A part-of-speech-based exploratory text mining of students’ looking-back evaluation

Toshiro Minami, Sachio Hirokawa, Yoko Ohura, Kiyota Hashimoto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In our lectures at universities, we observe that the students’ attitudes affects a lot to their achievements. In order to prove this observation based on data, we have been investigating to find effective methods that extract students’ attitudes from lecture data; such as examination score as an index to student’s achievement, attendance and homework data for his/her effort, and answer texts of the term-end questionnaire as information source of attitude. In this chapter, we take another approach to investigate the influences of words used in the answer texts of students on their achievements. We use a machine learning method called Support Vector Machine (SVM), which is a tool to create a model for classifying the given data into two groups by positive and negative training sample data. We apply SVM to the answer texts for analyzing the influences of parts of speech of words to the student’s achievement. Even though adjectives and adverbs are the same in the sense that they modify nouns and verbs, we found that adverbs affects much more than adjectives, as a result. From our experiences so far, we believe that analysis of answers to the evaluations of students toward themselves and lectures are very useful source of finding the students’ attitudes to learning.

Original languageEnglish
Title of host publicationAdvances in Natural Language Processing, Intelligent Informatics and Smart Technology - Selected Revised Papers from the 11th International Symposium on Natural Language Processing SNLP-2016 and the 1st Workshop in Intelligent Informatics and Smart Technology
EditorsRachada Kongkachandra, Thepchai Supnithi, Thanaruk Theeramunkong
PublisherSpringer Verlag
Pages61-72
Number of pages12
ISBN (Print)9783319700151
DOIs
Publication statusPublished - Jan 1 2018
Event11th International Symposium on Natural Language Processing, SNLP-2016 and 1st Workshop in Intelligent Informatics and Smart Technology, 2016 - Phranakhon Si Ayutthaya, Thailand
Duration: Feb 10 2016Feb 12 2016

Publication series

NameAdvances in Intelligent Systems and Computing
Volume684
ISSN (Print)2194-5357

Other

Other11th International Symposium on Natural Language Processing, SNLP-2016 and 1st Workshop in Intelligent Informatics and Smart Technology, 2016
CountryThailand
CityPhranakhon Si Ayutthaya
Period2/10/162/12/16

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

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    Minami, T., Hirokawa, S., Ohura, Y., & Hashimoto, K. (2018). A part-of-speech-based exploratory text mining of students’ looking-back evaluation. In R. Kongkachandra, T. Supnithi, & T. Theeramunkong (Eds.), Advances in Natural Language Processing, Intelligent Informatics and Smart Technology - Selected Revised Papers from the 11th International Symposium on Natural Language Processing SNLP-2016 and the 1st Workshop in Intelligent Informatics and Smart Technology (pp. 61-72). (Advances in Intelligent Systems and Computing; Vol. 684). Springer Verlag. https://doi.org/10.1007/978-3-319-70016-8_6