Boosting the L2 Learners’ Reading Comprehension Capability by Employing Nearpod Media

Author:

Mastura Amy,Dewi Silvi Listia,Misnar Misnar,Zuhra Intan,Misnawati Misnawati

Abstract

Objective: This study aimed to enhance L2 learners' reading comprehension by integrating Nearpod media into the teaching strategy at Universitas Almuslim. The main goal was to evaluate the effectiveness of this technology-based learning in boosting L2 reading comprehension. Method: A pre-experimental research design was employed in this study, in which the L2 learners at Universitas Almuslim were grouped without a control group for comparison. Pre-tests and post-tests were conducted using the Nearpod platform to assess the L2 learners' reading comprehension skills. The data acquired from the pre-test and post-test were quantitatively analyzed with SPSS Statistics Output to determine whether or not there was a significant difference when using the Nearpod media in class. Results: The outcomes revealed a significant difference in the L2 reading comprehension when exposed to Nearpod. It showed that the post-test reading comprehension mean score was higher than the pre-test mean score. Thus, the null hypothesis (Ho) was rejected, whereas the alternative hypothesis (Ha) was accepted. Novelty: By integrating technology into the classroom, this study contributes to the growing body of knowledge on effective strategies for language learning. The findings emphasize the potential of Nearpod media to engage and empower L2 learners, providing a novel and prospective option for boosting language teaching, particularly in reading comprehension.

Publisher

Indonesia Approach Education

Subject

General Medicine

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3