Genre-based writing and the progression of textual competence in basiceducation middle grades
DOI:
https://doi.org/10.64747/q4ewz489Keywords:
genre‑based writing, textual progression, NLP metrics, large‑scale assessment (SEST), middle basic educationAbstract
This study examined the genre‑based progression of writing competence from 5th to 7th grades of Ecuador’s Basic Education across contrasting settings: Guayas (coastal, more urban) and Chimborazo/Cotopaxi (Andean, more rural/indigenous). We employed an explanatory sequential mixed‑methods design (QUAN→qual) combining: (i) primary sampling of authentic student texts in four school genres (narrative, news report, description, procedural/instruction), scored with analytic rubrics (α/κ ≥ 0.70; metric invariance across provinces); (ii) extraction of NLP metrics (lexical density, T‑unit length, referential cohesion, connectives); and (iii) linkage with open data (SEST‑INEVAL grade‑7 scores; AMIE; H3/OSM/WorldPop/VIIRS). Analyses included multilevel models (student–section–school), Genre Progression Index (GPI) estimates, and school‑level correlations with SEST. Findings indicate a substantive 5th→7th progression that varies by genre, with steeper gradients in news and procedural writing. Guayas shows a relative advantage in news (higher GPI and grade slope), tied to improvements in inverted‑pyramid structure, lead quality, and source use; the Andean sample displays qualitative strengths in register and audience alignment. NLP metrics partially mediate the grade effect (indirect β ≈ 0.06), adding sensitivity to textual complexity. At the school level, news writing (grade‑7) is the strongest predictor of SEST Language & Literature (β ≈ 0.31), followed by procedural writing (β ≈ 0.24). Robustness held under design weights, multiple imputation, and alternative specifications. We conclude that genre‑based instruction—making macrostructure and cohesion explicit through mentor texts and formative feedback—accelerates writing development. We recommend hybrid sequences (deconstruction→joint writing→independent writing), emphasis on news/procedural genres, and low‑cost kits (templates and open rubrics) prioritizing rural and EIB contexts. The open‑data package (anonymized microdata, scripts, JSON‑LD metadata) enables replication, auditing, and responsible scaling
References
Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), 1–48. https://doi.org/10.18637/jss.v067.i01
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B, 57(1), 289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
Biber, D., Gray, B., & Poonpon, K. (2011). Should we use characteristics of conversation to measure grammatical complexity in L2 writing? TESOL Quarterly, 45(1), 5–35. https://doi.org/10.5054/tq.2011.244483
Bürkner, P.-C. (2017). brms: An R package for Bayesian multilevel models using Stan. Journal of Statistical Software, 80(1), 1–28. https://doi.org/10.18637/jss.v080.i01
Crossley, S. A., Kyle, K., & McNamara, D. S. (2016). The development and use of cohesive devices in L2 writing and their relations to judgments of essay quality. Journal of Second Language Writing, 32, 1–16. https://doi.org/10.1016/j.jslw.2016.01.003
Graham, S., & Perin, D. (2007). A meta-analysis of writing instruction for adolescent students. Journal of Educational Psychology, 99(3), 445–476. https://doi.org/10.1037/0022-0663.99.3.445
Graesser, A. C., McNamara, D. S., Louwerse, M. M., & Cai, Z. (2004). Coh-Metrix: Analysis of text on cohesion and language. Behavior Research Methods, Instruments, & Computers, 36(2), 193–202. https://doi.org/10.3758/BF03195564
Halliday, M. A. K., & Matthiessen, C. (2014). Halliday’s introduction to functional grammar (4th ed.). Routledge. https://doi.org/10.4324/9780203431269
Hidalgo, M. A. Á., Varela, J., Terán‑Mendoza, O., & Rodríguez‑Rivas, M. E. (2025). Desempeño lector y equidad en la Educación Básica Superior: Análisis multinivel con datos administrativos. Horizonte Científico International Journal, 3(2), 1–14. https://doi.org/10.64747/cq73z358
Hyland, K. (2007). Genre pedagogy: Language, literacy and L2 writing instruction. Journal of Second Language Writing, 16(3), 148–164. https://doi.org/10.1016/j.jslw.2007.07.005
Kyle, K., & Crossley, S. A. (2015). Automatically assessing lexical sophistication: Indices, tools, findings, and application. Behavior Research Methods, 47(2), 540–559. https://doi.org/10.3758/s13428-014-0488-0
Kuznetsova, A., Brockhoff, P. B., & Christensen, R. H. B. (2017). lmerTest package: Tests in linear mixed effects models. Journal of Statistical Software, 82(13), 1–26. https://doi.org/10.18637/jss.v082.i13
Lu, X. (2010). Automatic analysis of syntactic complexity in second language writing. International Journal of Corpus Linguistics, 15(4), 474–496. https://doi.org/10.1075/ijcl.15.4.02lu
Martin, J. R., & Rose, D. (2012). Learning to write, reading to learn: Genre, knowledge and pedagogy in the Sydney School. Equinox. https://doi.org/10.1558/equinox.23758
McCarthy, P. M., & Jarvis, S. (2010). MTLD, vocd-D, and HD-D: A validation study of sophisticated approaches to lexical diversity assessment. Behavior Research Methods, 42(2), 381–392. https://doi.org/10.3758/BRM.42.2.381
Nation, K. (2017). Nurturing a lexical legacy: Reading experience is critical for the development of word reading skill. NPJ Science of Learning, 2, 3. https://doi.org/10.1038/s41539-017-0004-7
Perfetti, C., & Stafura, J. (2022). Reading ability: Lexical quality to comprehension—Revisited. Scientific Studies of Reading, 26(Suppl. 1), 3–23. https://doi.org/10.1080/10888438.2022.2057000
Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. https://doi.org/10.18637/jss.v048.i02
Schleppegrell, M. J. (2004). The language of schooling: A functional linguistics perspective. Lawrence Erlbaum. https://doi.org/10.4324/9781410610317
Suggate, S. P. (2016). A meta-analysis of the long-term effects of phonemic awareness, phonics, fluency, and reading comprehension interventions. Journal of Learning Disabilities, 49(1), 77–96. https://doi.org/10.1177/0022219414528540
van Buuren, S., & Groothuis‑Oudshoorn, K. (2011). mice: Multivariate imputation by chained equations in R. Journal of Statistical Software, 45(3), 1–67. https://doi.org/10.18637/jss.v045.i03
Vera Chávez, S. L., Cando Cañizares, G. de L., Bedoya Navas, M. G., & Uquillas Vega, S. M. (2025). Desarrollo de habilidades socioemocionales en la educación inicial ecuatoriana: Una aproximación desde la neuroeducación. Horizonte Científico International Journal, 3(2), 1–13. https://doi.org/10.64747/xmeafg82
Weiss, D. J., Nelson, A., Gibson, H. S., Temperley, W., Peedell, S., Lieber, A., Hancher, M., Poyart, E., Belchior, S., Fullman, N., Mappin, B., Dalrymple, U., Rozier, J., Lucas, T. C. D., Howes, R. E., Tusting, L. S., Kang, S. Y., Cameron, E., Bisanzio, D., … Gething, P. W. (2018). A global map of travel time to cities to assess inequalities in accessibility in 2015. Nature, 553(7688), 333–336. https://doi.org/10.1038/nature25181
Wilkinson, M. D., Dumontier, I., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., … Mons, B. (2016). The FAIR guiding principles for scientific data management and stewardship. Scientific Data, 3, 160018. https://doi.org/10.1038/sdata.2016.18
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Fernando Alexi Vinueza Echeverría, Nancy Cecilia Loarte Valle, Carmen Nelly Loarte Valle, Marcia Lucía Delgado Yépez (Autor/a)
This work is licensed under a Creative Commons Attribution 4.0 International License.
