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32nd ACM International Conference on Information and Knowledge Management (CIKM)

作者： Hong, Yuting Tong, Shiwei Huang, Wei Zhuang, Yan Liu, Qi Chen, Enhong Li, Xin He, Yuanjing Univ Sci & Technol China Anhui Prov Key Lab Big Data Anal & Applicat Hefei Anhui Peoples R China State Key Lab Cognit Intelligence Hefei Anhui Peoples R China Univ Sci & Technol China Hefei Anhui Peoples R China IFLYTEK Co Ltd Artificial Intelligence Res Inst Hefei Anhui Peoples R China Open Univ China Beijing Peoples R China

ISBN: (纸本)9798400701245

computerized adaptive testing (CAT) arises as a promising personalized test mode in online education, targeting at revealing students' latent knowledge state by selecting test items adaptively. The item selection strategy is the core component of CAT, which searches for the best suitable test item based on students' current estimated ability at each test step. However, existing selection strategies behave in a brute-force manner, which results in the time complexity being linear to the number of items (N) in the item pool, i.e., O (N). Thus, in reality, the search latency becomes the bottleneck for CAT with a large-scale item pool. To this end, we propose a Search-Efficient computerized adaptive testing framework (SECAT), which aims at enhancing CAT with an efficient selection strategy. Specifically, SECAT contains two main phases: item pool indexing and item search. In the item pool indexing phase, we apply a student-aware spatial partition method on the item pool to divide the test items into many sub-spaces, considering the adaptability of test items. In the item search phase, we optimize the traditional single-round search strategy with the asymptotic theory and propose a multi-round search strategy that can further improve the time efficiency. Compared with existing strategies, the time complexity of SECAT decreases from O(N) to O (logN). Across two real-world datasets, SECAT achieves over 200x speed up with negligible accuracy degradation.

关键词： computerized adaptive testing Educational Resource Search Educational Measurement Cognitive Diagnosis

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Identifying the content for an item bank and computerized adaptive testing system to measure the impact of age-related macular degeneration on health-related quality of life

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QUALITY OF LIFE RESEARCH 2022年第4期31卷 1237-1246页

作者： Fenwick, Eva K. Lee, Ester P. X. Man, Ryan E. K. Ho, Kam Chun Najjar, Raymond P. Milea, Dan Teo, Kelvin Y. C. Tan, Anna C. S. Lee, Shu Yen San Yeo, Ian Yew Tan, Gavin S. W. Mathur, Ranjana Wong, Tien Yin Cheung, Chui Ming Gemmy Lamoureux, Ecosse L. Singapore Eye Res Inst Singapore Natl Eye Ctr 20 Coll RdLevel 6 Singapore 169856 Singapore Natl Univ Singapore Duke NUS Med Sch Singapore Singapore UNSW Sydney Sydney NSW Australia Univ Melbourne Parkville Vic Australia

Purpose We are developing an age-related macular degeneration (AMD) health-related quality of life (HRQoL) item bank, applicable to Western and Asian populations. We report primarily on content generation and refinement, but also compare the HRQoL issues reported in our study with Western studies and current AMD-HRQoL questionnaires. Methods In this cross-sectional, qualitative study of AMD patients attending the Singapore National Eye Centre (May-December 2019), items/domains were generated from: (1) AMD-specific questionnaires;(2) published articles;(3) focus groups/semi-structured interviews with AMD patients (n = 27);and (4) written feedback from retinal experts. Following thematic analysis, items were systematically refined to a minimally representative set and pre-tested using cognitive interviews with 16 AMD patients. Results Of the 27 patients (mean +/- standard deviation age 67.9 +/- 7.0;59.2% male), 18 (66.7%), two (7.4%), and seven (25.9%) had no, early-intermediate, and late/advanced AMD (better eye), respectively. Whilst some HRQoL issues, e.g. activity limitation, mobility, lighting, and concerns were similarly reported by Western patients and covered by other questionnaires, others like anxiety about intravitreal injections, work tasks, and financial dependency were novel. Overall, 462 items within seven independent HRQoL domains were identified: Activity limitation, Lighting, Mobility, Emotional, Concerns, AMD management, and Work. Following item refinement, items were reduced to 219, with 31 items undergoing amendment. Conclusion Our 7-domain, 219-item AMD-specific HRQoL instrument will undergo psychometric testing and calibration for computerized adaptive testing. The future instrument will enable users to precisely, rapidly, and comprehensively quantify the HRQoL impact of AMD and associated treatments, with item coverage relevant across several populations.

关键词： Age-related macular degeneration Quality of life Item bank computerized adaptive testing Qualitative

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The Effect of computerized adaptive testing on Motivation and Anxiety: A Systematic Review and Meta-Analysis

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ASSESSMENT 2023年第5期30卷 1379-1390页

作者： Akhtar, Hanif Silfiasari Vekety, Boglarka Kovacs, Kristof Eotvos Lorand Univ Budapest Hungary Univ Muhammadiyah Malang Malang Indonesia

Although many studies have been carried out on the psychometric aspects of computerized adaptive testing (CAT), its psychological aspects are less researched. Early studies claimed that CAT can be more motivating and induce less anxiety than traditional fixed-item tests (FIT). The purpose of this systematic review and meta-analysis was to gain a comprehensive understanding of the effects of CAT on motivation and anxiety in comparison to traditional fixed-item testing. Seven databases were examined. Articles were eligible if they employed an empirical study containing a direct comparison between CAT and FIT. Meta-analytical results showed no overall effect of test type on anxiety and motivation when comparing CAT with FIT (k = 11, g+ = 0.06, p = .28). However, easier CAT had positive effect compared with FIT (k = 2, g+ = .22, p < .001). Certain modifications in CAT administration can provide positive psychological effects for test-takers.

关键词： computerized adaptive testing fixed-item testing motivation anxiety meta-analysis

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GMOCAT: A Graph-Enhanced Multi-Objective Method for computerized adaptive testing 23

GMOCAT: A Graph-Enhanced Multi-Objective Method for Computer...

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29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

作者： Wang, Hangyu Long, Ting Yin, Liang Zhang, Weinan Xia, Wei Hong, Qichen Xia, Dingyin Tang, Ruiming Yu, Yong Shanghai Jiao Tong Univ Shanghai Peoples R China Jilin Univ Changchun Peoples R China Huawei Noahs Ark Lab Shenzhen Peoples R China Huawei CBG Edu AI Lab Shenzhen Peoples R China

ISBN: (纸本)9798400701030

computerized adaptive testing (CAT) refers to an online system that adaptively selects the best-suited question for students with various abilities based on their historical response records. Compared with traditional CAT methods based on heuristic rules, recent data-driven CAT methods obtain higher performance by learning from large-scale datasets. However, most CAT methods only focus on the quality objective of predicting the student ability accurately, but neglect concept diversity or question exposure control, which are important considerations in ensuring the performance and validity of CAT. Besides, the students' response records contain valuable relational information between questions and knowledge concepts. The previous methods ignore this relational information, resulting in the selection of sub-optimal test questions. To address these challenges, we propose a Graph-Enhanced Multi-Objective method for CAT (GMOCAT). Firstly, three objectives, namely quality, diversity and novelty, are introduced into the Scalarized Multi-Objective Reinforcement Learning framework of CAT, which respectively correspond to improving the prediction accuracy, increasing the concept diversity and reducing the question exposure. We use an Actor-Critic Recommender to select questions and optimize three objectives simultaneously by the scalarization function. Secondly, we utilize the graph neural network to learn relation-aware embeddings of questions and concepts. These embeddings are able to aggregate neighborhood information in the relation graphs between questions and concepts. We conduct experiments on three real-world educational datasets. The experimental results show that GMOCAT not only outperforms the state-of-the-art methods in the ability prediction, but also achieve superior performance in improving the concept diversity and alleviating the question exposure.

关键词： computerized adaptive testing cognitive diagnosis reinforcement learning educational measurement

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The Impact of Item Model Parameter Variations on Person Parameter Estimation in computerized adaptive testing With Automatically Generated Items

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APPLIED PSYCHOLOGICAL MEASUREMENT 2023年第4期47卷 275-290页

作者： Tian, Chen Choi, Jaehwa Univ Maryland Dept Human Dev & Quantitat Methodol College Pk MD USA George Washington Univ Dept Educ Leadership Washington DC USA Univ Maryland Dept Human Dev & Quantitat Methodol 3942 Campus Dr College Pk MD 20742 USA

Sibling items developed through automatic item generation share similar but not identical psychometric properties. However, considering sibling item variations may bring huge computation difficulties and little improvement on scoring. Assuming identical characteristics among siblings, this study explores the impact of item model parameter variations (i.e., within-family variation between siblings) on person parameter estimation in linear tests and computerized adaptive testing (CAT). Specifically, we explore (1) what if small/medium/large within-family variance is ignored, (2) if the effect of larger within-model variance can be compensated by greater test length, (3) if the item model pool properties affect the impact of within-family variance on scoring, and (4) if the issues in (1) and (2) are different in linear vs. adaptive testing. Related sibling model is used for data generation and identical sibling model is assumed for scoring. Manipulated factors include test length, the size of within-model variation, and item model pool characteristics. Results show that as within-family variance increases, the standard error of scores remains at similar levels. For correlations between true and estimated score and RMSE, the effect of the larger within-model variance was compensated by test length. For bias, scores are biased towards the center, and bias was not compensated by test length. Despite the within-family variation is random in current simulations, to yield less biased ability estimates, the item model pool should provide balanced opportunities such that "fake-easy" and "fake-difficult" item instances cancel their effects. The results of CAT are similar to that of linear tests, except for higher efficiency.

关键词： automatic item generation computerized adaptive testing item model parameter variation identical sibling model

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Enhancing computerized adaptive testing with Batteries of Unidimensional Tests

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APPLIED PSYCHOLOGICAL MEASUREMENT 2023年第3期47卷 167-182页

作者： Anselmi, Pasquale Robusto, Egidio Cristante, Francesca Univ Padua Dept FISPPA Padua Italy Univ Padua Dept FISPPA Via Venezia 14 I-35131 Padua Italy

The article presents a new computerized adaptive testing (CAT) procedure for use with batteries of unidimensional tests. At each step of testing, the estimate of a certain ability is updated on the basis of the response to the latest administered item and the current estimates of all other abilities measured by the battery. The information deriving from these abilities is incorporated into an empirical prior that is updated each time that new estimates of the abilities are computed. In two simulation studies, the performance of the proposed procedure is compared with that of a standard procedure for CAT with batteries of unidimensional tests. The proposed procedure yields more accurate ability estimates in fixed-length CATs, and a reduction of test length in variable-length CATs. These gains in accuracy and efficiency increase with the correlation between the abilities measured by the batteries.

关键词： item response theory computerized adaptive testing test battery collateral information empirical prior test speededness

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Concerto Software for computerized adaptive testing - Free Version

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MEASUREMENT-INTERDISCIPLINARY RESEARCH AND PERSPECTIVES 2023年第3期21卷 194-202页

作者： Cheng, Yiling Kaohsiung Med Univ Dept Psychol Kaohsiung Taiwan Kaohsiung Med Univ Dept Psychol 100Shiquan 1st Rd Kaohsiung 701 Taiwan

computerized adaptive testing (CAT) offers an efficient and highly accurate method for estimating examinees' abilities. In this article, the free version of Concerto Software for CAT was reviewed, dividing our evaluation into three sections: software implementation, the Item Response Theory (IRT) features of CAT, and user experience. Overall, Concerto is an excellent tool for researchers seeking to create computerized adaptive (or non-adaptive) tests, providing a robust platform with comprehensive IRT capabilities and a user-friendly interface.

关键词： computerized adaptive testing Concerto software review

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Development of a computerized adaptive testing for ADHD using Bayesian networks: An attempt at classification

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CURRENT PSYCHOLOGY 2023年第22期42卷 19230-19240页

作者： Jiang, Zhehan Ma, Wenchao Flory, Kate Zhang, Dan Zhou, Wenjing Shi, Dexin Hua, Xiaochen Liu, Ren Peking Univ Inst Med Educ Beijing Peoples R China Univ Alabama Dept Educ Studies Psychol Res Methodol & Counsell Tuscaloosa AL USA Univ South Carolina Dept Psychol Columbia SC 29208 USA Tsinghua Univ Dept Psychol Beijing Peoples R China Hefei Univ Technol Sch Foreign Studies Hefei Anhui Peoples R China Univ Calif Merced Psychol Sci Merced CA USA

Quantifying the severity of neurological disorders, such as attention-deficit/hyperactivity disorder (ADHD), is encouraged in practice. To explore the methodological properties of data-driven classification, this study aimed to develop computerized adaptive testing (CAT) based on Bayesian networks to classify ADHD symptom severity for individual subjects efficiently. The Current Symptoms Scale was used to build an ADHD symptom severity classifier in a sample of 892 college students, and the CAT making use of information gains from conditional probabilities of the Bayesian network was evaluated through a simulation study. The results showed that distributing 8 out of 18 items on average to an individual subject would result in 85% classification accuracy, supporting the adaption of surveying ADHD to digital platforms demanding much-shortened scales. The severity classifier based on Bayesian networks can assist diagnostic tasks via a data-driven mechanism. Further, integrating CAT into the classifier can shorten the scale while maintain acceptable measurement quality. The ADHD symptoms were used in the paper;however, the proposed method applies to other psychological symptoms as well. The impact and limitations of the CAT for ADHD were discussed, and several suggestions for future research were provided.

关键词： Bayesian networks computerized adaptive testing ADHD Psychometrics Classification

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Controlling the Minimum Item Exposure Rate in computerized adaptive testing: A Two-Stage Sympson–Hetter Procedure

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Applied Psychological Measurement 2023年第7-8期47卷 460-477页

作者： Chao, Hsiu-Yi Chen, Jyun-Hong Soochow University Taiwan National Cheng Kung University Taiwan

computerized adaptive testing (CAT) can improve test efficiency, but it also causes the problem of unbalanced item usage within a pool. The effect of uneven item exposure rates can not only induce a test security problem due to overexposed items but also raise economic concerns about item pool development due to underexposed items. Therefore, this study proposes a two-stage Sympson–Hetter (TSH) method to enhance balanced item pool utilization by simultaneously controlling the minimum and maximum item exposure rates. The TSH method divides CAT into two stages. While the item exposure rates are controlled above a prespecified level (e.g., r_min) in the first stage to increase the exposure rates of the underexposed items, they are controlled below another prespecified level (e.g., r_max) in the second stage to prevent items from overexposure. To reduce the effect on trait estimation, TSH only administers a minimum sufficient number of underexposed items that are generally less discriminating in the first stage of CAT. The simulation study results indicate that the TSH method can effectively improve item pool usage without clearly compromising trait estimation precision in most conditions while maintaining the required level of test security. © The Author(s) 2023.

关键词： computerized adaptive testing item exposure control item pool utilization Sympson–Hetter procedure

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Efficient and precise Ultra-QuickDASH scale measuring lymphedema impact developed using computerized adaptive testing

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QUALITY OF LIFE RESEARCH 2022年第3期31卷 917-925页

作者： Xu, Cai Schaverien, Mark V. Christensen, Joani M. Sidey-Gibbons, Chris J. Univ Texas MD Anderson Canc Ctr Houston TX 77030 USA Univ Texas MD Anderson Canc Ctr Dept Symptom Res 1515 Holcombe BlvdUnit 1055 Houston TX 77030 USA Univ Texas MD Anderson Canc Ctr Dept Plast Surg Houston TX 77030 USA

Purpose This study aimed to evaluate and improve the accuracy and efficiency of the QuickDASH for use in assessment of limb function in patients with upper extremity lymphedema using modern psychometric techniques. Method We conducted confirmative factor analysis (CFA) and Mokken analysis to examine the assumption of unidimensionality for IRT model on data from 285 patients who completed the QuickDASH, and then fit the data to Samejima's graded response model (GRM) and assessed the assumption of local independence of items and calibrated the item responses for CAT simulation. Results Initial CFA and Mokken analyses demonstrated good scalability of items and unidimensionality. However, the local independence of items assumption was violated between items 9 (severity of pain) and 11 (sleeping difficulty due to pain) (Yen's Q3 = 0.46) and disordered thresholds were evident for item 5 (cutting food). After addressing these breaches of assumptions, the re-analyzed GRM with the remaining 10 items achieved an improved fit. Simulation of CAT administration demonstrated a high correlation between scores on the CAT and the QuickDash (r = 0.98). Items 2 (doing heavy chores) and 8 (limiting work or daily activities) were the most frequently used. The correlation among factor scores derived from the QuickDASH version with 11 items and the Ultra-QuickDASH version with items 2 and 8 was as high as 0.91. Conclusion By administering just these two best performing QuickDash items we can obtain estimates that are very similar to those obtained from the full-length QuickDash without the need for CAT technology.

关键词： QuickDASH measure Item response theory computerized adaptive testing Lymphedema Patient reported outcome measure Ultra-QuickDASH

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