DEVELOPMENT OF METHODOLOGIES TO ASSESS THE IMPACT OF AUTONOMOUS ROBOTICS COMPETITIONS IN SCIENCE, TECHNOLOGY, ENGINEERING, AND MATH EDUCATION

Competition can drive students to work harder resulting in better acquired skills. Our goal is to assess how robotic competitions improve students' science, technology, engineering, and math skills. To prove the unique benefit of interdisciplinary robotic competitions we need measurable data that quantifies the student's experiences. This can be acquired through short assessments given to a group of students before and after a robotics competition. Another group of students, who did not participate in the competition, act as a control group by also taking the same pre- and post-assessments. Methodologies including assessment questions, procedures and web-based database tools were developed to aid in this research. User friendliness was a key requirement. [REMOVED] (www.[REMOVED].net), an annual autonomous robotics competition for 5th to 12th grade students, was used to complete this research. [REMOVED] challenges teams of students to design, build, and program robots. A web-based assessment tool, allowing the researcher to anonymously gather assessment data and analyze the students’ performance, was developed and integrated into the website [REMOVED].org. This tool included functions for contacting competition coaches using the [REMOVED] database, posting online assessments, gathering data, and analyzing results. The tool also generated unique codes to insure full anonymity for students. The codes were used to hold the assessment results to compare the pre- and post-assessment scores. A preliminary test was held during [REMOVED] 2008, a sub program of [REMOVED]. At this event the tools were proven to work completely for data acquisition. However, the environment, timing, and interface all had unexpected effects on student and coach participation during the test. Psychological aspects of this assessment were realized and had to be incorporated into a refinement of the overall methodology. In order to collect statistically reliable and valid data the system has to be tailored to encourage a dynamic group of volunteers to participate even though they get no direct reward. Incorporating these lessons learned will enhance our scientific process of measuring the improvement of the participants’ skills.