基于微信公众平台的移动微型学习实证研究———以“ 数据结构公众平台”为例

Mobile Micro-learning Research Based on the WeChat Public Platform:A Case Study of a “ Data Structure” Course

随着近年来移动技术和网络环境的不断优化，新型的移动终端将成为未来微型学习的有效支撑。然而，如何将移动终端应用于实际的微型学习，仍存在诸多问题有待解决。为了探索移动终端上的有效学习模式，本研究依托微信公众平台，创建了“数据结构”课程学习公众号，面向598名关注用户，采用内容分析与问卷调查相结合的方法，分别从学习者的基本特征、学习内容、学习行为、学习效果四个方面进行统计与分析。研究结果表明，微信公众平台在吸引学习者、传播微内容、推进个性化学习与实时效果评估等方面有积极的促进作用，同时也发现微信用户的地域分布、网络环境、知识结构和学习需求存在显著差异，学习资源转换率偏低，学习者之间交流不畅，学习行为可控性较弱等。为此本研究建议:以专业知识的社会化普及为目标，注重以“微信用户”为核心的教学设计;加强推送频率与媒介形式并重的资源建设;创建微信技术多元支持下的学习情境;以及融入情感与认知因素的学习支持服务以使微信用户获得更佳的学习效果，提升移动微型学习的社会效益。

With the development of mobile Internet technology， micro-learning based on novel mobile terminals has become complementary to informal learning in recent years. The WeChat public platform， the micro message account service produced by Tencent Inc on August 23， 2012， can support organizations or individuals to create mobile course， edit materials， share information and interact with all the users. For mobile micro-learning， however， it is a complete learning process including not only the resources for communication but also the learning mode， the learning activity， the learning interaction and the support services. Therefore， there are still many issues to be addressed during the application process. In order to discover the learning model of micro-learning， we present a case study of the “Data Structure” (DS) course which is based on the WeChat public platform. Before this study， the DS course used the Moodle platform and had accumulated more than six years of course construction and application. It also won the national quality courses ( Network Education) award in 2010. As a supplement of online learning， we designed and built 32 learning materials in different formats on DS WeChat micro course. These learning materials are in the mixture format with graphics， textures or videos. After nearly four months of operation， we have collected the data of 598 users， and analyzed their learning needs， learning behaviors and learning effect by using content analysis and questionnaire survey. The results confirm that the WeChat public platform plays a positive role in attracting new learners， communicating micro learning content， promoting individual learning and real -time effect evaluation. On the other hand， the findings also show that the WeChat users are extremely dispersed. There are 38. 69% users coming from the first-tier cities such as Beijing， Shanghai and Guangzhou， and more than 50% users are in the other 25 cities of China. For this reason， many of them substantially differ in the knowledge background， network environment and learning needs. Besides， they have low learning participation and too much randomness of learning behavior. According to the statistics in this study， after learning materials have been published， the average resource conversion rate is less than 27% in the first seven days. Furthermore， only 9. 53% of users are giving feedback on questions or evaluations， and 11. 7% of users are choosing to drop out by the end of this study. Because of the technical limitations， the users won't be allowed to make conversation with other users by the WeChat public platform if they need help from peers. The WeChat public platform can only provide the conditions to have communication between the users and the managers. In order to improve the situation， we suggest circulating the professional knowledge as the target， paying attention to the WeChat users-centered pedagogical design， enriching the types of learning resources， increasing the frequency of material updating， enhancing the support of multiple WeChat learning technology， strengthening the learning support services which include cognitive and emotional elements and so on. It is reasonable to believe that the WeChat users will get better leverage by learning the mobile course as listed above. The mobile micro-learning based on the WeChat platform， meanwhile， will also gain the broader recognition and social influence.