![]() Enders, University of California – Los Angeles PDC02 : An Introduction to Multiple Imputation for Educational Research There will be designated time for participants using EdSurvey to practice the techniques with the variables of their own interest. This course will introduce unique design features of ILSAs data to researchers and provide guidance in data analysis strategies that they require, including the selection and use of appropriate plausible values, sampling weights, and variance estimation procedures. The participants will learn how to use the EdSurvey package to perform the statistical techniques used most often in ILSAs data analyses, including selecting an appropriate sample, estimating the mean scale scores for groups of students, benchmark analysis, gap analysis, linear regression, logistic regression, and correlations. They will learn how to manipulate the data, including merging, subsetting, and recoding data. Participants will begin installing the EdSurvey R package and importing the data files into R. Public-use TIMSS data files will be used as example data sets. This course will introduce participants to the procedures of analyzing data from international large-scale assessments (ILSAs) using NCES’s EdSurvey R Package. Department of Education Paul Dean Bailey, American Institutes for Research Ebru Erberber, American Institutes for Research Instructors: Ting Zhang, American Institutes for Research Emmanuel Sikali, U.S. In the end of the study, recommendations were made for curriculum designers, classroom practitioners, and further studies.PDC01 : Analyzing Data From International Large-Scale Assessments Using R The more helpful suggestions they obtained, the more positive opinions they gave to a certain type of feedback. Student writers' responses to each type of feedback were closely related to the amount of constructive comments they received. On the whole, intermediate and low achievers, based on their preference, ranked teacher feedback the most important, then peer feedback and finally self-directed feedback whereas high achievers placed teacher feedback first, self-directed feedback second, and peer feedback last. In addition, all students were in favor of modified teacher feedback but gave negative opinions to traditional teacher feedback. However, intermediate and low achievers gave a higher percentage of satisfaction to peer response activities than high achievers because the former could obtain more constructive peer feedback than the latter. Major findings indicated that intermediate and low achievers, though making more efforts in conducting self-directed feedback, felt unsatisfied with this activity while high achievers, investing less energy and time, gave more positive opinions to this activity. A rubric was developed to examine the changes students made after having incorporated the three types of feedback into their drafts. The qualitative software, ATLAS.ti, was employed to analyze interview and peer response data according to the code lists developed for this purpose. This research, based on the activity system model proposed by Engestrom (1987), was a case study in which interviewing student participants, observing classroom activities, audiotaping peer response sessions, and examining students' drafts and feedback sheets were the methods to collect data. ![]() Low achievers have difficulties in keeping up with competent writers in learning writing skills while advanced students complain of their learning too little from the class. Large size writing classes, quite common in private institutions of higher education in Taiwan, cannot be effectively operated to meet individual students' needs in improving their writing performance. The purpose of this study was to examine students' experiences and perceptions of multiple interaction activities (self-directed, peer, and teacher feedback) implemented in a large multilevel EFL writing class in one private technological university in the southern part of Taiwan.
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