UC Berkeley

Graph technologies are now widely available in K-12 science and mathematics classrooms. These technologies have the potential to impact the learning of science and mathematics, especially by supporting student investigations. We use meta-analysis to analyze 42 design and comparison studies involving data from 7699 students spanning over 35 years. In these studies, graphing technologies include computer software such as simulations; online tools such as graph utilities; and sensors such as temperature probes. We characterize the assessments used to measure graphing. We describe the investigative activities that graphing supports including generating hypotheses or predictions, collecting data, analyzing or interpreting data, and reflecting. Studies show that graphing technologies impact learning of mathematics and science topics as well as graphing itself. These technologies are especially advantageous for learning complex topics where students need to conduct investigations to interpret change over time or position such as functions, kinematics, and thermodynamics. Recent studies take advantage of logs of student interactions to study the design of automated guidance for graphing. We discuss the implications of these findings for instruction at the K-12 level.