Textual complexity in oral narratives produced by informants with different levels of education
Abstract
In this paper, a corpus formed by twenty oral narratives (ten produced by elementary school students and ten produced by undergraduate students) is analyzed with the aim of verifying whether the textual complexity of the narratives increases as the level of education increases. The tool used to analyze the textual complexity of the narratives in the corpus is the computational system NILC-Metrix, which employs two hundred metrics for this purpose. Eleven metrics were chosen which demonstrate that the narratives produced by the undergraduate students present higher textual complexity than the narratives produced by elementary school students.
Keywords:
Textual complexity, Narrative, Level of education
References
Antonio, J. D. (1998). “Narrativas orais e narrativas escritas: a estrutura argumental preferida, e outras preferências”. In Faculdade de Ciências e Letras: Doutorado. Universidade Estadual Paulista Júlio de Mesquita Filho.
Antonio, J. D. (2004). “Estrutura retórica e articulação de orações em narrativas orais e em narrativas escritas do português”. In Faculdade de Ciências e Letras: Doutorado. Universidade Estadual Paulista Júlio de Mesquita Filho.
Evers, A. (2018). “A redação engaiolada: padrões lexicais e ensino de redação em cursos pré-vestibulares populares”. In Instituto de Letras: Doutorado. Universidade Federal do Rio Grande do Sul. [link].
Branco, A., Rodrigues, J., Costa, F., Silva, J. and Vaz, R. (2014a). Rolling out Text Categorization for Language Learning Assessment Supported by Language Technology. In Computational Processing of the Portuguese Language: 11th International Conference, PROPOR 2014, Sao Carlos/SP, Brazil, October 6-8, 2014, Proceedings (Vol. 8775, p. 256). Springer.
Branco, A., Rodrigues, J., Costa, F., Silva, J. and Vaz, R. (2014b). Assessing automatic text classification for interactive language learning. In International Conference on Information Society (i-Society 2014) (pp. 70-78). IEEE. https://doi.org/10.1109/i-Society34498.2014
Goldman, S. R. and Lee, C. D. (2014). Text complexity: State of the art and the conundrums it raises. The Elementary School Journal, 115(2), 290-300. https://doi.org/10.1086/678298
Feng, L., Jansche, M., Huenerfauth, M. and Elhadad, N. (2010, August). A comparison of features for automatic readability assessment. In Proceedings of the 23rd International Conference on Computational Linguistics: Posters (p. 276-284). https://aclanthology.org/C10-2032.pdf
Flesch, Rudolf (1979). “How to write in plain English: A book for lawyers and consumers”, New York, Harper.
Gunning, R. (1952). “The technique of clear writing”, McGraw-Hill, New York.
Leal, S. E., Scarton, C. E., Cunha, A., Hartmann, N. S., Duran, M. S. and Aluísio, S. M. (2021) NILC-Metrix Doc. NILC-Metrix. Acesso em 19 mai 2023. Disponível em
Leal, S. E., Duran, M. S., Scarton, C. E., Hartmann, N. S. and Aluísio, S. M. (2022). NILC-Metrix: assessing the complexity of written and spoken language in Brazilian Portuguese. arXiv preprint arXiv:2201.03445. https://doi.org/10.48550/arXiv.2201.03445 https://arxiv.org/abs/2201.03445
McNamara, D. S., Graesser, A. C., McCarthy, P. M. and Cai, Z. (2014). Automated evaluation of text and discourse with Coh-Metrix, Cambridge, Cambridge University Press.
Ponomarenko, G. L. and Evers, A. (2022). “Leiturabilidade e ensino: autores-base e seus trabalhos”, In Acessibilidade textual e terminológica, Edited by Maria José B. Finatto & Liana Braga Paraguassu, Uberlândia, Edufu, p. 41-71.
Santucci, V., Santarelli, F., Forti, L. and Spina, S. (2020). Automatic classification of text complexity. Applied Sciences, 10(20), 7285. https://doi.org/10.3390/app10207285
Sheehan, K. M., Flor, M. and Napolitano, D. (2013). A two-stage approach for generating unbiased estimates of text complexity. In Proceedings of the Workshop on Natural Language Processing for Improving Textual Accessibility (pp. 49-58). https://aclanthology.org/W13-1506.pdf
Štajner, S., Evans, R., Orasan, C. and Mitkov, R. (2012). What can readability measures really tell us about text complexity. In Proceedings of workshop on natural language processing for improving textual accessibility (p. 14-22). https://aclanthology.org/W13-15.pdf
Yasseri, T., Kornai, A. and Kertész, J. (2012). A practical approach to language complexity: a Wikipedia case study. PloS one, 7(11), e48386. https://doi.org/10.1371/journal.pone.0048386
Antonio, J. D. (2004). “Estrutura retórica e articulação de orações em narrativas orais e em narrativas escritas do português”. In Faculdade de Ciências e Letras: Doutorado. Universidade Estadual Paulista Júlio de Mesquita Filho.
Evers, A. (2018). “A redação engaiolada: padrões lexicais e ensino de redação em cursos pré-vestibulares populares”. In Instituto de Letras: Doutorado. Universidade Federal do Rio Grande do Sul. [link].
Branco, A., Rodrigues, J., Costa, F., Silva, J. and Vaz, R. (2014a). Rolling out Text Categorization for Language Learning Assessment Supported by Language Technology. In Computational Processing of the Portuguese Language: 11th International Conference, PROPOR 2014, Sao Carlos/SP, Brazil, October 6-8, 2014, Proceedings (Vol. 8775, p. 256). Springer.
Branco, A., Rodrigues, J., Costa, F., Silva, J. and Vaz, R. (2014b). Assessing automatic text classification for interactive language learning. In International Conference on Information Society (i-Society 2014) (pp. 70-78). IEEE. https://doi.org/10.1109/i-Society34498.2014
Goldman, S. R. and Lee, C. D. (2014). Text complexity: State of the art and the conundrums it raises. The Elementary School Journal, 115(2), 290-300. https://doi.org/10.1086/678298
Feng, L., Jansche, M., Huenerfauth, M. and Elhadad, N. (2010, August). A comparison of features for automatic readability assessment. In Proceedings of the 23rd International Conference on Computational Linguistics: Posters (p. 276-284). https://aclanthology.org/C10-2032.pdf
Flesch, Rudolf (1979). “How to write in plain English: A book for lawyers and consumers”, New York, Harper.
Gunning, R. (1952). “The technique of clear writing”, McGraw-Hill, New York.
Leal, S. E., Scarton, C. E., Cunha, A., Hartmann, N. S., Duran, M. S. and Aluísio, S. M. (2021) NILC-Metrix Doc. NILC-Metrix. Acesso em 19 mai 2023. Disponível em
Leal, S. E., Duran, M. S., Scarton, C. E., Hartmann, N. S. and Aluísio, S. M. (2022). NILC-Metrix: assessing the complexity of written and spoken language in Brazilian Portuguese. arXiv preprint arXiv:2201.03445. https://doi.org/10.48550/arXiv.2201.03445 https://arxiv.org/abs/2201.03445
McNamara, D. S., Graesser, A. C., McCarthy, P. M. and Cai, Z. (2014). Automated evaluation of text and discourse with Coh-Metrix, Cambridge, Cambridge University Press.
Ponomarenko, G. L. and Evers, A. (2022). “Leiturabilidade e ensino: autores-base e seus trabalhos”, In Acessibilidade textual e terminológica, Edited by Maria José B. Finatto & Liana Braga Paraguassu, Uberlândia, Edufu, p. 41-71.
Santucci, V., Santarelli, F., Forti, L. and Spina, S. (2020). Automatic classification of text complexity. Applied Sciences, 10(20), 7285. https://doi.org/10.3390/app10207285
Sheehan, K. M., Flor, M. and Napolitano, D. (2013). A two-stage approach for generating unbiased estimates of text complexity. In Proceedings of the Workshop on Natural Language Processing for Improving Textual Accessibility (pp. 49-58). https://aclanthology.org/W13-1506.pdf
Štajner, S., Evans, R., Orasan, C. and Mitkov, R. (2012). What can readability measures really tell us about text complexity. In Proceedings of workshop on natural language processing for improving textual accessibility (p. 14-22). https://aclanthology.org/W13-15.pdf
Yasseri, T., Kornai, A. and Kertész, J. (2012). A practical approach to language complexity: a Wikipedia case study. PloS one, 7(11), e48386. https://doi.org/10.1371/journal.pone.0048386
Published
2023-09-25
How to Cite
ANTONIO, Juliano Desiderato.
Textual complexity in oral narratives produced by informants with different levels of education. In: BRAZILIAN SYMPOSIUM IN INFORMATION AND HUMAN LANGUAGE TECHNOLOGY (STIL), 14. , 2023, Belo Horizonte/MG.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 258-267.
DOI: https://doi.org/10.5753/stil.2023.232701.
