The Impact of Teaching Presence in Intensive Online Courses on Perceived Learning and Sense of Community: A Mixed Methods Study

This mixed methods concurrent triangulation design study was predicated upon two models that advocated a connection between teaching presence and perceived learning: the Community of Inquiry Model of Online Learning developed by Garrison, Anderson, and Archer (2000); and the Online Interaction Learning Model by Benbunan-Fich, Hiltz, and Harasim (2005). The objective was to learn how teaching presence impacted students’ perceptions of learning and sense of community in intensive online distance education courses developed and taught by instructors at a regional comprehensive university. In the quantitative phase online surveys collected relevant data from participating students (N = 397) and selected instructional faculty (N = 32) during the second week of a three-week Winter Term. Student information included: demographics such as age, gender, employment status, and distance from campus; perceptions of teaching presence; sense of community; perceived learning; course length; and course type. The students claimed having positive relationships between teaching presence, perceived learning, and sense of community. The instructors showed similar positive relationships with no significant differences when the student and instructor data were compared. The qualitative phase consisted of interviews with 12 instructors who had completed the online survey and replied to all of the open-response questions. The two phases were integrated using a matrix generation, and the analysis allowed for conclusions regarding teaching presence, perceived learning, and sense of community. The findings were equivocal with regard to satisfaction with course length and the relative importance of the teaching presence components. A model was provided depicting relationships between and among teaching presence components, perceived learning, and sense of community in intensive online courses.

Evaluating Measurement Invariance with Censored Ordinal Data: A Monte Carlo Comparison of Alternative Model Estimators and Scales of Measurement

Evaluations of measurement invariance provide essential construct validity evidence. However, the quality of such evidence is partly dependent upon the validity of the resulting statistical conclusions. The presence of Type I or Type II errors can render measurement invariance conclusions meaningless. The purpose of this study was to determine the effects of categorization and censoring on the behavior of the chi-square/likelihood ratio test statistic and two alternative fit indices (CFI and RMSEA) under the context of evaluating measurement invariance. Monte Carlo simulation was used to examine Type I error and power rates for the (a) overall test statistic/fit indices, and (b) change in test statistic/fit indices. Data were generated according to a multiple-group single-factor CFA model across 40 conditions that varied by sample size, strength of item factor loadings, and categorization thresholds. Seven different combinations of model estimators (ML, Yuan-Bentler scaled ML, and WLSMV) and specified measurement scales (continuous, censored, and categorical) were used to analyze each of the simulation conditions. As hypothesized, non-normality increased Type I error rates for the continuous scale of measurement and did not affect error rates for the categorical scale of measurement. Maximum likelihood estimation combined with a categorical scale of measurement resulted in more correct statistical conclusions than the other analysis combinations. For the continuous and censored scales of measurement, the Yuan-Bentler scaled ML resulted in more correct conclusions than normal-theory ML. The censored measurement scale did not offer any advantages over the continuous measurement scale. Comparing across fit statistics and indices, the chi-square-based test statistics were preferred over the alternative fit indices, and ΔRMSEA was preferred over ΔCFI. Results from this study should be used to inform the modeling decisions of applied researchers. However, no single analysis combination can be recommended for all situations. Therefore, it is essential that researchers consider the context and purpose of their analyses.

A Comparative Study of the Information-Seeking Behavior of Bachelor of Science and Master of Science Agricultural Extension and Education Students

This study compares information-seeking behavior of Bachelor of Science and Master of Science students in the fields of agricultural extension and education. The authors surveyed Iranian students in departments of agricultural extension and education at four universities in Tehran, Shiraz, Mollasani, and Kermanshah. This study focused on three aspects: (1) comparison of amounts of information-seeking behavior between Bachelor of Science and Master of Science agricultural extension and education students; (2) comparison of information-seeking behavior varieties in Bachelor of Science and Master of Science agricultural extension and education students; (3) Comparison of amounts of available information resources at four universities and its effectiveness on students' information-seeking behavior; and (4) comparison of research and educational outputs in Bachelor of Science and Master of Science students. Scale free technique, division by mean method, principal components analysis technique, Delphi method, t-test, correlation and regression tools were used for data analysis. This study revealed that Bachelor of Science students' information-seeking behavior is for improving educational output, but Master of Science students' information-seeking behavior is for promoting research output. Among varieties of Internet searching skills, library searching skills, and awareness of library information-seeking methods with students' information-seeking behavior, there are not significant differences between two groups of students.

Use of policy, education, and enforcement to reduce binge drinking among university students: The NU Directions project

This paper describes a program, conducted over a 5-year period, that effectively reduced heavy drinking and alcohol-related harms among university students. The program was organized around strategies to change the environment in which binge drinking occurred and involved input and cooperation from officials and students of the university, representatives from the city and the neighborhood near the university, law enforcement, as well as public health and medical officials. In 1997, 62.5% of the university’s approximately 16,000 undergraduate student population reported binge drinking. This rate had dropped to 47% in 2003. Similar reductions were found in both self-reported primary and secondary harms related to alcohol consumption.

African American Student Access To and Completion Of Higher Education, 1960-1992: A Correspondence Theory Analysis

“This presentation utilizes correspondence theory to analyze African American undergraduate student access to and completion of higher education in the United States. Findings from this research are presented and policy recommendations affecting Black student enrollment and graduation are discussed.”