NDLI: Assistance and Feedback Mechanism in an Intelligent Tutoring System for Teaching Conversion of Natural Language into Logic

Content Provider	Springer Nature Link
Author	Perikos, Isidoros Grivokostopoulou, Foteini Hatzilygeroudis, Ioannis
Copyright Year	2017
Abstract	Logic as a knowledge representation and reasoning language is a fundamental topic of an Artificial Intelligence (AI) course and includes a number of sub-topics. One of them, which brings difficulties to students to deal with, is converting natural language (NL) sentences into first-order logic (FOL) formulas. To assist students to overcome those difficulties, we developed the NLtoFOL system and equipped it with a strong assistance and feedback mechanism. In this work, first, we present that feedback mechanism. The mechanism can provide assistance before an answer is submitted, if requested, but mainly it provides assistance after an answer is submitted. To that end, it characterizes the answer in terms of completeness and accuracy to determine the level of incorrectness, based on an answer categorization scheme, introduced in this paper. The automatically generated natural language feedback sequences grow from general to specific and can include statements on a student’s metacognitive state. Feedback is provided as natural language sentences automatically generated through a template-based natural language generation mechanism. Second, we present an extensive evaluation of the effectiveness of the assistance and feedback mechanism on students’ learning. The evaluation of feedback with students showed that full feedback sequences lead to greater learning gains than sequences consisting of only flag feedback and bottom-out hints (n = 226), and that generic, template-based feedback sequences are comparable to the utility of problem-specific hints generated by human tutors (n = 120).
Starting Page	475
Ending Page	514
Page Count	40
File Format	PDF
ISSN	15604292
Journal	International Journal of Artificial Intelligence in Education
Volume Number	27
Issue Number	3
e-ISSN	15604306
Language	English
Publisher	Springer New York
Publisher Date	2017-02-24
Publisher Institution	International AIED Society
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Student assistance Learning analytics Answer categorization Feedback sequencing Educational Technology User Interfaces and Human Computer Interaction Feedback effectiveness evaluation Artificial Intelligence (incl. Robotics) Error categorization Computers and Education Feedback framework
Content Type	Text
Resource Type	Article
Subject	Education Computational Theory and Mathematics E-learning

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