Optimizing Components Selection in Blended Learning: Toward Sustainable Students Engagement and Success

Author:

Alammary Ali Saleh1ORCID

Affiliation:

1. College of Computing and Informatics, Saudi Electronic University, Jeddah 393453, Saudi Arabia

Abstract

Selecting the most appropriate components for a blended learning course is a multifaceted challenge influenced by various criteria. The impact of these influential criteria on the design process is not always obvious. The aim of this study is to assist academics in designing sustainable and engaging blended courses by investigating the impact of these criteria on the selection of blended learning components. By selecting the right mix of components, academics can foster a sustainable and meaningful involvement of students in their learning process over time, ensuring that students’ engagement is both enduring and beneficial in achieving academic success. A modified Delphi survey was utilized in this study, involving the participation of eighteen experts experienced in instructional design and online teaching. The analysis primarily relied on quantitative methods, utilizing the mean (to indicate central tendency) and standard deviation (to measure dispersion) for presenting the experts’ responses. Additionally, qualitative analysis of experts’ comments provided deeper insights into their quantitative ratings. Findings indicate that face-to-face collaborative activities should be the preferred method of delivery for academics aiming to enhance students’ engagement and foster their higher-order thinking skills, which students often find challenging. However, this approach is most effective when the group size is manageable. For larger student groups, online collaborative work can be a suitable alternative, provided there is ample online resource support. The results also indicate that online self-paced learning can be advantageous for lower-order thinking learning outcomes, particularly in situations where teaching staff is limited.

Publisher

MDPI AG

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