自主学习投入度实时分析方法及应用研究

发布时间：2018-07-08 15:04

本文选题：在线学习 + 在线学习行为　；参考：《电化教育研究》2017年10期

【摘要】：在线学习者学习投入度是影响在线学习效果、满意度和质量的重要因素,是远程教育和在线教育领域研究的热点之一。文章针对在线学习中的独立自主学习,根据x API标准所提出的在线学习活动,确定当前能反应独立自主学习活动的三类数据——教学视频播放行为数据、视频观看时长和并发学习行为数据,提出在线学习投入度算法,实现了对自主学习投入度的实时观察及计算。基于提出的自主学习投入度算法,对1万多在线学习者真实的在线学习行为数据进行挖掘和分析,主要研究结论包括:(1)实时了解和监控自主学习过程中群体和个体投入情况的特点,可以促使学习者准确知晓并自我调整学习状态,实现教学方的有效监控;(2)通过分析投入度数据,能够挖掘一些难以直接观察到的在线自主学习规律和特点;(3)有必要动态分析视频学习材料的学习投入度情况,从而辨析视频学习材料的有效性和可行性,这能为视频学习材料的设计、制作、调整和修改提供数据支持和依据,避免设计制作的盲目性和主观性。
[Abstract]:The degree of learning commitment of online learners is an important factor that affects the effect, satisfaction and quality of online learning, and it is one of the hotspots in the field of distance education and online education. Aiming at the independent learning in online learning, according to the online learning activities proposed by the x API standard, this paper determines three kinds of data which can reflect the independent learning activities at present-teaching video playing behavior data. Based on the data of video viewing time and concurrent learning behavior, an online learning input algorithm is proposed to realize the real-time observation and calculation of the investment degree of autonomous learning. Based on the proposed autonomous learning investment algorithm, the real online learning behavior data of more than 10,000 online learners are mined and analyzed. The main conclusions are as follows: (1) understanding and monitoring the characteristics of group and individual input in the process of autonomous learning in real time can promote learners to know and self-adjust their learning state accurately. (2) by analyzing the input data, we can mine some online autonomous learning rules and characteristics that are difficult to observe directly; (3) it is necessary to dynamically analyze the learning input of video learning materials. Thus, the validity and feasibility of video learning materials are analyzed, which can provide data support and basis for the design, production, adjustment and modification of video learning materials, and avoid blindness and subjectivity of design and production.
【作者单位】：华南师范大学教育信息技术学院;华南师范大学现代远程教育研究所;
【基金】：国家自然科学基金项目“移动学习行为感知下教育资源语义组织与存储优化研究”(项目编号:61370178) 广东省研究生教育创新计划项目“全日制教育硕士优秀教学案例资源库系统建设的研究与实现”(项目编号:C1087109)
【分类号】：G434

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