Adaptive Tool for Teaching Programming Using Conceptual Maps

Volarić, Tomislav; Vasić, Daniel; Brajković, Emil

doi:10.1007/978-3-319-47295-9_27

Cited by 7 publications

(1 citation statement)

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“…In this paper we extend our research from [1] where we presented and evaluated methods for finding similarity between textual data. These methods can be used inside modules of ITS to evaluate student performance [2]. ITS systems are computer-based instructional systems that are composed of four principal models: the expert model, the learner model, the tutor model and the interface.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Methods for Sentence Similarity for Use in Intelligent Tutoring System

Brajković¹,

Vasić²,

Volarić³

2018

Adv. sci. technol. eng. syst. j.

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Finding similarity of textual data is very important task in natural language processing. In this article we present approach to finding similarity of words, paragraphs, sentences and documents. Semantic similarity is one of the central tasks in many applications, including text summarization, Intelligent Tutoring Systems (ITS) etc. In ITS sentence similarity is used to compare the student's response with the correct answer. The result is used to gain information about student's level of knowledge. We propose three different methods that measure text to text semantic relatedness. There are multiple approaches to finding the right measure to determine the similarity of the sentences. Some measure the alignment of characters, and other measure semantic similarity between sentences. In this work we present and evaluate methods for finding not just similarity of sentences but even also similarity of whole paragraphs and documents. We have evaluated these methods using the data from the Yahoo Question and Answer of the Non-Factual Data Set.

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Section: Introductionmentioning

confidence: 99%