Publication details
Tutoring and Automatic Evaluation of Logic Proofs
| Authors | |
|---|---|
| Year of publication | 2013 |
| Type | Article in Proceedings |
| Conference | Proceedings of the 12th European Conference on e-Learning ECEL 2013 |
| MU Faculty or unit | |
| Citation | |
| Field | Use of computers, robotics and its application |
| Keywords | graph mining; logic proofs; resolution; automatic evaluation; frequent subgraphs; classification |
| Description | Tutoring of logic proofs is an important part of undergraduate courses of logic. Commonly, a tutor trains and tests students’ skills to build correct logic proofs. We introduce a system for training of students’ ability to construct correct proofs in propositional or predicate logic. In addition to common techniques including presentations supported by slides and exercises we use animations which are based on carefully selected demonstrative examples and their step-by-step solutions. Animations are interactive so that a student may choose a particular step, a sequence of steps, and/or a particular task. In order to test students’ knowledge, we prepared a questionnaire that captures the entire process of a logic proof construction. A student constructs a proof and then answers questions from the questionnaire. We describe the design of the questionnaire and discuss its dis/advantages. We then apply frequent subgraph mining together with supervised machine learning algorithms to perform an automatic evaluation of correctness of the proofs. In addition to classifying the proofs as correct or incorrect, a report containing the summary of errors and suggested penalty points is produced. |