Factors Affecting the Classification Accuracy and Average Length of a Variable-Length Cognitive Diagnostic Computerized Test

In computerized adaptive testing (CAT), a variable-length stopping rule refers to ending item administration after a pre-specified measurement precision standard has been satisfied. The goal is to provide equal measurement precision for all examinees regardless of their true latent trait level. Several stopping rules have been proposed in unidimensional CAT, such as the minimum information rule or the maximum standard error rule. These rules have also been extended to multidimensional CAT and cognitive diagnostic CAT, and they all share the same idea of monitoring measurement error. Recently, Babcock and Weiss (J Comput Adapt Test2012. https://doi.org/10.7333/1212-0101001) proposed an "absolute change in theta" (CT) rule, which is useful when an item bank is exhaustive of good items for one or more ranges of the trait continuum. Choi, Grady and Dodd (Educ Psychol Meas 70:1-17,2010) also argued that a CAT should stop when the standard error does not change, implying that the item bank is likely exhausted. Although these stopping rules have been evaluated and compared in different simulation studies, the relationships among the various rules remain unclear, and therefore there lacks a clear guideline regarding when to use which rule. This paper presents analytic results to show the connections among various stopping rules within both unidimensional and multidimensional CAT. In particular, it is argued that the CT-rule alone can be unstable and it can end the test prematurely. However, the CT-rule can be a useful secondary rule to monitor the point of diminished returns. To further provide empirical evidence, three simulation studies are reported using both the 2PL model and the multidimensional graded response model.

For item selection in cognitive diagnostic computerized adaptive testing (CD-CAT), ideally, a single item selection index should be created to simultaneously regulate precision, exposure status, and attribute balancing. For this purpose, in this study, we first proposed an attribute-balanced item selection criterion, namely, the standardized weighted deviation global discrimination index (SWDGDI), and subsequently formulated the constrained progressive index (CP_SWDGDI) by casting the SWDGDI in a progressive algorithm. A simulation study revealed that the SWDGDI method was effective in balancing attribute coverage and the CP_SWDGDI method was able to simultaneously balance attribute coverage and item pool usage while maintaining acceptable estimation precision. This research also demonstrates the advantage of a relatively low number of attributes in CD-CAT applications.

To improve the calibration accuracy and calibration efficiency of cognitive diagnostic computerized adaptive testing (CD-CAT) for new items and, ultimately, contribute to the widespread application of CD-CAT in practice, the current article proposed a Gini-based online calibration method that can simultaneously calibrate the Q-matrix and item parameters of new items. Three simulation studies with simulated and real item banks were conducted to investigate the performance of the proposed method and compare it with the joint estimation algorithm (JEA) and the single-item estimation (SIE) methods. The results indicated that the proposed Gini-based online calibration method yielded higher calibration efficiency than those of the SIE method and outperformed the JEA method on item calibration tasks in terms of both accuracy and efficiency under most experimental conditions.

An econometric analysis of three health economic issues in China

Advantageous to assessment in many fields, CAT (computerized adaptive testing) use in general practice has been scarce. In adapting CAT to general practice, the basic assumptions of item response theory and the case specificity must be taken into account. In this context, this study first evaluated the feasibility of converting written extended matching tests into CAT. Second, it questioned the content validity of CAT. A stratified sample of students was invited to participate in the pilot study. The items used in this test, together with their parameters, originated from the written test. The detailed test paths of the students were retained and analysed thoroughly. Using the predefined pass–fail standard, one student failed the test. There was a positive correlation between the number of items and the candidate's ability level. The majority of students were presented with questions in seven of the 10 existing domains. Although proved to be a feasible test format, CAT cannot substitute for the existing high-stakes large-scale written test. It may provide a reliable instrument for identifying candidates who are at risk of failing in the written test.

This entry presents an overview of computer‐adaptive testing (CAT). The basic CAT algorithm is introduced, followed by a discussion of item response theory (IRT) test information functions and their role in adaptive testing. Issues such as test efficiency and security risks under CAT are also discussed. The entry concludes with a description of four promising CAT variants, including CAT shadow tests, a‐stratified CAT, testlet‐based CAT, and computer‐adaptive multistage testing.

Background: Demoralization, anxiety, irritability, and depression are common among hospital patients and are associated with poorer outcomes and greater healthcare burden. Early identification is essential, but simultaneous screening across multiple domains is often impractical with questionnaires. Computerized Adaptive Testing (CAT) offers a solution by tailoring item administration, reducing test length while preserving measurement precision. The aim of this study was to develop and validate FRIDA (Four-factor Rapid Interactive Diagnostic Assessment), a freely accessible, web-based CAT for rapid multidimensional screening of psychopathology in hospital patients. Methods: We analysed data from 472 medically ill in-patients at a University Hospital. Item calibration was performed using a four-factor graded response model (demoralization, anxiety, irritability, depression) in the mirt package. CAT simulations were run with 1000 virtual respondents to optimize item selection, exposure control, and stopping rules. The best configuration was applied to the real dataset. Criterion validity for demoralization was evaluated against the Diagnostic Criteria for Psychosomatic Research (DCPR). Results: The four-factor model showed good fit (CFI = 0.947, RMSEA = 0.080). Factor correlations were moderate to high, with the strongest overlap between demoralization and depression (r = 0.93). In simulations, the CAT required, on average, 7.8 items and recovered trait estimates with high accuracy (r = 0.94-0.97). In real patients, mean test length was 11 items, with accuracy of r = 0.95 across domains. FRIDA demonstrated good criterion validity for demoralization (AUC = 0.816; sensitivity 80%, specificity 67.5%). Conclusions: FRIDA is the first freely available, multidimensional CAT for rapid screening of psychopathology in hospital patients. It offers a scalable, efficient, and precise tool for integrating mental health assessment into routine hospital care.

Towards improving detection of early warning signals within organizations : an approach to the identification and utilization of underlying factors from an organizational perspective

Neonatal hearing loss is a change with important influence in children's cognitive development.To diagnose the possible case we hove tree options:· Wait consequence to diagnose hearing loss· Selection possible cases according to risk factors· Make an universal screening to select possible hearing loss casesFrom in 1991 we start to use PEATC we have done all three options.We report the findings in each one to conclude that the best option is an universal screening based on OTOEA.When we doing a hearing screening based on risk factor we reduce middle-aged at the moment of diagnosis but it loss 48% non transmissive hearing loss.Finally we recommended an universal screening because decreased middle-aged less than one year old and in theory it con recognize the possible hearing loss cases.

Blastocystis hominis , a protozoan parasite commonly found in the gut of humans and animals, is closely related to a variety of gastrointestinal diseases, such as abdominal pain, diarrhea and intestinal mucosal damage. B. hominis is distributed all over the world. The in vitro culture of B. hominis is of great significance for the clinical diagnosis of B. hominis infection and the establishment of B. hominis animal model, the study of genotype and pathogenic mechanism and so on. The selection of efficient and economical culture medium lays the foundation for the follow-up study of B. hominis life cycle, morphological classification, infection immunity and so on. The state, type, serum concentration of culture medium and culture conditions are important factors affecting the culture of B. hominis in vitro . This review summarizes the research progress of B. hominis culture in vitro and the culture conditions suitable for rapid growth and propagation of B. hominis under different physical conditions, expounds the differences between different media and the factors affecting the culture of B. hominis in vitro , in order to provide reference for clinical and scientific researchers to select suitable culture medium and culture conditions. 摘要： 人芽囊原虫( Blastocystis hominis )呈世界性分布,是一种常见的人和动物肠道内寄生原虫,与多种胃肠道疾病 (如腹痛、腹泻、肠黏膜损伤)密切相关。体外培养人芽囊原虫对于临床诊断人芽囊原虫感染、建立人芽囊原虫动物模 型、进行基因型和致病机制等研究具有重要意义;选择髙效经济的培养基为人芽囊原虫的生活史、形态分类、感染免疫 等后续研究奠定基础。培养基的状态、种类、血清浓度和培养条件等是影响人芽囊原虫体外培养的重要因素。本综述 总结了人芽囊原虫体外培养的研究进展及不同物理状态下适合人芽囊原虫快速生长繁殖的培养条件,阐述了不同培 养基之间的差异及影响人芽囊原虫体外培养的因素,旨在为临床和科研工作者选择合适的培养基及培养条件提供 参考。

The goal of the new edition is to continue with a systems view of the world. For a more robust and worldwide market dissemination, the new edition has changed to a reference book. The project systems approach to project management, is needed in executing projects across countries and across cultures, which is a crucial requirement in today's globalized and intertwined economics. The book uses ample graphical representations to clarify the concepts and techniques presented. The case examples help to reinforce the topics covered. Several illustrative examples and practice exercises are included. Each chapter is updated and new chapters include Project Simulation and Project Templates. A new chapter on managing complex projects in an age of artificial intelligence adds a unique value to the book. Features Highlights contemporary best practices of project management Uses a systems framework to integrate quantitative and qualitative tools Offers illustrative examples and practice exercises Covers project schedule performance appraisal techniques Discusses the knowledge areas contained in the Project Management Book of Knowledge (PMBOK) Presents software applications for project management, as well as case examples

Computerized Adaptive Testing (CAT) offers an efficient and personalized method for assessing examinee proficiency by dynamically adjusting test questions based on individual performance. Compared to traditional, non-personalized testing methods, CAT requires fewer questions and provides more accurate assessments. As a result, CAT has been widely adopted across various fields, including education, healthcare, sports, sociology, and the evaluation of AI models. While traditional methods rely on psychometrics and statistics, the increasing complexity of large-scale testing has spurred the integration of machine learning techniques. This paper aims to provide a machine learning-focused survey on CAT, presenting a fresh perspective on this adaptive testing paradigm. We delve into measurement models, question selection algorithm, bank construction, and test control within CAT, exploring how machine learning can optimize these components. Through an analysis of current methods, strengths, limitations, and challenges, we strive to develop robust, fair, and efficient CAT systems. By bridging psychometric-driven CAT research with machine learning, this survey advocates for a more inclusive and interdisciplinary approach to the future of adaptive testing.

With the rapid development of intelligent education, Computerized Adaptive Testing(CAT) has garnered significant attention for its ability to tailor exercises to individual examinees. The adaptability of CAT is primarily achieved through the alternating optimization of two core components: the cognitive diagnosis model and the exercise selection module. However, existing CAT approaches, despite their remarkable achievements, often come at the expense of high time costs. Statistical-based approaches incur increased time overhead due to complex computations, while data-driven approaches further exacerbate time inefficiency because of the iterative processes in reinforcement learning, making it challenging to balance evaluation effectiveness and time efficiency. To this end, in this paper, we propose HashCAT, an efficient CAT approach based on learning to hash, aiming to balance efficiency and evaluation effectiveness. Our approach comprises two stages: the hash representation generation and the exercise selection. In the first stage, we design an information alignment module and a novel cognitive diagnosis function to model the interaction between examinees and exercises, generating hash representations with clear physical significance. In the second stage, we propose an uncertainty reduction-based algorithm that utilize information entropy to quantify the uncertainty in student ability estimation and selects exercises that most effectively reduce this uncertainty. Experimental results on four real-world datasets demonstrate that the proposed method significantly improves question selection efficiency while maintaining competitive evaluation performance. The code exists anonymously in https://github.com/sherklock/Intelligent-Education/tree/main/HashCAT-main.

To evaluate the usefulness of computerized adaptive testing (CAT) in medical school, the General Examination for senior medical students was administered as a paper and pencil test (P&P) and using CAT. The General Examination is a graduate examination, which is also a preliminary examination for the Korean Medical Licensing Examination (KMLE). The correlations between the results of the CAT and P&P and KMLE were analyzed. The correlation between the CAT and P&P was 0.8013 (p=0.000); that between the CAT and P&P was 0.7861 (p=0.000); and that between the CAT and KMLE was 0.6436 (p=0.000). Six out of 12 students with an ability estimate below 0.52 failed the KMLE. The results showed that CAT could replace P&P in medical school. The ability of CAT to predict whether students would pass the KMLE was 0.5 when the criterion of the theta value was set at -0.52 that was chosen arbitrarily for the prediction of pass or failure.

به‌منظور ارزیابی آثار تنش رطوبتی بر صفات زراعی و مورفولوژیک لاین‌های اینبرد نوترکیب گندم، مطالعه‌ای با استفاده از 169‌لاین در قالب دو طرح لاتیس جداگانه (تنش رطوبتی و شاهد) اجرا شد. دو رژیم رطوبتی مشتمل بر آبیاری بر اساس 70 و 130‌میلی‌متر تبخیر از تشتک تبخیر کلاس A و همین‌طور درصد رطوبت وزنی خاک استفاده شد. نتایج تجزیه واریانس نشان داد که تفاوت بین لاین‌ها در شرایط عادی رطوبتی برای کلیه صفات به‌جزء تعداد دانه در سنبله، وزن دانه در سنبله، طول سنبله، تعداد روز تا گرده‌افشانی و تعداد روز تا رسیدگی معنی‌دار بوده است. در شرایط تنش رطوبتی نیز تفاوت لاین‌ها برای همه صفات به‌جزء تعداد دانه در سنبله، وزن هزار‌دانه و طول سنبله معنی‌دار بود. تنش رطوبتی موجب کاهش تعداد روز تا ظهور سنبله، تعداد روز تا گرده‌افشانی، تعداد روز تا رسیدگی، تعداد سنبله در واحد سطح، طول سنبله، ارتفاع بوته، تعداد دانه در سنبله، وزن دانه در سنبله، وزن هزار‌دانه، عملکرد بیولوژیک، عملکرد دانه و شاخص برداشت گردید. وراثت‌پذیری خصوصی شاخص برداشت در شرایط عدم تنش رطوبتی کمتر از شرایط اعمال تنش بود. بیش‌ترین وراثت‌‌پذیری خصوصی در شرایط معمول رطوبتی به تعداد سنبله در واحد سطح (77درصد) و در شرایط تنش رطوبتی به عملکرد دانه (84درصد) اختصاص داشت. نتایج رگرسیون مرحله‌ای در شرایط تنش رطوبتی نشان داد که تعداد سنبله در واحد سطح اولین متغیر وارد شده به مدل بوده است که به‌تنهایی 65‌درصد از تغییرات عملکرد دانه را تبیین نمود.