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Identifying Essential Elements in Justifications of Student Drafts

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Methodologies and Intelligent Systems for Technology Enhanced Learning

Abstract

The proposal draft is the first step to achieve a degree by students in many educational institutions. This proposal is transformed into a thesis after several revisions by an academic adviser. In addition, each proposal must comply with requirements of institutional guidelines. In this paper, we explore a learning approach to identify essential elements: importance, necessity, convenience, and benefits; that are expected to appear in a justification section of a proposal or thesis draft. We present a method based on a Language Model approach. Preliminary results show that the elements of necessity, importance, and benefits obtained acceptable results, considering that this task is complex for an academic adviser. The identification of convenience requires further improvement. A language model based on n-grams showed more consistent and better results than a model based on neural networks. Part of speech tagging contributes to improve results in both language model techniques.

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References

  1. Allen, G.: The graduate students’ guide to theses and dissertations: a practical manual for writing and research. Jossey-Bass Inc. Pub., San Francisco (1976)

    Google Scholar 

  2. Hernández, R., Fernández, C., Batista, M.: Metodología de la investigación. Mc Graw Hill (2010)

    Google Scholar 

  3. González-López, S., López-López, A.: Colección de Tesis y Propuesta de Investigación en TICs: un recurso para su análisis y estudio. XIII Congreso Nacional de Investigación Educativa, p. 15 (2015)

    Google Scholar 

  4. Valenti, S., Neri, F., Cucchiarelli, A.: An Overview of Current Research on Automated Essay Grading. Journal of Information Technology Education 2, 319–330 (2003)

    Article  Google Scholar 

  5. Burstein, J., Marcu, D.: A Machine Learning Approach for Identification of Thesis and Conclusion Statements in Student Essays. Computers and the Humanities 37, 455–467 (2003)

    Article  Google Scholar 

  6. González, S., Bethard, S., López-López, A.: Identifying weak sentences in student drafts: a tutoring system. In: Methodologies and Intelligent Systems for Technology Enhanced Learning, vol. 292, pp. 77–85 (2014)

    Google Scholar 

  7. Daudaravicius, V.: Automated evaluation of scientific writing: AESW shared task proposal. In: Proceedings of the Tenth Workshop on Innovative Use of NLP for Building Educational Applications, pp. 56–63. Association for Computational Linguistics (2015)

    Google Scholar 

  8. Mikolov, T., Deoras, A., Kombrink, S., Burget, L., Cernocký, J.: Empirical evaluation and combination of advanced language modeling techniques. In: INTERSPEECH, pp. 605–608 (2011)

    Google Scholar 

  9. Turian, J., Ratinov, L., Bengio, Y.: Word representations: a simple and general method for semi-supervised learning. In: Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, pp. 384–394. Association for Computational Linguistics (2010)

    Google Scholar 

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Correspondence to Aurelio López-López .

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© 2016 Springer International Publishing Switzerland

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Tadeo, J.R.H., López-López, A., González-López, S. (2016). Identifying Essential Elements in Justifications of Student Drafts. In: Caporuscio, M., De la Prieta, F., Di Mascio, T., Gennari, R., Gutiérrez Rodríguez, J., Vittorini, P. (eds) Methodologies and Intelligent Systems for Technology Enhanced Learning . Advances in Intelligent Systems and Computing, vol 478. Springer, Cham. https://doi.org/10.1007/978-3-319-40165-2_11

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  • DOI: https://doi.org/10.1007/978-3-319-40165-2_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40164-5

  • Online ISBN: 978-3-319-40165-2

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