Many argue that the United States is falling behind other countries in technology innovation. Some attribute this situation to ineffective education in the areas of math, science, and technology. Research using affective measures has provided evidence of links between student attitudes in math and technology education. With the aim of extending the research, this study examines the psychometric properties of the Mathematics Information Processing Scale1 (MIPS). The MIPS uses both cognitive and affective measures to explore various dimensions of students’ approaches to learning statistics and mathematics. The original study used exploratory factor analysis, while this study uses confirmatory factor analysis to revise the MIPS instrument. By combining both cognitive and affective measures in a single instrument, the MIPS offers the potential to contribute new research knowledge toward the goal of improving math and technology education.