MOOC 学习行为影响因素研究

Research on Factors Affecting the MOOC Learning Behavior

近几年，国内外MOOC 快速发展，然而学习中断现象严重。虽然一门MOOC 的注册人数动辄几 千，甚至上万，但真正完成学习并获得结业证书的人数非常少。关于MOOC 学习行为影响因素的研究目前较少。 本研究基于TAM3 模型建立了MOOC 学习行为影响因素模型，并进行实证研究。本课题通过网络和面对面相结 合的方式发放问卷。网络问卷使用问卷星发放，对清华大学的在校生面对面发放，并使用SPSS17. 0、AMOS21. 0 等工具对调查数据进行分析，包括信效度检验、路径图分析、变量间总效应计算等。研究表明:学习者MOOC 学 习意向与学习行为之间呈显著正相关;主观规范和有用性感知与学习意向呈显著正相关;易用性感知与学习意 向呈正相关，但不显著;主观规范、地位、学习适用性、学习绩效与有用性感知呈显著正相关;结果展示性与有用 性感知呈正相关但不显著;计算机自我效能感、娱乐性感知、客观使用与易用性感知呈显著正相关;外部支持、计 算机偏好与易用性感知呈正相关但不显著;计算机焦虑与易用性感知呈负相关但不显著。在所有原始变量中 (不包括有用性感知和易用性感知)，主观规范对学习意向的影响效应最大。对有用性感知影响最大的变量是 学习绩效感知，对易用性感知影响最大的是学习者计算机自我效能感。研究还发现，计算机焦虑对易用性感知 的影响被MOOC 使用经验显著调节。研究建议加大MOOC 宣传力度、鼓励学习者参与、采取一定的管理措施等 对策，改善学习者MOOC 学习行为，提升MOOC 的学习效率和效果。

Nowadays， MOOC ( Massive Open Online Course) is developing rapidly. However， the effect of MOOC study needs improving. According to related statistics， the course completion rate on Coursera platform is only 7% - 9% . The data Jordan (2013) obtained from investigating some major platforms shows that although the passing rates of some MOOCscan reach 40% ， those of most MOOCs are below 10% . Venkatesh (2008) puts forward a TAM3 model by combining TAM2 and perceived ease of use model. The TAM3 model has many advantages including its comprehensiveness and operability. Based on TAM3 model， this paper conducted an empirical research and built an MOOC learning behavior influencing factors model. We designed and administrated a questionnaire through both face -to-face and the Internet network. As a result， a total of 325 effective questionnaires are returned. The data was or ganized and analyzed using SPSS17. 0 and AMOS 21. 0 as statistical tools. The result shows that the intention of learning MOOC has a significant positive correlation with MOOC learning behavior. Subjective norm and perceived usefulness have significant positive correlations with MOOC behavior intention. Perceived ease of use has a positive cor relation with MOOC behavior intension， but the correlation is not significant. The perceived usefulness has the highest positive correlation with MOOC behavior intention (regression coefficient is 0. 444)， and followed by subjective norm and perceived ease of use. The subjective norm， image，job relevance and output quality have significant positive corre lations with MOOC perceived useless. Output quality have the highest positive correlation with perceived usefulness(re gression coefficient is 0. 413) and followed by subjective norm，study relevance，image，result demonstrability and per ceived ease of use in turn depending on the regression coefficient size. Computer self-efficacy，perceptions of external control，perceived enjoyment and objective usability all have significant positive correlations with MOOC perceived ease of use. Computer anxiety has a negative correlation with perceived ease of use， but not at a significant degree. Com puter playfulness has a positive correlation with perceived ease of use， but not significantly . Computer self -efficacy have a high positive correlation with perceived ease of use (regression coefficient is 0. 191)， followed by perceived en joyment，objective usability perceptions of external control and computer playfulness in turn depending on the regression coefficient size. Subjective norm has a significant positive correlation with image. We concluded that EXP has a signif icant regulating effect on the path PEOU<---CANX( |CR>1. 96). The model has good explanation powers for re lated variables. Finally， some countermeasures are discussed， such as vigorously advertising MOOC， encouraging participation of MOOC，taking effective management strategies.