Technology-enhanced learning (TEL) of finite state machines (FSMs)

Abstract

Finite State Machines (FSMs) are pivotal in both computer science and engineering, essential for numerous software and hardware applications. Traditional educational approaches to teaching FSMs typically involve theoretical lectures supplemented by physical modeling. However, these methods often lack the dynamic and interactive engagement necessary for optimal learning. With the increasing adoption of Technology-Enhanced Learning (TEL) in education, there is a significant opportunity to improve how FSMs are taught. This project introduces an innovative approach by developing an algorithm that generates random state diagrams and truth tables. This tool allows students to interactively engage with FSM concepts through completing and checking these elements themselves, thereby fostering a deeper understanding of the material. Preliminary results from the implementation of this tool show that it successfully enhances students' learning experience by providing immediate feedback and encouraging active learning. This report details the development of the algorithm, its integration into a TEL environment, and evaluates its effectiveness in enhancing students' understanding of FSMs.