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Faculty Lend a Helping Hand to Student Success: Measuring Student-Faculty Interactions. Amber D. Lambert, Ph.D . Louis M. Rocconi, Ph.D. Amy K. Ribera , Ph.D. Angie L. Miller, Ph.D. Yiran Dong Center for Postsecondary Research Indiana University. Outline. Literature Review - PowerPoint PPT Presentation
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Faculty Lend a Helping Hand to Student Success: Measuring Student-Faculty InteractionsAmber D. Lambert, Ph.D.Louis M. Rocconi, Ph.D.Amy K. Ribera , Ph.D.Angie L. Miller, Ph.D.
Yiran Dong Center for Postsecondary ResearchIndiana University
Outline
0Literature Review
0Current Study
0Methods
0Results
0Discussion
Literature Review
0Student-faculty interactions generally have a positive influence on educational outcomes, such as:0 Cognitive growth and development of college students
(Astin, 1993; Pascarella & Terenzini, 2005)0 Retention (Lau, 2003; Pascarella & Terenzini, 1977)
0Recent researchers have found that not all kinds of interaction have the same impact on student outcomes
Literature Review (cont.)
0 Teaching Clarity0 Refers to teaching methods where “faculty demonstrate a level of
transparency in their approach to instruction and goal setting in an effort to help students better understand expectations and comprehend subject matter” (BrckaLorenz, Ribera, Kinzie, & Cole, p. 2)
0 Positive relationship with various educational outcomes such as student achievement and satisfaction (Hativa, 1998; Pascarella & Terenzini, 2005; Chesebro & McCroskey, 2001).
0 Good Faculty Practices0 Relationship between student and faculty that moves beyond the
formal instruction that takes place during class (Crisp, 2009)
The Current Study
0Main purpose: To explore how to measure student interactions with faculty in a concise way as part of a larger survey.
0 In particular, we are interested in: 0 whether the student-faculty interaction items load onto
two distinct components, 0 if these two components have good measurement
properties, 0 whether these components are good predictors of GPA and
persistence into the second year.
Method: Participants
0Data from the National Survey of Student Engagement (NSSE) 2011 pilot study (NSSE 2.0)
01,006 first-year and 2,578 senior students attending 19 U.S. institutions
0 Institutions represented variety of regions, Carnegie classifications, and enrollment sizes
034% males and 66% females
079% with full-time enrollment status
Method: Measures
0All relevant survey items from the 2011 NSSE 2.0 pilot administration were included in the EFA.
0CFA analyses were done for those items that fell into the student-faculty interactions components.
0For the predicative validity analyses, survey responses were also merged with institution-provided grade-point-average (GPA) and persistence outcome.0 Controls: gender, ethnicity, parental education level, and
prior academic ability (composite SAT and ACT scores)
Method: Analyses
0 A variable was created using a random number generator that put each student into one of two groups.
0 The first group consisting of half of the sample was used to conduct the exploratory factor analyses. 0 Direct oblimin rotation (oblique) used
0 The second half was used in the confirmatory factor analysis. 0 AMOS used to build the model
0 The entire sample was used for the predictive validity analyses.0 Ordinary least squares (OLS) regression models for academic year GPA 0 Logistic regression models for persistence
Confirmatory Factor Analysis: Model-fit Results
Note: Strong model fit is reflected by GFI greater than .85, CFI greater than .90, RMSEA less than .06, and PCLOSE greater than .05.
Model statistics N GFI CFI RMSEA PCLOSE
First-year 306 .999 .999 .0003 .90
Seniors 631 .999 .999 .0140 .93
Path Model for Good Faculty Practices and Teaching Clarity Subscales
Items, CFA Factor Loadings, and Cronbach’s Alphas for First-Year and
Senior StudentsItem FY Factor Loading SR Factor Loading
GFP1 Got to know you and your background .57 .66
GFP2 Taught in ways that encouraged your active participation .71 .86
GFP3 Created an atmosphere conducive to your learning .99 .93
Cronbach’s α .817 .857
TC1 Clearly explained course goals and requirements .66 .78
TC2 Taught course sessions in an organized way .79 .84
TC3 Used examples or illustrations to explain difficult points .76 .83
Cronbach’s α .832 .862
Predicting GPAR2 ΔR2 Beta
First-year
Control Variables .247 -- --
Teaching Clarity .263 .016 .127
Good Faculty Practices .280 .033 .184
Seniors
Control Variables .164 -- --
Teaching Clarity .177 .013 .114
Good Faculty Practices .210 .046 .217
Predicting Persistence
0Those in the middle 50% on Teaching Clarity have 79% greater odds of being retained than those in the bottom quartile of Teaching Clarity
0Those in the top quartile of Teaching Clarity have 53% greater odds of being retained than those in the bottom quartile of Teaching Clarity
0The average persistence rate difference between those in the top and bottom quartile in Good Faculty Practices was 7%
Limitations
0NSSE is limited to those institutions that choose to participate
0Not all of the possible predictors of GPA and persistence were available to us
0Relied on self-reported perceptions of student experiences
Discussion
0These items included in a larger survey serve as a good proxy for student-faculty interactions
0Both the EFA and CFA suggest that these items make two strong scales for teaching clarity and good faculty practices that are also related to one another
0As theorized from the literature, these measures for teaching clarity and good faculty practices also influence students’ GPA and persistence
Discussion (cont.)
0 These results would suggest that the more personal interactions found in the good faculty practices scale, such as got to know you and your background, that are much less likely to be found on course evaluations might be a more important predictor of student success
0 Measures like the short sets of items described previously could provide additional information on some aspects of classroom practices that are not being measured by course evaluations, especially in light of the problems with course evaluations and other assessments of instructor quality
Questions? Comments?
Contact Information
0Amber D. Lambert – email: [email protected] M. Rocconi – email: [email protected] K. Ribera – email: [email protected] L. Miller – email: [email protected] Dong – email: [email protected]
References0 Astin, A. (1993). What matters in college? Four critical years revisited. San Francisco: Jossey-
Bass.0 BrckaLorenz, A., Ribera, A., Kinzie, J., & Cole, E. (in press). Examining effective faculty
practice: Teaching clarity and student engagement. To Improve the Academy, 31. 0 Chesebro, J. L., & McCroskey, J. C. (2001). The relationship of teacher clarity and immediacy
with student state receiver apprehension, affect and cognitive learning. Communication Education, 50(1), 59-68.
0 Crisp, G. (2009). Conceptualization and initial validation of the college student mentoring scale. Journal of College Student Development, 50(2), 177-191.
0 Hativa, N. (1998). Lack of clarity in university teaching: A case study. Higher Education, 36(3), 353-381.
0 Lau, L. K. (2003). Institutional factors affecting student retention. Education, 124(1), 126–136.
0 Pascarella, E. T., Terenzini, P. T. (1977). Patterns of student-faculty informal interaction beyond the classroom and voluntary freshman attrition. Journal of Higher Education, 48(5), 540-552.
0 Pascarella, E. T., & Terenzini, P. T. (2005). How college affects students(Vol. 2): A third decadeof research. San Francisco: Jossey-Bass.
Introducing Updated NSSE
0Retains NSSE’s focus on diagnostic & actionable information
0New Engagement Indicators0 Academic challenge0 Deep approaches to learning0 Collaborative learning0 Quantitative reasoning0 Experiences with faculty0 Campus environment0 Interactions with diversity
0Modules0New & Updated Items0 Comparisons to Prior-Year Results0 FSSE & BCSSE Updates
Register Now for NSSE 2013(deadline Sept.
25)