Innovators in mathematics and science education have developed uses of technology aimed at increasing children’s access to complex and important concepts. An example of a technology in pervasive use is the graphing calculator. About half of American high schools students have a graphing calculator. Large, sound data sets contain data on the effects of pervasive use. In particular, frequent use of a graphing calculator is associated with high scores on the National Assessment of Educational Progress (NAEP). (The National Center for Educational Statistics calls NAEP “the Nation’s Report Card”). Experimental evidence backs this result: a meta-analysis of 54 experiments shows strong positive effects when graphing calculators are used as a component of a curricular intervention. Theory supports the result as well. For example, Mayer’s theory of multimedia predicts gains when linguistic (e.g., Algebra) and visual (e.g., Graphs) are both used. Interestingly, however, not all uses of technology are beneficial. For example, the use of computers for drill and practice is negatively correlated with scores on NAEP. This finding raises issues of design and classroom practice.
With respect to design, we can think of technology as filling a gap between elementary school and disciplinary training at the university level. At the elementary school level, well-designed physical manipulatives are very common and quite effective. At the university level, no one would question the appropriateness of access to powerful discipline-specific applications. What is the pathway from physical manipulatives to powerful disciplinary applications? Researchers have developed “virtual manipulatives” and “modeling tools” to fit in the development sequence between elementary school and university education. Overall, researchers see technology not merely as enabling learning things better but also enabling learning of better things. Researchers do not expect a direct impact from technology on children’s cognition or attitudes. Instead, a typical logical model would trace the impact of alignment to state’s standards and mandatory assessments. The role of teacher professional development and teaching practice would be an important focus. As it is common to find significant variance at the school, classroom, and child levels, statistical analysis is performed using Hierarchical Linear Modeling.
Research funded by the National Science Foundation tends to focus on how interventions can enable students to learn more sophisticated science or mathematics concepts. Research funded by the U.S. Department of Education tends to look at how to improve test performance at a particular grade level. Due to these emphases, very little longitudinal research is performed on the consequences to children of transitions between media-rich and media-poor learning environments. By focusing on longitudinal and cross-context studies, NIH could contribute in important ways to what we know about how children learn with media.