1. THE IMPACT OF STUDENT PROGRESS FACTORS ON STUDENT PERSISTENCE IN E-LEARNING Anna H. Lint TUI University (Trident University International) February 03, 2011 2/03/2011

2. 2 AGENDA Abstract Introduction Problem Statement & Research Questions Literature Review Research Methodology Data Analysis & Presentation of Results Discussion & Implications of the Research 2/03/2010

3. 3 ABSTRACT The Purpose of the study : To evaluate and test the theoretical underpinnings of the Kember’s (1995) student progress model that examines the direct or indirect effects of student persistence in e- learning. Research Methodology * Sample population: 169 students at HCC * Instrument: DESP & SOAP / * Analysis: Logistic & Multiple Regression Findings & Limitations * Significance: external attribution (Q13, AdQ13 /w CVs: Q13, AdQ13, Q14), academic incompatibility (Q13) academic integration (Q14); GPA (partial mediation effect) * Limitations: local cc, individual perception 2/03/2011

4. 4 INTRODUCTION The knowledge gap Student attrition theories: Spady (1971) Tinto (1975) Bean & Metzner (1985) Kember (1989) Kember (1995) Kember’s (1995) student progress model predates the proliferation of online courses that occurred after the mid 1990s. Whether the Kember model fits with the current e-learning in a community college. The significance of the study Student persistence is a critical issue in e-learning Relationships among student perceptions, learning styles, and student persistence Application of Kember’s 1995 model to e-learning retention Future use for increasing student persistence. 2/03/2011

5. 5 PROBLEM STATEMENT Dropout: 20 to 50 % of online students Online retention rate: 10 to 20 % lower than traditional class settings Kember (1995) student progress model Developed for distance education which was the early stage of internet e-learning environment Lack of the association of student performance, cost-benefit analysis, and student persistence Measuring college student retention is complicated, confusing, and context dependent Evaluate direct or indirect effect among variables concerning student persistence (Student progress factors, learning styles, student persistence) Mixed results of Kember model 2/03/2011

6. 6 RESEARCH QUESTIONS 1. Is there a statistically significant relationship between student perceptions of the academic experience (a) social integration, (b) academic integration, (c) external attribution, and (d) academic incompatibility with student persistence (within the online learning environment at the community college level)? Does the relationship statistically significantly vary with respect to student characteristics and learning style? 2. Is there a statistically significant relationship between student perceptions of the academic experience (a) social integration, (b) academic integration, (c) external attribution, and (d) academic incompatibility with student persistence mediated by student performance (GPA)? 3. Is there a statistically significant relationship between student perceptions of the academic experience (a) social integration, (b) academic integration, (c) external attribution, and (d) academic incompatibility with student persistence mediated by cost-benefits? 2/03/2011

7. 7 LITERATURE REVIEW Persistence in E-learning The relationship among the components of Kember’s model: social and academic integration, external attribution, and academic incompatibility and their influence on persistence The contributions of student characteristics and learning styles to persistence The relationship between GPA and persistence Student cost-benefit analysis with persistence 2/03/2011

8. 8 THEORETICAL ORIENTATION & CONCEPTUAL FRAME WORK Figure 1. A model of student progress (Kember, 1995, p. 55) 2/03/2011 Permission granted by Copyright Clearance Center, 03/13/2010 social integration entry characteristics external attribution academic incompatibility academic integration GPA outcome cost/ benefit

9. 9 THEORETICAL ORIENTATION & CONCEPTUAL FRAME WORK (Cont.) Figure 2. Conceptual Framework 2/03/2011 DV Persistence IVs (Student Perceptions) Social integration Academic integration External Attribution Academic incompatibility Performance (GPA) Cost-Benefit CVs Characteristics (Age, Gender, Delivery mode, Major, Work environment, Marital status, E-learning experience) Learning Styles (VARK)

10. 10 RESEARCH METHODOLOGY Research Design Post-positivist worldview: reflects the need to identify and assess the causes that influence outcomes Quantitative research using survey/ sample population/ data collection and analysis Sampling and Population Population: 169 community college students (out of a sample of 800), Maryland : 21.1% return rate Sample size: minimum 97, α =.05 with a medium ES (f 2=.15), power (.80) 2/03/2011

11. 11 RESEARCH METHODOLOGY (Cont.) Data Collection Upon the IRB approval, web based cross-sectional survey with target students of summer 2010 at a community college, MD Data log, removal of error data, exporting to Excel Filtering data against research questions, importing data to SPSS 16.0 Instrumentation Section I: Student Characteristics Section II: Student Performance, Cost-Benefit analysis, and Student Persistence Student Online Academic Persistence (SOAP) inventory (cost-benefit & intent to persist: reliability of.84 &.68) Section III: Student Perceptions Distance Education Student Progress (DESP) inventory (reliability of social integration: 0.69, external attribution: 0.77, academic integration: 0.80, and academic incompatibility: 0.76) 2/03/2011

12. 12 RESEARCH METHODOLOGY (Cont.) Statistical Analysis Table 1: Research questions, Variables, and Statistical Analysis 2/03/2011 Research Questions IVs/CVs/MVs DV Statistics 1.Is there a statistically Student Perceptions Student Descriptive significant relationship (social integration, Persistence statistics between student perceptions academic integration, (items 13, of the academic experience external attribution, 14 & 16/ Logistic (a)social integration academic categorical regression (b)academic integration incompatibility) & continuous (c)external attribution, and data) Multiple (d)academic incompatibility Covariant: regression with student persistence Characteristics (within the online learning (age, gender, environment at the community delivery mode, college level?) Does the major, work relationship statistically environment. significantly vary with marital status respect to student e-learning experience) characteristics and Learning Styles learning style? (VARK)

13. 13 RESEARCH METHODOLOGY (Cont.) Table 1. (Continued) 2/03/2011 2.Is there a statistically Student Perceptions Student Descriptive significant relationship (social integration, Persistence statistics between student perceptions academic integration, (items 13, of the academic experience external attribution, 14 & 16/ Logistic (a)social integration academic categorical regression (b)academic integration incompatibility) & continuous (c)external attribution, and data) Multiple (d)academic incompatibility Mediator: regression with student persistence Student mediated by student Performance performance (GPA)? (measured by GPA)

14. 14 RESEARCH METHODOLOGY (Cont.) Table 1. (Continued) 2/03/2011 3.Is there a statistically Student Perceptions Student Descriptive significant relationship (social integration, Persistence statistics between student perceptions academic integration, (items 13, of the academic experience external attribution, 14 & 16/ Logistic (a)social integration academic categorical regression (b)academic integration incompatibility) & continuous (c)external attribution, and data) Multiple (d)academic incompatibility Mediator: regression with student persistence Cost-benefits mediated by cost-benefits?

15. 15 DATA ANALYSIS & PRESENTATION OF RESULTS Descriptive Statistics : Sample: 169 students out of 800 (21.1% return rate), survey: 3 times Student Characteristics Gender (F: 78.4%); Age (Over 23: 54.7%); Marital (S: 66.0%); Delivery Mode (O: 75.3%); Major: (S: 58.2%); Online Experience (Y: 56.2%); Work Environment (Static location: 84.4%) Learning Style: V (42.6%); A (11.7%); R/W (30.2%); K (15.4%) GPA (M=3.0418, SD=.84562); Cost-benefits (M=3.0281, SD=.73098) Student Persistence (Q13, Ad.Q13, & Q14) by Student Perceptions Table 2. Mean scores of student persistence by student perceptions 2/03/2011 Q13 AdQ13 Q14 Social Int. 3.38 (SD:.061) 3.28 (SD:.063) 3.29 (SD:.109) Academic Int. 3.46 (SD:.045) 3.38 (SD:.047) 3.36 (SD:.090) External Att. 2.66 (SD:.051) 2.70 (SD:.052) 2.80 (SD:.094) Academic Inc. 2.95 (SD:.043) 2.94 (SD:.048) 2.95 (SD:.093)

16. 16 DATA ANALYSIS & PRESENTATION OF RESULTS (Cont.) Bivariate Analysis Table 3. Correlation between Ivs, CVs, & MVs and Student Percistence (Q13, AdQ13, & Q14) Note. *p<.05, **p<.01. Spearman correlation was used for dichotomous variables. Pearson correlation was used for continuous variables. 2/03/2011 Q13 AdQ13 Q14 Social Int..168.012 -.201* Academic Int..276**.150.273** External Att. -.290* -.216* -.248** GPA.197*.236*.248** Cost-benefits -.036 -.078*.003 Age -.175* -.075 -.132 On-experience.219**.159.236**

17. 17 DATA ANALYSIS & PRESENTATION OF RESULTS (Cont.) Multivariate Analyses of Student Persistence 1. Research Question I Table 4. Regression Analysis Predicting the Variance of Student Perception, Student characteristics, and Student Persistence Note. OR was used for the probability of Q13 & AdQ13. β was used for the probability of Q14. *p<.05, **p<.01. 2/03/2011 No control Control by CV Q13 / AdQ13 / Q14 (β) Q13 / AdQ13 / Q14 (β) Academic Int..269* External Att..159**.213*.149*.135* -.768* Academic Inc. 3.796* Marital 13.124* On-experience 3.050* 3.472*.623* LS Auditory 15.196*

18. 18 DATA ANALYSIS & PRESENTATION OF RESULTS (Cont.) 2. Research Question II Baron and Kenny (1986) four steps for mediation: IV+DV(1) - IV+MV(2) - IV+MV+DV (3&4) Sobel test for checking the complete mediation. Partial mediation effect of GPA to the relationship between S. Perceptions & S. Persistence Table 5. Regression Analyses for Student Perceptions and Student Persistence Mediated by GPA Note. Logistic regression was used for Q13 & AdQ13. Multiple regression analysis was used for Q14. 3. Research Question III No mediation effect of Cost-benefits to the relationship between S. Perceptions & S. Persistence 2/03/2011 No Mediation Mediated by GPA Q13 / AdQ13 / Q14 Q13 / AdQ13 / Q14 Academic Int..895*.720* External Att. -1.837** -1.545* -1.930** -1.884** Academic Inc. 1.334* 1.406* GPA.744**.871**.385**

19. 19 DISCUSSION & IMPLICATIONS OF THE RESEARCH Study Findings External attribution had a significant relationship with Q13 & AdQ13. External attribution had a significant relationship with Q13, AdQ13, &Q14 controlling with CVs. Academic incompatibly had a significant relationship with Q13. Academic integration had a significant relationship with Q14. Prior online experience had a significant relationship with Q13 & Q14. Single & Auditory learners had a significant relationship with AdQ13. A partial mediate effect of GPA and no mediate effect of Cost-benefits for the relationship between student perception and student persistence 2/03/2011

20. 20 DISCUSSION & IMPLICATIONS OF THE RESEARCH (Cont.) Research Question I Hypothesis of RQ1 is partially accepted and rejected. External attribution decreased in the odds of intent to enroll by a factor of.159 for Q13/.213 for AdQ13; Academic incompatibility increased by a factor of 3.796 for Q13; Academic integration was statistically significant on Q14. Prior online: Q13 & Q14; Single: Ad.Q13; Auditory: AdQ13// External attribution: Q13, AdQ13, & Q14 Discussion & Suggestions Kember model: The importance of Social & Academic integration in distance education In this study: External attribution (negative) is dominant The harm of social networking for student persistence: Kord (2008), Hewitt (2003) Suggestions: 1. E-learning institutions need to understand the trend of students 2. Reducing External attribution such as social networking by reinforcing college website (user friendly) and providing time management course for multiple obligations 3. Increasing Academic integration by course related feedback. 4. Tailored courses for the Academic incompatibility (Intensive, regular, extended course) 5. Prior online experience/ auditory learning style 2/03/2011

21. 21 DISCUSSION & IMPLICATIONS OF THE RESEARCH (Cont.) Research Question II The hypothesis of mediate effect of GPA on the relationship between S. Perceptions & S. Persistence was partially accepted. A partial mediation effect of GPA. Discussion and Suggestions GPA & persistence: Woosely (2009), Davis (2010) Direct effect of GPA and partial mediate effect Based on the results of RQ I, GPA can be increased by the academic feedback and encouragement. Allow students flexible time line to understand the content of the course Research Question III The hypothesis of mediate effect of Cost-benefits on the relationship between S. Perceptions & S. Persistence was accepted. No mediation effect of Cost-benefit. Cost-benefits & persistence: Tinto (1975), Strevy (2009), Stuart (2010) Yet the significant relationship among academic integration, academic incompatibility, and Cost-benefits. 2/03/2011

22. 22 DISCUSSION & IMPLICATIONS OF THE RESEARCH (Cont.) Implication & Conclusion Kember (1995) included external attribution and academic incompatibility as a harmful factor External attribution was significant to most scores of student persistence: 1) Reflecting the current stream of e-learning environment such as IT & Social network, 2) Time management for multiple obligations of students Academic incompatibility & Academic integration: Tailored due date, flexible coursework, feedback, & encouragement of student performance GPA: Encouragement of student performance by increasing appropriate academic environment Prior online experience, Single, & Auditory learning style 2/03/2011

23. 23 DISCUSSION & IMPLICATIONS OF THE RESEARCH (Cont.) Recommendations & Limitations Recommendations for future research Sample pools from 100% e-learning institutions Administrator, faculty, and staff perspective for student persistence Examine and compare the tailored programs for student persistence: intensive, regular, and extended Three scores of student persistence in this study: compare, develop, or elaborate the definition of student persistence. Limitations Non-random sample of students matriculating in online and hybrid courses Some students might select the online courses without original intention Learning style was self-assessed by participants The DESP inventory is mainly focused on student perceptions, thus the lack of identifying the institution's e-learning environment The study may not be generalized to other e-learning students in other locations or having other values for their education 2/03/2011