Effects of Differential Item Discriminations between Individual-Level and Cluster-Level under the Multilevel Item Response Theory Model

This study attempted to interpret differential item discriminations between individual and cluster levels by focusing on patterns and magnitudes of item discriminations under 2PL multilevel IRT model through a set of variety simulation conditions. The consistency between the mean of individual-level ability estimates and cluster-level ability estimates was evaluated by the correlations between them. As a result, it was found that they were highly correlated if the patterns of item discriminations were the same for both individual and cluster levels. The magnitudes of item discriminations themselves did not affect much on correlations, as far as the patterns were the same at the two levels. However, it was found that the correlation became lower when the patterns of item discriminations were different between the individual and cluster levels. Also, it was revealed that the mean of the estimated individual-level abilities would not be necessarily a good representation of the cluster-level ability, if the patterns were different at the two levels.

How to Write and Assess M/C Tests Paper Based on the Theory of Item Analysis

M/C test is always an essential means of testing for language teachers.However,we have every reason to doubt whether a randomly designed M/C test could effectively reflect the testees' language standard.In most language testing,before the actual writing of a test paper,we should first analyze the items to see whether they're good or qualified enough to be put into the test paper or to be included in the item bank for further use because it is only through item analysis that we can make the test paper more scientific.Based on this theory,there 're some principles we should follow when writing or assessing M/C tests.

Guided Waves Mode Discrimination in Pipes NDT Based on the Matching Pursuit Method

Ultrasonic guided wave have the multi-modes and dispersive characteristics, and its modes are easy to be converted at boundary or when running into defects in pipes, which makes the discrimination of different guided waves modes of the reflection signals in pipes NDT very hard. In this work, firstly, the experiments are carried out to test two kinds of stainless steel pipes by applying guided waves NDT, one is integrated pipe and another is non-integrated pipe with a small hole defect, and the detected guided waves echo signals are respectively obtained. Secondly, the measured signals are processed by matching pursuit method and the Chirplet matching atom parameters are calculated. By calculating the time-frequency distributions spectrum of detected guided waves echo signals, torsional, flexural and longitudinal guided waves modes are identified from the intact pipe, and the two wave-packets with torsional and flexural guided waves modes are also identified from the pipe with hole defect. The results showed that the matching pursuit method has a tremendous advantage to identify different guided waves modes in pipes nondestructive testing.

Reducing Item Exposure in Computerized Adaptive Testing Systems Using Automatic Item Generation

This paper studies the technics of reducing item exposure by utilizing automatic item generation methods. Known test item calibration method uses item parameter estimation with the statistical data, collected during examinees prior testing. Disadvantage of the mentioned item calibration method is the item exposure; when test items become familiar to the examinees. To reduce the item exposure, automatic item generation method is used, where item models are being constructed based on already calibrated test items without losing already estimated item parameters. A technic of item model extraction method from the already calibrated and therefore exposed test items described, which can be used by the test item development specialists to integrate automatic item generation principles with the existing testing applications.

A Test Items Knowledge Library System for Adaptive Learning

A test items knowledge library system of for adaptive learning is proposed in this paper. The first step is to carry out the quantity and quality analysis of the test items by using the Bloom＇s revised taxonomy and scale anchoring respectively to produce the characteristics for test items. A smoothing method of arbitrary anchoring revised from scale anchoring is first proposed to make tests more accurate in distinguishing test levels. In addition, raised three dimensional indicators based on the Bloom＇s revised taxonomy are adopted to validate test contents and therefore it concretely describes the examining function of items. The items obtained have the precise and concrete properties; an item knowledge library is therefore constructed combining teaching materials and items using the technologies of ontology and knowledge management. Finally, a knowledge library system of test items is established to achieve the purpose of adaptive learning for learners.

A Study on College English Test Construction and Evaluation

Testing is a universal feature of social life.Throughout history people have been put to the test to prove their capabilities or to establish qualifications.Language tests play an important role in many people's lives,acting as gateways at important transitional moments in education.The college English test paper was reviewed and checked against the test specifications to see its content coverage and representative.To evaluate the test,this includes item analysis,descriptive statistics,validity,and what we see as the strong points and the weaknesses of the test based on the analysis and the testing conditions,both of which provided validity evidence.In order to gather details of the test items,item analysis was done to find out the difficulty and discrimination of each item and identify misfit items for further discussion.

实用汉语水平认定考试(C.TEST)语音测试现状分析

本文根据历次"实用汉语水平认定考试(C.TEST)"测试的题目数据,对C.TEST语音测试的试卷质量、题型效果、测试点类型等方面进行综合分析。结果表明,语音测试题整体区分度较好,但普遍容易;语音读辨题型的难度明显大于听辨题型,区分度也是前者好于后者;不同测试点类型的题目平均区分度相差不大,但难度存在一定差距。笔者认为,C.TEST语音测试当务之急是提高题目的整体难度,特别是听辨题以及声母、声-韵测试题的难度。

基于Gitest Ⅲ的听力过关测试试题项目分析

通过利用GitestⅢ软件,作者对湖南城市学院英语专业2009年1月听力过关测试全部客观题进行了较为详细的项目分析,检测了试题的信度和效度,并针对分析结果提出在设计听力测试客观题方面应注意的问题及建议。

Routine blood tests to predict liver fibrosis in chronic hepatitis C

AIM: To verify the usefulness of FibroQ for predicting fi brosis in patients with chronic hepatitis C, compared with other noninvasive tests. METHODS: This retrospective cohort study included 237 consecutive patients with chronic hepatitis C who had undergone percutaneous liver biopsy before treatment. FibroQ, aspartate aminotransferase (AST)/alanine aminotransferase ratio (AAR), AST to platelet ratioindex, cirrhosis discriminant score, age-platelet index (API), Pohl score, FIB-4 index, and Lok's model were calculated and compared. RESULTS: FibroQ, FIB-4, AAR, API and Lok's model results increased significantly as fibrosis advanced (analysis of variance test: P < 0.001). FibroQ trended to be superior in predicting signifi cant fi brosis score in chronic hepatitis C compared with other noninvasive tests. CONCLUSION: FibroQ is a simple and useful test for predicting signifi cant fi brosis in patients with chronic hepatitis C.

基于人工神经网络的C．TEST阅读理解题目难度的预测研究

实用汉语水平认定考试(简称C.TEST)是用来测试母语非汉语的外籍人士在国际环境下社会生活以及日常工作中实际运用汉语能力的考试。由于C.TEST的考试题目公开,题库数量较小,所以通过一般标准化考试采用的在部分目标被试中实施预测(field test)的方法来获取考试题目的难度参数存在困难。然而,人工神经网络技术作为现代人工智能研究的成果,在预测(prediction)领域发挥了很大作用。本文选取C.TEST(A-D级)的阅读理解题目作为研究材料,运用人工神经网络技术对其难度进行预测,得到了网络预测难度值与实际考试难度值显著相关的研究结果。这一结果表明,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。

Designing of A Computerized Cognitive Adaptive Testing Model

Therecouldbenoscienceasweknowitwithoutmeasurement.Testing,includingallformsoflanguagetestingandpsychometricsitself,isoneformofmeasurement.Alanguagetestmaybedefinedasaprocedureforelicitinglanguageperformanceandaprocedureforassessingthatperformance.How...

A new discriminative sparse parameter classifier with iterative removal for face recognition

Face recognition has been widely used and developed rapidly in recent years.The methods based on sparse representation have made great breakthroughs,and collaborative representation-based classification(CRC)is the typical representative.However,CRC cannot distinguish similar samples well,leading to a wrong classification easily.As an improved method based on CRC,the two-phase test sample sparse representation(TPTSSR)removes the samples that make little contribution to the representation of the testing sample.Nevertheless,only one removal is not sufficient,since some useless samples may still be retained,along with some useful samples maybe being removed randomly.In this work,a novel classifier,called discriminative sparse parameter(DSP)classifier with iterative removal,is proposed for face recognition.The proposed DSP classifier utilizes sparse parameter to measure the representation ability of training samples straight-forward.Moreover,to avoid some useful samples being removed randomly with only one removal,DSP classifier removes most uncorrelated samples gradually with iterations.Extensive experiments on different typical poses,expressions and noisy face datasets are conducted to assess the performance of the proposed DSP classifier.The experimental results demonstrate that DSP classifier achieves a better recognition rate than the well-known SRC,CRC,RRC,RCR,SRMVS,RFSR and TPTSSR classifiers for face recognition in various situations.

An Analysis of the Listening Comprehension in CET-6——Illustrated by the CET-6 Test on June,2018

The College English Test Band Six(CET-6)is one of the most widely applied exam across China.As a national teaching test,CET-6 is sponsored by the Department of higher education of the Ministry of education of The People’s Republic of China and held twice a year.In this study,77 sophomores of different majors were tested using the listening test in June 2018.It is ensured that the test method is exactly same as that of CET-6.The purpose of this paper is to analyze the content and specification of CET-6 listening comprehension test,and to evaluate this part in detail according to the real data,including score report and item analysis,trying to provide some enlightenment for the revision of the examination.

慢性心力衰竭患者运动康复依从性量表的编制及信效度检验

背景慢性心力衰竭患者运动康复效果的维持有赖于良好的运动康复依从行为,有效及科学地评估其运动康复依从性具有重要的实践意义,但目前国内外尚缺乏公认的慢性心力衰竭患者运动康复依从性评价工具。目的编制慢性心力衰竭患者运动康复依从性量表,为快速便捷地评估慢性心力衰竭患者运动康复依从性提供科学、适宜的工具。方法在前期慢性心力衰竭患者运动康复最佳证据总结和质性研究的基础上,通过文献回顾、结合课题组意见,形成初始条目池;根据小样本预调查、德尔菲专家函询形成临床测试版量表。便利抽样法选取2020年11月—2021年2月在江苏省3所三级甲等医院心血管内科就诊的稳定期慢性心力衰竭患者作为研究对象。第一阶段发放有效量表274份,结合项目反应理论和经典测量理论对量表的条目进行筛选并进行探索性因子分析,形成正式版量表;第二阶段发放有效量表282份,对正式版量表进行验证性因子分析和信效度分析,形成最终版量表。结果正式量表包括2个维度11个条目。各条目的难度合理,且均未出现逆反阈值,条目区分度、项目信息量及项目特征曲线均较优。量表总的Cronbach’sα系数为0.905,其中“处方依从”维度Cronbach’sα系数为0.895,“监测依从”维度Cronbach’sα系数为0.910。总折半信度为0.724、重测信度为0.902。探索性因子分析结果显示2个因子能解释总变异的70.231%,进一步验证性因子分析的结果显示模型各参数较优,拟合较好。结论本研究构建的慢性心力衰竭患者运动康复依从性量表的条目难度、区分度合理,项目信息量较好,同时具有较高的信度和效度,可作为慢性心力衰竭患者运动康复依从性的评估工具。

Novel approach for the automated detection of allergy test using spectral imaging

This paper proposes a novel approach for the automatic detection of allergy test (allergy lesion). A hyperspectral microscope system was used to image the test samples which were diagnosed by dermatologist. It was found that allergy of different levels, and healthy skin cells show absorption spectra, which are sufficiently characteristic and yet reproducible enough to allow for differentiation when using a spectroscopic system. Principal components analysis was used to extract relevant features that could be used for classification from these spectra. Preliminary results indicate that the different types of allergy cells can be reliably distinguished by these features. We conclude that hyperspectral microscopic analysis is a promising approach for improving and automating the diagnosis of allergy test as well as another skin lesions.

基于大语言模型的试题自动生成路径研究

大语言模型具有强大的自然语言理解与生成能力,将大语言模型应用于试题自动生成领域,能够极大地提高我国教育考试发展的数字化水平。在具体教育场景中,尚需克服大模型普遍缺少专业知识、知识水平难以达到专业课程的教学精度、难度等挑战。为提高大模型自动生成试题的质量,本研究构建一种基于大语言模型的试题自动生成路径,并对其进行验证研究。首先是基于检索增强进行知识集成,其次是将课程知识以知识点的形式融入提示模板,最后是结合提示工程的效用,使大模型在理解课程知识的基础上执行大量试题生成任务。验证结果发现,自动生成试题的合格率为86.47%,随机抽取试题组成的测验难度为0.67,试题接受度良好。

How to Design an English Test Paper

It is quite necessary for teachers of English to know the basic knowledge and techniques about how to design good English testpapers. To meet this necessity, this paper first tells of the basic principles and requirements of designing English test papers, then the procedures,and, at last, the characters of some test questions and the techniques when designing them.

大规模教育考试命题教师的胜任特征——基于O^(*)NET工作分析的研究

提升命题质量需要加强命题教师胜任特征研究。为此,本研究采用O*NET工作分析问卷对参与大规模教育考试命题的136名教师进行调查,问卷内容涵盖工作任务、知识、技能、能力和工作风格。结果发现:1)语文、数学、英语三个学科的命题教师对工作任务、知识、技能、工作风格的重要性评价比较一致;2)不同学科命题教师注重的必备能力既有相同之处,又存在差异;3)正式试卷命题教师比模拟试卷命题教师更强调合作的重要性。研究结果对基于胜任特征的大规模教育考试命题教师的选聘、培训和考核具有参考价值。

中文版hearWHO应用程序在听力筛查中的验证

目的验证中文版hearWHO应用程序,一款噪声下数字言语测试工具,在听力筛查中的有效性。方法招募听力正常者12名,听力损失患者92例。所有受试者依次完成纯音听阈测试、声导抗测试以及中文版hearWHO测试。分析双耳PTA0.5~4kHz和hearWHO得分的相关性,采用受试者工作特性曲线及曲线下面积等参数,确定hearWHO得分在最佳诊断截点下的灵敏度和特异度。结果hearWHO得分与较好耳和较差耳纯音听阈均值PTA0.5~4kHz均呈显著负相关性,相关系数分别为-0.552和-0.693(P<0.001)。按PTA0.5~4kHz≥20dBHL为存在听力损失的标准,当hearWHO得分≤60时,提示至少单耳出现听力下降,灵敏度和特异度分别为0.733、0.690;当hearWHO得分≤50时,提示受试者可能存在双耳听力下降,灵敏度和特异度分别为0.815、0.917。结论hearWHO对检出单耳或双耳听力损失的灵敏度和特异度均较高,当hearWHO得分≤60时,提示受试者有必要转诊进行进一步的听力检测及诊断。

劳动教育融入中高考的价值、内涵与路径

在中高考试题中融入劳动教育,引导学生树立劳动观念、弘扬劳动精神、提高劳动能力,是新时代落实党中央对劳动教育新要求、改革教育教学评价的必要举措,也是构建引导德智体美劳全面发展的考试内容体系的现实需要。以语文中高考试题命制为例,劳动教育的融入可从劳动核心素养的维度出发丰富试题内涵,以情境化试题为考查载体,通过文本材料选择和试题设计构建基于语文学科素养和劳动素养相结合的各种情境,有机渗透劳动教育理念与内涵,增强学生在语文学习过程中对劳动价值、劳动精神的体验与领悟。