富数据环境中的自我损耗:大学生学业焦虑的发生机制

Self-depletion in Data-rich Environments:The Mechanism of College Students'Academic Anxiety

随着学习分析技术的发展和成熟,越来越多的教育产品应运而生。面对富数据环境,学习者很难适应甚至利用数据实现自我提高。在此过程中可能由于过分关注数据容易导致心理资源消耗进入自我损耗状态,进而产生学业焦虑。为了明确学业焦虑的产生和发展,提高学习效率,促进学生全面发展,采用扎根理论的研究方法,基于自我损耗理论,依托学习分析仪表盘的使用过程对某课程中大学生焦虑人群进行访谈,利用NVivo软件整理、分析访谈内容,进而分析学业焦虑的发生过程,探究大学生学业焦虑的发生机制。结果表明,理想表现和实际表现的落差和同伴之间的对比是引发学业焦虑的关键,焦虑后的行为和焦虑水平双向影响,学习者焦虑水平也受仪表盘的使用体验影响。

With the development and maturity of learning analysis technology,more and more educational products have been applied.In the face of a data-rich environment,it is difficult for learners to adapt or even use data to achieve self-improvement.In this process,excessive attention to data may easily lead to psychological resource consumption into a state of self-depletion,resulting in academic anxiety.In order to clarify the generation and development of academic anxiety,improve learning efficiency,and promote the all-round development of students,this study adopts a research method of grounded theory,based on self-depletion theory,relying on the use process of learning analysis dashboard to interview college students'anxiety groups in a course,using NVivo software to sort out and analyze the interview content to analyze the occurrence process of academic anxiety,and explore the mechanism of college students'academic anxiety.The results show that the gap between ideal performance and actual performance and the contrast between peers are the key to causing academic anxiety.Bidirectional effects of post-anxiety behavior and anxiety levels;Learner anxiety levels are also affected by the experience of using the dashboard.