Student-centered learning in the digital age: in-class adaptive instruction and best practices

Daniel Ginting, Delli Sabudu, Yusawinur Barella, Ahmad Madkur, Ross Woods, Mezia Kemala Sari
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Abstract

Adaptive instruction is a promising solution to the limitations of traditional classroom instruction, which assumes that all students learn in the same way and at the same pace. Adaptive instruction tailors the learning experience to each student’s needs and abilities. Several adaptive instruction tools and platforms exist, including intelligent tutoring systems, learning management systems, mobile apps, AI chatbots, and adaptive machine-learning programs. The Adaptive Instruction of Student Control Theoretical Framework suggests that allowing students to control their use of learning resources leads to better learning outcomes. Implementing adaptive instruction in higher education can be difficult due to faculty buy-in, technical infrastructure, and student motivation. Effective instructional design is crucial for adaptive instruction to support student control and maximize benefits. Overall, instructors must pay attention to student motivation and work to create learning environments that foster motivation, autonomy, and engagement to implement adaptive instruction successfully.
数字时代以学生为中心的学习:课内自适应教学与最佳实践
传统课堂教学假定所有学生都以同样的方式、同样的进度学习,而适应性教学则是解决这一局限性的一个很有前途的办法。自适应教学根据每个学生的需求和能力定制学习体验。目前已有多种自适应教学工具和平台,包括智能辅导系统、学习管理系统、移动应用程序、人工智能聊天机器人和自适应机器学习程序。学生控制自适应教学理论框架认为,允许学生控制自己对学习资源的使用会带来更好的学习效果。由于教师的认同、技术基础设施和学生的积极性等原因,在高等教育中实施自适应教学可能比较困难。有效的教学设计对于自适应教学支持学生控制和最大限度地提高效益至关重要。总之,教师必须关注学生的学习动机,努力创造能够促进学习动机、自主性和参与性的学习环境,以成功实施自适应教学。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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