测验难度

  • 网络test difficulty
测验难度测验难度
  1. 条目分析结果:各分测验难度在0.46~0.54,大多数分测验的难度值大于0.5。

    Item analysis : The difficulty of sub-tests ranged from 0.46 to 0.54 , most sub-tests were over 0.5 .

  2. 结果:各分测验难度在0.38~0.60之间,总体难度是0.50,具有有效区分效度(0.20以上)的条目占85%以上。重测相关系数为0.79,总分α系数为0.80。考试的难度合适;

    Results : The difficulty of sub-tests ranged from 0.38 to 0.60 , while the average difficulty of the whole scale was 0.50 . The discrimination of 85 % items was over 0.2.Reliability and Validity meets the criteria of psychometrics .

  3. 他的测验的难度使班上半数学生都没有通过。

    The ruggedness of his exams caused half the class to fail .

  4. 这一研究结果证明,利用人工神经网络模型对语言测验的题目难度等参数进行预测是可行的,后续的研究应该将重点放在进一步提高人工神经网络预测的准确性方面。

    The study results show that using of artificial neural network model to predict the difficulty parameters is feasible . Follow-up studies should focus on improving the accuracy of artificial neural network further .

  5. 通过对瑞文测验项目的难度影响因素进:行分析,在原因素测量模型的基础上,提出新的因素测量模型,用实际的调查数据检验该模型。

    The factors of Raven test is conducted analysis , and a new measurement model of the factors structure is put forward on the basis of the original measurement model , and is verified by the actual survey data .

  6. 分测验二的项目难度分布比较合理,多数项目鉴别力较高,而分测验一的项目难度分布和项目鉴别力则有待于在今后的研究中进一步提高。

    The item difficulty distribution and the discrimination of the subtest 2 are good , but the item difficulty distribution and the discrimination of the subtest 1 should be improved in further studies .

  7. 60,与学业能力倾向测验相关.中学数学学习能力测验难度设计的理论与实践

    60 . The correlations between subscales or full scale and academic aptitude test were from . Difficulty Design for the Middle School Maths Aptitude Test : Theory to Practice

  8. 研究者设计项目结构编制矩阵测验,通过认知模型与编制矩阵测验项目的难度建立的数学模型,来验证认知模型为矩阵问题的自适应项目生成服务。

    The researcher has designed item structures to develop matrices , and has built mathematical models with the cognitive models and the item difficult to verify the cognitive models for adaptive item generation .