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Exploring Dialogism Using Language Models

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Artificial Intelligence in Education (AIED 2021)

Abstract

Dialogism is a philosophical theory centered on the idea that life involves a dialogue among multiple voices in a continuous exchange and interaction. Considering human language, different ideas or points of view take the form of voices, which spread throughout any discourse and influence it. From a computational point of view, voices can be operationlized as semantic chains that contain related words. This study introduces and evaluates a novel method of identifying semantic chains using BERT, a state-of-the-art language model for computational linguistics. The resulting model generalizes to multiple relations including repetitions, semantically related concepts from WordNet (i.e., synonyms, hypernyms, hyponyms, and siblings), as well as pronominal resolutions. By combining the attention scores between words, word pairs are merged into connected components that denote emerging voices from the discourse. The introduced visualization argues for a more dense capturing of inner semantic links between words and even compound words in contrast to classical methods of building lexical chains.

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Notes

  1. 1.

    https://www.spacy.io, Retrieved April 15th, 2021.

  2. 2.

    http://lsa.colorado.edu/spaces.html, Retrieved April 15th, 2021.

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Acknowledgments

This research was supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNCS – UEFISCDI, project number TE 70 PN-III-P1-1.1-TE-2019-2209, ATES – “Automated Text Evaluation and Simplification”, the Institute of Education Sciences (R305A180144 and R305A180261), and the Office of Naval Research (N00014-17-1-2300; N00014-20-1-2623). The opinions expressed are those of the authors and do not represent views of the IES or ONR.

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Correspondence to Mihai Dascalu .

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Ruseti, S., Dascalu, MD., Corlatescu, DG., Dascalu, M., Trausan-Matu, S., McNamara, D.S. (2021). Exploring Dialogism Using Language Models. In: Roll, I., McNamara, D., Sosnovsky, S., Luckin, R., Dimitrova, V. (eds) Artificial Intelligence in Education. AIED 2021. Lecture Notes in Computer Science(), vol 12749. Springer, Cham. https://doi.org/10.1007/978-3-030-78270-2_53

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  • DOI: https://doi.org/10.1007/978-3-030-78270-2_53

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