Universidad de Guayaquil
Catálogo Bibliográfico

Classifying Vocabulary into Parts of Speech to Improve Reading Comprehension

Por: Colaborador(es): Tipo de material: TextoTextoIdioma: Español Detalles de publicación: Universidad Casa Grande. Departamento de Posgrado, 2019Descripción: 80 p.; DigitalTema(s): Clasificación CDD:
  • POS 2019
Recursos en línea: Resumen: This research aimed to find out whether parts of speech classification can improve students’ reading comprehension in a private language school in Loja. A mixed-method design was used to gather quantitative and qualitative data. A pre-test and a post-test were used to measure students reading comprehension and to record the number of words classified according to parts of speech. Results demonstrated that there was an increase of classified words on the posttest compared with the pretest. Cohen’s d was calculated and the result obtained was 0.22 (medium effect size). Furthermore, there was an improvement in the reading comprehension results with an increase of 1.83 points in the means of the pretest and the posttest scores. Additionally, students’ perspectives towards reading comprehension were measured with a pre and a post survey through a Likert scale. Results revealed that participants changed positively after the intervention. Consequently, it was demonstrated that classifying parts of speech is an effective technique for students to improve reading comprehension. These findings have significant implications for both English teachers and learners in the academic field, particularly to those who want to improve reading comprehension.
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Tipo de ítem Biblioteca actual Colección Signatura topográfica Estado Notas Fecha de vencimiento Código de barras
Tesis Tesis Biblioteca Tesis Tesis CD UCG Tesis 2104 RUIc POS 2019 (Navegar estantería(Abre debajo)) Disponible mmejia Tesis2104

2019

This research aimed to find out whether parts of speech classification can improve students’ reading comprehension in a private language school in Loja. A mixed-method design was used to gather quantitative and qualitative data. A pre-test and a post-test were used to measure students reading comprehension and to record the number of words classified according to parts of speech. Results demonstrated that there was an increase of classified words on the posttest compared with the pretest. Cohen’s d was calculated and the result obtained was 0.22 (medium effect size). Furthermore, there was an improvement in the reading comprehension results with an increase of 1.83 points in the means of the pretest and the posttest scores. Additionally, students’ perspectives towards reading comprehension were measured with a pre and a post survey through a Likert scale. Results revealed that participants changed positively after the intervention. Consequently, it was demonstrated that classifying parts of speech is an effective technique for students to improve reading comprehension. These findings have significant implications for both English teachers and learners in the academic field, particularly to those who want to improve reading comprehension.

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