通过交互式移动和自适应学习平台提高教育设计能力:实证研究

Jie Li, Qian Li
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引用次数: 0

摘要

随着教育技术的不断进步,交互式移动和自适应学习平台在教育领域发挥着越来越重要的作用。这一点在培养教育专业学生的教育设计能力方面尤为明显,因为这些平台展示了其独特的价值。教育设计能力是教育专业学生的一项重要技能,直接关系到未来教学活动的设计和实施质量。传统的教育方法往往不能充分考虑学生的个体差异,导致个性化能力培养不足。本研究旨在通过互动、移动、自适应学习平台,探索并实现教育专业学生教育设计能力的精准培养。本文首先回顾了目前应用交互式移动和自适应学习平台培养教育设计能力的情况。它强调了现有研究方法中与个性化匹配和推荐系统设计相关的不足之处。针对这些不足,本研究提出了一套新的自适应匹配方法。这些方法包括基于竞争优势思维的能力特征识别、个人实力模型的构建、匹配计算,以及使用投影决策法和匈牙利法优化决策方案。此外,该研究还设计了一种基于明确评级的学习项目推荐算法,以提高学习项目推荐的准确性和个性化。这些方法的应用不仅提高了教育专业学生的教育设计能力,也为交互式、移动式和自适应学习平台的开发提供了新的理论支持和实践指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing Educational Design Capabilities through Interactive Mobile and Adaptive Learning Platforms: An Empirical Study
With the continuous advancement of educational technology, interactive mobile and adaptive learning platforms are playing an increasingly important role in the field of education. This is particularly evident in the development of educational design skills among education students, as these platforms showcase their unique value. Educational design capability is a crucial skill for education students, directly related to the quality of designing and implementing future teaching activities. Traditional methods of education often fail to fully consider individual student differences, resulting in inadequate cultivation of personalized capabilities. This study aims to explore and achieve precise cultivation of educational design capabilities in education students through interactive, mobile, and adaptive learning platforms. This paper first reviews the current application of interactive mobile and adaptive learning platforms to cultivate educational design capabilities. It highlights deficiencies in existing research methods related to personalized matching and recommendation system design. To address these deficiencies, this study proposes a new set of adaptive matching methods. These methods include capability characteristic recognition based on competitive advantage thinking, the construction of individual strength models, as well as matching calculation, and decision- making scheme optimization using the projection decision method and the Hungarian method. Additionally, the study designs a learning project recommendation algorithm based on explicit ratings to enhance the accuracy and personalization of learning project recommendations. The application of these methods not only enhances the educational design capabilities of education students but also provides new theoretical support and practical guidance for the development of interactive, mobile, and adaptive learning platforms.
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