Unblinding a Braille machine — A case study of reverse problem-based learning

Engineering Education includes not only teaching theory fundamental concepts but also its verification during practical lessons in laboratories. The used strategies to carry out this action are frequently founded on Problem Based Learning that start from a given state and point forward to a target state. The possibility or the performance of this action depends on previous states if the present one was caused by or resulted from earlier stages. This often happens in engineering education if the achieved results do not match the desired ones, e.g. when programming code is being developing or when the cause of the wrong behavior of an electronic circuit is being identified. It is thus important to also prepare students to go in the reverse way, i.e. given a start state generate the explanation or even the principles that underlie it. Later on, this sort of skills will be important. For instance, to a doctor making a patient´s story or to an engineer discovering the source of a malfunction. Among others, this learning methodology presents pedagogical advantages besides the enhanced preparation of students to their future work. The present work relates an automation project developed by a group of students, in a laboratory. The main target was to improve the performance of a given machine. However, in a scenario of reverse problem-base learning, students had first to discover and characterize the entire machines function before being allowed (and being able) to propose a solution for the presented problem.