混合学习教学法及其在高等教育中的实施:孟加拉国视角

Shrabonti Mitra, MD. Abdul Malek, Tanzin Sultana, Abhijit Pathak, Md. Jainal Abedin, Khadizatul Kobra, Md. Habib Ullah, Mayeen Uddin Khandaker
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引用次数: 0

摘要

本文回顾了全球高等教育混合学习的理论基础和组成部分,分析了2016年1月至2020年12月期间来自五个国家发表的六篇文章。该研究确定了教师面临的挑战,包括工作量、及时性、缺乏管理BL的学术和技术技能。平衡面对面和在线学习也很有挑战性。为了解决这些问题,强调了工作人员培训、支持和联网的重要性,提出了一种改进的孟加拉国高等教育BL模式,可在大流行后使用机器学习方法实施。混合BL模型被推荐给孟加拉国的机构,利用机器学习算法通过技术应用促进基于结果的学习。对孟加拉国BGC信托大学的120名学生进行了初步调查,使用从机器学习算法中获得的统计数据来探索混合学习方法的适用性。事实证明,机器学习有利于数据分析,为寻求结合技术的有效教学策略的教育工作者和政策制定者提供了有价值的见解。这项研究强调了机器学习在进行调查和分析高等教育混合学习相关数据方面的潜力,为该领域做出了重大贡献。
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Blended learning pedagogy and its implementation in the tertiary education: Bangladesh perspectives
This paper reviews the theoretical foundations and components of blended learning (BL) in higher education globally, analyzing six articles from five countries published between January 2016 and December 2020. The study identified challenges faced by instructors, including workload, timeliness, and lack of academic and technical skills to manage BL. Balancing face-to-face and online learning was also challenging. To address these issues, the importance of staff training, support, and networking was emphasized, proposing a modified BL model for tertiary education in Bangladesh, which could be implemented post-pandemic using a machine-learning approach. The mixed BL model was recommended for Bangladeshi institutions, utilizing machine learning algorithms to facilitate outcome-based learning through technological applications. A preliminary survey of 120 students from BGC Trust University in Bangladesh was conducted using statistical data obtained from machine learning algorithms to explore the applicability of the mixed-learning approach. Machine learning proved beneficial for data analysis, drawing valuable insights for educators and policymakers seeking effective teaching strategies that incorporate technology. This research underscores the potential of machine learning in conducting surveys and analyzing data related to blended learning in tertiary education, offering significant contributions to the field.
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