For many people, a high standard for student learning is desirable. This is what underlies current standard-based science education reforms around the world. As someone who was born and brought up in a less-privileged home and educated in a resource-limited school environment in a developing country, I always had to study hard to meet various standards from elementary to high school to univ- sity. My first book in English published over 10 years ago (Liu, X. [1996]. Mathematics and Science Curriculum Change in the People¿s Republic of China. Lewiston, NY: The Edwin Mellen Press) provided me an opportunity to examine standards (i. e. , Chinese national science teaching syllabi) from a historical and political point of view. I argued that standards are developed for particular poli- cal agendas in order to maintain the privileged position of certain groups (i. e. , urban residents) in a society at expenses of others (i. e. , rural residents). Thus, underneath standards is systematic discrimination and injustice. Since then, I have had opportunities to study the issue of standards in much more breadth and depth. This book, Linking Competence to Opportunities to Learn: Models of Competence and data mining, provides me an opportunity to examine standards from a different perspective: opportunity to learn.

Preface Introduction Equity and Excellence in Standard-based Education Chapter 1 Competence and Opportunity-To-Learn Chapter 2 Models of Competence and Data Mining Chapter 3 Models of Competence and Opportunities to Learn in the Classroom Chapter 4 Models of Competence and Opportunities to Learn at Home Chapter 5 Models of Competence and Opportunities to Learn in Schools Chapter 6 Pedagogical and Policy Implications Appendix A Variables Related to Teaching Practices Measured in 1996 Grades 4 and 8 NAEP Science Appendix B Variables Related to Family Background and Home Environment Measured in 1996 Grades 4 and 8 NAEP Science Appendix C Variables Related to School Context Measured in 1996 Grades 4 and 8 NAEP Science Appendix D Accuracy Measures of Competence Models Appendix E Tutorial on the Weka Machine Learning Workbench Appendix F Machine Learning Algorithms Implemented in Weka