE) • Department of Educational Administration at the University Nebraska – Lincoln (UNL) • Asynchronous computer-mediated environment, using Lotus Notes and Blackboard platforms • Initiated in 1992 with first enrollees in 1994 • More than 350 students • More than 40 online courses

  4. Study Purpose • The purpose of the study was to understand what challenged matriculation of doctoral students’ pursuing degrees in the computer-mediated asynchronous learning environment. • In the first phase, the quantitative research questions addressed how selected internal and external variables to the ELHE-DE program serve as predictors to students’ persistence in the program. • In the second phase, four qualitative case studies explored the results from the statistical tests in detail.

  5. Theoretical Perspective • Three major theories of student persistence: • Tinto’s Student Integration Theory (1975) • Bean’s Student Attrition Model (1980) • Kember’s Model of Dropout from Distance Education Courses (1995)

  6. Research Design • Mixed methods sequential explanatory design (Creswell, 2002, 2003; Tashakkori & Teddlie, 1998); • Two phases: quantitative and qualitative; • Two types of data: quantitative and qualitative; • The data is connected or “mixed” at some stage/stages in the research process;

  7. Participants • Current and former doctoral students in the ELHE-DE program (N=278); • Students were referred to as distance, if they had taken half of their classes via distributed means; • Criteria for selecting the participants included: • being in ELHE-DE vs. other programs; • time period of 1994-Spring 2003; • must have taken ½ of course work via distributed means; • be either admitted, graduated, or withdrawn from the program; • must have taken at least one online course • in the program.

  8. Phase 1: Quantitative Data Collection • Cross-sectional web-based survey (April 1 – July 18, 2003); • Self-developed instrument (5 to 7-point Likert type scales); • 17-months in development, organized by factors, and piloted tested (N=13); • Convenience sampling (N=278); • Response rate: 74.5% (N=207): • Beginning group: 78 (84.8%) • Matriculated group: 78 (70.9%) • Graduated group: 26 (100%) • Withdrawn/Inactive group: 25 (50%)

  9. Variables • Dependent/grouping variable: student membership in one of 4 groups (labeled “student persistence”); • 10 composite predictor variables identified based on theory and qualitative thematic analysis study of 7 active ELHE-DE students (Spring 2002): • “online learning environment”, “program”, “online learning community”, “faculty”, “student support services”, “academic advisor”, “family and significant other”, “employment”, “finances”, “self-motivation”.

  10. Quantitative Data Analysis • Univariate analysis (scale items): • Descriptive statistics • Cross tabulation • Frequency counts • Multivariate analysis (10 composite variables): • Data screening • Discriminant function analysis • Reliability and validity of the instrument

  11. Quantitative Results • Demographic Information: • 71.4% between 36 and 54 years of age • 54.6% women • 92.8% employed full-time • 66.7% non-residents of Nebraska • 81.1% married with children

  12. Quantitative Results (cont.) • Scale Items Frequencies Analysis: • most participants were satisfied with their academic experiences in the program; • most participants received all the needed support from both the institution and external entities; • most participants were comfortable learning in the CMAL environment; • participants differently benefited from the virtual community; • participants had different experiences with academic advising; • most participants were highly motivated to earn the doctoral degree.

  13. Quantitative Results (cont.) • Discriminant function analysis: • 1 discriminant function: “ELHE-DE program” • 5 variables significantly contributed to the function discriminating 4 groups: • Program • Online learning environment • Faculty • Self-motivation • Student support services • Withdrawn/Inactive group differed from the other three groups the most; • Graduate group differed from both Beginning and Matriculated groups; • Matriculated group differed notably from Beginning group.

  14. Connecting Quantitative and Qualitative Data • Cases Selection: • two-stage selection procedure: • typical response for each group • maximal variation sampling • 3 females and 1 male were selected. • Interview Protocol Development: • 5 questions relate to 5 factors found statistically significant: • online learning environment • ELHE-DE program • faculty • student support services • self-motivation • 2 questions related to academic advisor and virtual learning community.

  15. Phase 2: Qualitative Data Collection • 4 cases (Gwen, Lorie, Larry, Susan) • Multiple case study design • Multiple data sources: • In-depth semi-structured telephone interviews • Follow-up email interviews • Academic transcripts and students’ files • Elicitation materials • Participants’ responses to the open-ended and multiple choice questions on the survey from Phase 1 • Researchers’ reflection notes • Archival Lotus Notes classes

  16. Qualitative Data Analysis • Within-case analysis: • open-coding and theme development • constructing a case study narrative composed of descriptions and themes; • Cross-case analysis: • Comparing themes and categories • Comparing text units (sentences) per theme and case • Verification Procedures

  17. Qualitative Results (cont.) • Within-case analysis: • 4 themes: • quality of academic experiences • online learning environment • support and assistance • self-motivation • Cross-case analysis: • same 4 themes • similar and different categories

  18. Qualitative Results: Themes by Cases • Cross-thematic analysis based on text units (sentences): • quality of academic experiences (n=494) (Gwen and Lorie); • support infrastructure (n=432) (Larry); • advantages and/or disadvantages of the CMAL environment (n=379) (Susan); • self-motivation (n=235) (Gwen, Lorie, Larry, Susan).

  19. Conclusions • Program should be scholarly, challenging, relevant, have high standards, and be learner-centered. • Learning in the CMAL format should match students’ learning style preferences. • Instructors must be facilitators of learning and be actively involved with online courses.

  20. Conclusions (cont.) • Institutional DE student support infrastructure should be in place to assist distance learners. • Student motivation is extremely important for students who pursue their doctorate degrees via DE. • Academic advisor plays a lesser role in students’ matriculation in the CMAL environment. • The existence or absence of online learning community did not significantly affect students’ persistence.

  21. Delimitations and Limitations • confined to only one graduate program; • provided only one perspective on persistence; • used convenience sampling; • 100% response rate from Graduated group; • not all students withdrawn from the ELHE-DE program could be located; • limited generalizability of discriminant function analysis results; • different interpretations by different readers; • possible researcher’s bias in the analysis of the qualitative findings.

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