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出 处:《现代计算机》2016年第12期45-49,共5页Modern Computer
基 金:2015年度江苏省高等教育教改立项研究课题(No.2015JSJG375);全国旅游职业教育教学指导委员会2015年科研项目立项课题(No.LZW201505);全国旅游职业教育教学指导委员会2015年科研项目(No.LZW201503)
摘 要:教学质量评价是高校教育教学决策的重要依据,而有效的教学质量评价依赖于全面、可靠的评价数据。教学质量多元评价体系是指采用多种有效的技术手段和评价方法,在非结构化的教学情境中评价教师教学过程和效果的一系列方法,以现代质量管理理论,进行多元评价内容与方式等方面的制度安排,并由多元评价主体来加以实施。大数据重在对大量数据进行多维、深度挖掘与科学分析,发现数据背后的隐含关系与价值,有助于教学质量评价从基于小样本数据或片段化信息的推测,转向基于全方位、全程化数据的证据性决策。运用数据挖掘技术对多元评价结果进行分析,有助于提高教学质量评价的信度和效度,减少评价过程中的张力与冲突。The evaluation of teaching quality is an important basis for colleges and universities to make decisions on education and teaching, and its effectiveness depends on the comprehensive and reliable data for evaluation. The pluralistic evaluation system of teaching quality refers to a series of methods to evaluate teachers' teaching process and effect with various effective techniques and methods in unstructured teach- ing situations. The system, based on the modern quality management theory, arranges content, methods and other aspects of the pluralistic evaluation, and carries it out by the pluralistic evaluator. With multi-dimensional and profound mining and scientific analysis on a large number of data, big data can discover the hidden relationship and value behind, thus promoting the evaluation of teaching quality to turn from the conjecture based on data of small samples or fragmented information to the evidence-based decision making on the comprehensive and whole-process data. An analysis on the results of pluralistic evaluation with data mining technology can help enhance the reliability and validity of the evaluation of teaching quality, and therefore reduce the tension and conflict in the process of evaluation.
分 类 号:G712[文化科学—职业技术教育学] TP311.13[文化科学—教育学]
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