In recent years considerable concern has arisen over cross-national student’s math achievement.
Numerous studies focusing on 8th grade student’s math achievement have been published.
However, most of the researchers adopted traditional statistical techniques to test their
hypotheses. Moreover, these hypotheses assumed restrictions without exploring the findings.
Therefore, the purpose of this study is to implement data mining techniques to re-examine the
Trends in International Mathematics and Science Study (TIMSS) 2007 among 8 grades’ student
in Taiwan and the U.S. Data mining techniques are applied to extract the TIMSS 2007 dataset to
explore and identify a new institutional typology based on the pattern of student types and
countries. After analyzing the dataset, this paper will present the findings, as well as information
for improving educational policies and resources in both the U.S. and Taiwan.
Relation:
Taiwan Education Research Association & Pacific Rim Objective Measurement Symposium 2013 (TERA&PROMS2013)
