Contemporary American Literature in Distance Learning: Creating Reading Motivation and Student Engagement

Reading Research Quarterly, Journal Year: 2025, Volume and Issue: 60(2)

Published: Feb. 3, 2025

Abstract The effectiveness of distance learning primarily depends on the motivation and engagement students. aim this article is to determine whether developed online course enhances students' read their with contemporary American literature. methodology based an experimental design. A mixed‐methods approach was employed for data analysis, combining statistical analysis ( t ‐test) qualitative survey methods (pre‐ post‐testing). study conducted a sample 150 Chinese students from two universities (Leshan Normal University Wuhan Qingchuan University), who took “Contemporary Literature” September December 2022. pre‐and post‐testing indicate significant improvements across most parameters. For instance, reading efficiency, confidence in abilities, potential succeed tasks increased by 21.4%; “Challenge” dimension showed notable growth 17.2%; curiosity rose 16.7%; also 18.5%. This demonstrates that greater interest stories, particularly those related fantasy, mystery, adventure, formed deeper connection characters narratives. Most notably, avoidance decreased 16.7%, which positive outcome as it indicates reduced likelihood avoiding assignments. Given large size, critical ‐value approximately 1.96. Since all ‐values exceed value 1.96, null hypothesis rejected favor alternative each dimension. had statistically impact reading. practical significance these results underscores literature courses, utilizing interactive learning.

Language: Английский

A machine‐learning model of academic resilience in the times of the COVID‐19 pandemic: Evidence drawn from 79 countries/economies in the PISA 2022 mathematics study

British Journal of Educational Psychology, Journal Year: 2024, Volume and Issue: 94(4), P. 1224 - 1244

Published: Sept. 22, 2024

Abstract Background Given that students from socio‐economically disadvantaged family backgrounds are more likely to suffer low academic performance, there is an interest in identifying features of resilience, which may mitigate the relationship between socio‐economic status and performance. Aims This study sought combine machine learning explainable artificial intelligence (XAI) technique identify key resilience mathematics during COVID‐19. Materials Methods Based on PISA 2022 data 79 countries/economies, random forest model coupled with Shapley additive explanations (SHAP) value not only uncovered but also examined contributions each feature. Results Findings indicated 35 were identified classification academically resilient non‐academically students, largely validated previous framework. Notably, gender differences shown distribution some features. Research findings tended have a stable emotional state, high levels self‐efficacy, truancy positive future aspirations. Discussion has established research paradigm essentially methodological nature bridge gap psychological theories big field educational psychology. Conclusion To sum up, our shed light issues education equity quality global perspective times COVID‐19 pandemic.

Language: Английский