摘要：AbstractThe growth of areas such as automation and robotics demands autonomous systems endowed with sophisticated perception systems like machine vision. However, undergraduate level education is not providing good results in this sense, because students do not participate in the creation of their own knowledge; they are only passive observers. On the other hand, FPGA technology has great potential in areas such as machine vision where many hypotheses are evaluated concurrently, high computation rates are required, and the current systems are far from equaling human performance. Our research notes that by using FPGA and constructivist learning as the methodology, assessment of learning in electronic sciences is not a separate process after learning has occurred, but rather learning and assessment are coterminous. Thus, this paper presents a constructivist tool focused on a machine vision course that allows students to implement and evaluate algorithms of this area on an FPGA. Selectioan and peer review under responsibility of Prof. Dr. Ferhan Odabaşı
