Promote an Abstract Understanding of the Problem-Solving Knowledge in the Theory of Computation Through Visualization-Based Intelligent Tutor System

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Abstract

Just like heart is to the body, so is theory of computation for computer science and engineering discipline. Course deals with designing of abstract machines like finite automata, push down automata and Turing machines. It not only involves designing but also theoretical concepts like theorems, proofs and examples and to deal with examples accordingly. This course involves visualization, imagination which is difficult for students in the physical classrooms and teacher needs to blend traditional black board teaching method with active learning strategies to make learning easy. A visualization-based intelligent tutor system (ITS) is a computer system that aims to provide immediate and customized instruction to learners, usually without intervention from a human teacher. This instructional strategy is helpful for enabling learning in positive manner as students can “see” what is happening and gets feedback. The active way of learning se using Java Formal Languages and Automata Package (JFLAP) tool. It is a preexisting software tool created by Professor Susan Rodger and her students at Duke University. The control group and experimental group results are presented in this paper partially; supporting the effect of the usage of the visualization-based intelligent tutor system on student learning. The experiment shows that use of VIT enhance learning ability and interest in the course. The usefulness is supported with survey questionnaire.

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Dixit, R., Nirgude, M., & Yalagi, P. (2022). Promote an Abstract Understanding of the Problem-Solving Knowledge in the Theory of Computation Through Visualization-Based Intelligent Tutor System. In Smart Innovation, Systems and Technologies (Vol. 251, pp. 19–28). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-16-3945-6_3

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