• Perceptual mismatches in a university English as a second language classroom

      Adams, Kristine A. L. (2012-08)
      This study investigates perceptual mismatches in a university English as a second language classroom. Perceptual Mismatches in the classroom are a failure on the part of teachers and students to understand or interpret something the same way. These mismatches can lead to missed learning opportunities that impede teaching and learning. The purpose of this teacher research was to identify mismatches in a university ESL classroom in the U.S. This course was designed for Chinese degree completion students. Data was collected via questionnaires, interviews, dialogue journals, and observations. The results of this study show a tendency in mismatches between teachers and students dealing with perceptions of teacher centered classrooms and learner centered classrooms, and communicative interactions. These mismatches may occur due to previous learning experiences and expectations. This study also shows there is a tendency towards mismatches between teachers, and there is much room in this field for further studies.
    • The treatment of missing data on placement tools for predicting success in college algebra at the University of Alaska

      Crawford, Alyssa (2014-05)
      This project investigated the statistical significance of baccalaureate student placement tools such as tests scores and completion of a developmental course on predicting success in a college level algebra course at the University of Alaska (UA). Students included in the study had attempted Math 107 at UA for the first time between fiscal years 2007 and 2012. The student placement information had a high percentage of missing data. A simulation study was conducted to choose the best missing data method between complete case deletion, and multiple imputation for the student data. After the missing data methods were applied, a logistic regression with fitted with explanatory variables consisting of tests scores, developmental course grade, age (category) of scores and grade, and interactions. The relevant tests were SAT math, ACT math, AccuPlacer college level math, and the relevant developmental course was Devm /Math 105. The response variable was success in passing Math 107 with grade of C or above on the first attempt. The simulation study showed that under a high percentage of missing data and correlation, multiple imputation implemented by the R package Multivariate Imputation by Chained Equations (MICE) produced the least biased estimators and better confidence interval coverage compared to complete cases deletion when data are missing at random (MAR) and missing not at random (MNAR). Results from multiple imputation method on the student data showed that Devm /Math 105 grade was a significant predictor of passing Math 107. The age of Devm /Math 105, age of tests, and test scores were not significant predictors of student success in Math 107. Future studies may consider modeling with ALEKS scores, and high school math course information.