Using Data Analysis to Improve Student Learning: Toward 100% Proficiency

Education reforms such as A Nation at Risk and Goals 2000 have come and gone. However, we can be confident that the goal of student improvement shall not pass if the core mission is student learning. The true mission of learning has prompted educators to ponder the following questions: How do we need each student to behave? How do we know when each student has behaved properly? How do we respond when students misbehave?

Standards of behavior such as attendance, discipline, homework, and academic learning are the answering points for the first question with connections to school policy and curriculum. The question of "how do we know?" is answered by assessment with relevant data support. Decisions to adjust student behaviors or to modify a school program are based on thorough data analysis and interpretation. What is the evidence that a student is not learning? A teacher is not effective? A school program is not serving the needs of students? The evidence can be addressed by information from a student record book; a teacher performance summary; a program survey or other data based reports. This book uses a unique blend of quantitative and qualitative strategies to tackle challenges in both student and school improvement and should be of interest to all educators.

Ovid K. Wong, Ph D., is dean of Adult Basic Education, Triton College in River Grove, Illinois.

Ming-Long Lam, Ph.D. is the manager of statistical research in SPSS, Inc. in Chicago.