About Us

Math Machines began in 1995 at Sinclair Community College in Dayton, Ohio. Robert Chaney (mathematics), Fred Thomas (physics) and Marta Gruesbeck (engineering) were the “Foundations Team” within one of the first grants from the National Science Foundation’s Advanced Technological Education program. We were present as NSF put the T in STEM—expanding beyond their traditional focus on science, engineering and math. After Fred retired from Sinclair, our team kept working as an independent 501(c)(3) organization. With additional support from NSF as well as from several other sources, we focused on designing hardware, software and classroom activities the connected science, technology, engineering and mathematics. We owe a powerful debt to the many secondary school and community college educators who participated in our workshops and added to our understanding. Although the non-profit 501(c)(3) was closed in 2021, we are continuing here to share the ideas and products of our work.

Mission and Tool

Our mission has always been to improve the quality of mathematical education, enhance the transfer of mathematical thinking into other classes, and increase students’ ability to apply rigorous mathematics outside the classroom. Our primary tool for carrying out this mission is “math machines”—simple devices which give an immediate, physical, dynamic expression to “abstract” mathematical equations.

How and Why Math Machines Improve Learning

Discovery is an essential component of effective learning experiences. Textbooks, lectures and demonstrations can be valuable, but students must still discover for themselves how concepts and methods fit into their own minds. Ultimately, we must each construct our own understanding by selecting, adapting and assembling the ideas we encounter.

Motivation is crucial. Many students have already tuned out, either because they believe math and science are "useless" or--worse--because they believe they are too "stupid" to master difficult material. Most students will excel in math and science when they see that the material is relevant and when they believe that they can succeed. It certainly helps too if we can make the learning both challenging and fun.

Time on Task is critical. Students learn more if they spend more time working with and thinking about the key ideas. Some students may be very good at quickly memorizing answers for a test, but the kind of learning that will last a lifetime does require time and focused effort. Short, focused and fun tasks are a good way to keep students engaged with the material long enough to learn it thoroughly.

Positive social interactions are key. Both in school and on the job, people must work effectively as part of a group. Positive interactions and improved learning occur when students and teachers work together to achieve shared goals. If, for example, students work together to move a SAM robot through a maze, the tasks of measurement, calculation and planning become shared responsibilities. If teachers of math, science and technology work together to help students master difficult skills and concepts, everyone benefits.

Realistic Career Applications should be part of all learning in math, science and technology. Every student (even the exceptional few who go on to earn a Ph.D. in math or science) will eventually need to earn a living. School-based education must always look beyond the school environment. This does not mean, however, that we should focus on narrow technical training. Good, high-paying jobs demand that students be able to solve realistic semi-structured problems, to apply math and science to realistic problems, and to adapt to new and often challenging situations. Career education is not an extra topic for math and science teachers--it's a better way of teaching the fundamental concepts and skills.

Real Assessment is better than testing. We all need tests at some point, but eventually we must judge ourselves in terms of what we actually achieve. Real tasks allow students to find out for themselves what they can do and what they still need to learn. By guiding students as they master real tasks, we can help them understand for themselves the power of what they know and what they can do.