Differences Between Self-Adapted and Computerized Adaptive Tests: A Meta-Analysis

Self-adapted testing has been described as a variation of computerized adaptive testing that reduces test anxiety and thereby enhances test performance. The purpose of this study was to gain a better understanding of these proposed effects of self-adapted tests (SATs); meta-analysis procedures were used to estimate differences between SATs and computerized adaptive tests (CATs) in proficiency estimates and post-test anxiety levels across studies in which these two types of tests have been compared. After controlling for measurement error, the results showed that SATs yielded proficiency estimates that were 0.12 standard deviation units higher and post-test anxiety levels that were 0.19 standard deviation units lower than those yielded by CATs. We speculate about possible reasons for these differences and discuss advantages and disadvantages of using SATs in operational settings.     

Procedures for Selecting Items for Computerized Adaptive Tests

Many procedures have been developed for selecting the "best" items for a computerized adaptive test. There is a trend toward the use of adaptive testing in applied settings such as licensure tests, program entrance tests, and educational tests. It is useful to consider procedures for item selection and the special needs of applied testing settings to facilitate test design. The current study reviews several classical approaches and alternative approaches to item selection and discusses their relative merit. This study also describes procedures for constrained computerized adaptive testing (C-CAT) that may be added to classical item selection approaches to allow them to be used for applied testing, while maintaining the high measurement precision and short test length that made adaptive testing attractive to practitioners initially.     

APPLICATION OF COMPUTERIZED ADAPTIVE TESTING TO EDUCATIONAL PROBLEMS

Three applications of computerized adaptive testing (CAT) to help solve problems encountered in educational settings are described and discussed. Each of these applications makes use of item response theory to select test questions from an item pool to estimate a student's achievement level and its precision. These estimates may then be used in conjunction with certain testing strategies to facilitate certain educational decisions. The three applications considered are (a) adaptive mastery testing for determining whether or not a student has mastered a particular content area, (b) adaptive grading for assigning grades to students, and (c) adaptive self-referenced testing for estimating change in a student's achievement level. Differences between currently used classroom procedures and these CAT procedures are discussed. For the adaptive mastery testing procedure, evidence from a series of studies comparing conventional and adaptive testing procedures is presented showing that the adaptive procedure results in more accurate mastery classifications than do conventional mastery tests, while using fewer test questions.     

Item Review and the Rearrangement Procedure: Its process and its results

Permitting item review is to the benefit of the examinees who typically increase their test scores with item review. However, testing companies do not prefer item review since it does not follow the logic on which adaptive tests are based, and since it is prone to cheating strategies. Consequently, item review is not permitted in many adaptive tests. This study attempts to provide a solution that would allow examinees to revise their answers, without jeopardizing the quality and efficiency of the test. The purpose of this study is to test the efficiency of a “rearrangement procedure” that rearranges and skips certain items in order to better estimate the examinees' abilities, without allowing them to cheat on the test. This was examined through a simulation study. The results show that the rearrangement procedure is effective in reducing the standard error of the Bayesian ability estimates and in increasing the reliability of the same estimates.     

Computerized Adaptive and Fixed-Item Testing of Music Listening Skill: A Comparison of Efficiency, Precision, and Concurrent Validity

We evaluated the efficiency, precision, and concurrent validity of results obtained from adaptive and fired-item music listening tests in three studies: (a) a computer simulation study in which each of 2,200 simulees completed a computerized adaptive tonal memory test, a computerized fired-item tonal memory test constructed from items in the adaptive test pool and two standardized group-administered tonal memory tests; (b) a live testing study in which each of 204 examinees took the computerized adaptive test and the standardized tests; and (c) a live testing study in which randomly equivalent groups took either the computerized adaptive test (n = 86) or the computerized fired-item test (n = 86). The adaptive music test required 50% to 93% fewer items to match the reliability and concurrent validity of the fired-item tests, and it yielded higher levels of reliability and concurrent validity than the fired-item tests when test length was held constant. These findings suggest that computerized adaptive tests, which typically have been limited to visually produced items, may also be well suited for measuring skills that require aurally produced items.     

Detecting Individual Differences in Change: Methods and Comparisons

This study examined and compared various statistical methods for detecting individual differences in change. Considering 3 issues including test forms (specific vs. generalized), estimation procedures (constrained vs. unconstrained), and nonnormality, we evaluated 4 variance tests including the specific Wald variance test, the generalized Wald variance test, the specific likelihood ratio (LR) variance test, and the generalized LR variance test under both constrained and unconstrained estimation for both normal and nonnormal data. For the constrained estimation procedure, both the mixture distribution approach and the alpha correction approach were evaluated for their performance in dealing with the boundary problem. To deal with the nonnormality issue, we used the sandwich standard error (SE) estimator for the Wald tests and the Satorra–Bentler scaling correction for the LR tests. Simulation results revealed that testing a variance parameter and the associated covariances (generalized) had higher power than testing the variance solely (specific), unless the true covariances were zero. In addition, the variance tests under constrained estimation outperformed those under unconstrained estimation in terms of higher empirical power and better control of Type I error rates. Among all the studied tests, for both normal and nonnormal data, the robust generalized LR and Wald variance tests with the constrained estimation procedure were generally more powerful and had better Type I error rates for testing variance components than the other tests. Results from the comparisons between specific and generalized variance tests and between constrained and unconstrained estimation were discussed.     

A Simulation and Comparison of Flexilevel and Bayesian Computerized Adaptive Testing

Computerized adaptive testing (CAT) is a testing procedure that adapts an examination to an examinee's ability by administering only items of appropriate difficulty for the examinee. In this study, the authors compared Lord's flexilevel testing procedure (flexilevel CAT) with an item response theory-based CAT using Bayesian estimation of ability (Bayesian CAT). Three flexilevel CATs, which differed in test length (36, 18, and 11 items), and three Bayesian CATs were simulated; the Bayesian CATs differed from one another in the standard error of estimate (SEE) used for terminating the test (0.25, 0.10, and 0.05). Results showed that the flexilevel 36- and 18-item CATs produced ability estimates that may be considered as accurate as those of the Bayesian CAT with SEE = 0.10 and comparable to the Bayesian CAT with SEE = 0.05. The authors discuss the implications for classroom testing and for item response theory-based CAT.     

Stratified and Maximum Information Item Selection Procedures in Computer Adaptive Testing

In this study we evaluated and compared three item selection procedures: the maximum Fisher information procedure (F), the a-stratified multistage computer adaptive testing (CAT) (STR), and a refined stratification procedure that allows more items to be selected from the high a strata and fewer items from the low a strata (USTR), along with completely random item selection (RAN). The comparisons were with respect to error variances, reliability of ability estimates and item usage through CATs simulated under nine test conditions of various practical constraints and item selection space. The results showed that F had an apparent precision advantage over STR and USTR under unconstrained item selection, but with very poor item usage. USTR reduced error variances for STR under various conditions, with small compromises in item usage. Compared to F, USTR enhanced item usage while achieving comparable precision in ability estimates; it achieved a precision level similar to F with improved item usage when items were selected under exposure control and with limited item selection space. The results provide implications for choosing an appropriate item selection procedure in applied settings.     

Some Practical Examples of Computer-Adaptive Sequential Testing

Computerized testing has created new challenges for the production and administration of test forms. Many testing organizations engaged in or considering computerized testing may find themselves changing from well-established procedures for handcrafiing a small number of paper-and-pencil test forms to procedures for mass producing many computerized test forms. This paper describes an integratedapproach to test development and administration called computer-adaptive sequential testing, or CAST. CAST is a structured approach to test construction which incorporates both adaptive testing methods with automated test assembly to allow test developers to maintain a greater degree of control over the production, quality assurance, and administration of different types of computerized tests. CAST retains much of the efficiency of traditional computer adaptive testing (CAT) and can be modified for computer mastery testing (CMT) applications. The CAST framework is described in detail and several applications are demonstrated using a medical licensure example.     

An Empirical Study of Computerized Adaptive Test Administration Conditions

This empirical study was designed to determine the impact of computerized adap- tive test (CAT) administration formats on student performance. Students in medical technology programs took a paper-and-pencil and an individualized, computerized adaptive test. Students were randomly assigned to adaptive test administration for- mats to ascertain the effect on student performance of altering: (a) the difficulty of the first item, (b) the targeted level of test difficulty, (c) minimum test length, and (d) the opportunity to control the test. Computerized adaptive test data were analyzed with ANCO VA. The paper-and.pencil test was used as a covariate to equalize abil- ity variance among cells. The only significant main effect was for opportunity to control the test. There were no significant interactions among test administration formats. This study provides evidence concerning adjusting traditional computer- ized adaptive testing to more familiar testing modalities.     

ITEM ANALYSIS FOR TEACHER-MADE MASTERY TESTS1

Various item selection techniques are compared on resultant criterionreferenced reliability and validity. Techniques compared include three nominal criterion-referenced methods, a traditional point biserial selection, teacher selection, and random selection. Eighteen volunteer junior and senior high school teachers supplied behavioral objectives and item pools ranging from 26 to 40 items. Each teacher obtained reponses from four classes. Pairs of tests of various length were developed by each item selection method. Estimates of test reliability and validity were obtained using responses independent of the test construction sample. Resultant reliability and validity estimates were compared across item selection techniques. Two of the criterion-referenced item selection methods resulted in consistently higher observed validity. However, the small magnitude of improvement over teacher or random selection raises a question as to whether the benefit warrants the necessary extra effort on the part of the classroom teacher.     

Longitudinal Multistage Testing

This article introduces longitudinal multistage testing (lMST), a special form of multistage testing (MST), as a method for adaptive testing in longitudinal large‐scale studies. In lMST designs, test forms of different difficulty levels are used, whereas the values on a pretest determine the routing to these test forms. Since lMST allows for testing in paper and pencil mode, lMST may represent an alternative to conventional testing (CT) in assessments for which other adaptive testing designs are not applicable. In this article the performance of lMST is compared to CT in terms of test targeting as well as bias and efficiency of ability and change estimates. Using a simulation study, the effect of the stability of ability across waves, the difficulty level of the different test forms, and the number of link items between the test forms were investigated.     

Rapid Assessment of Learners’ Proficiency: A cognitive load approach

To tailor instruction to levels of learner proficiency in a domain in adaptive learning environments, rapid on‐line methods of assessing learner knowledge and skills are required. Cognitive studies indicate that major factors in expert performance are organised structures in the person’s knowledge base. Measuring different levels of acquisition of such knowledge structures should be a major purpose of cognitive diagnostic assessment. Traditional tests may not provide reliable evidence for diagnostic purposes and are not suitable for dynamic learning environments. This paper discusses an alternative diagnostic approach based on monitoring immediate traces of students’ knowledge structures in working memory. Results of an experimental study applying this method to assessment of user reading skills are described. The study demonstrated a sufficiently high level of correlation (.66) between obtained measures and traditional test scores, and a substantial increase in reliability, with testing time reduced by a factor of 3.8.     

Using Patterns of Summed Scores in Paper-and-Pencil Tests and Computer-Adaptive Tests to Detect Misfitting Item Score Patterns

Two new methods have been proposed to determine unexpected sum scores on sub-tests (testlets) both for paper-and-pencil tests and computer adaptive tests. A method based on a conservative bound using the hypergeometric distribution, denoted p, was compared with a method where the probability for each score combination was calculated using a highest density region (HDR). Furthermore, these methods were compared with the standardized log-likelihood statistic with and without a correction for the estimated latent trait value (denoted as l*_z and l_z, respectively). Data were simulated on the basis of the one-parameter logistic model, and both parametric and non-parametric logistic regression was used to obtain estimates of the latent trait. Results showed that it is important to take the trait level into account when comparing subtest scores. In a nonparametric item response theory (IRT) context, on adapted version of the HDR method was a powerful alterative to p. In a parametric IRT context, results showed that l*_z had the highest power when the data were simulated conditionally on the estimated latent trait level.     

Reviewing and Changing Answers on Computer-adaptive and Self-adaptive Vocabulary Tests

Results obtained from computer-adaptive and self-adaptive tests were compared under conditions in which item review was permitted and not permitted. Comparisons of answers before and after review within the "review" condition showed that a small percentage of answers was changed (5.23%), that more answers were changed from wrong to right than from right to wrong (by a ratio of 2.92:1), that most examinees (66.5%) changed answers to at least some questions, that most examinees who changed answers improved their ability estimates by doing so (by a ratio of 2.55 to 1), and that review was particularly beneficial to examineees at high ability levels. Comparisons between the "review" and "no-review" conditions yielded no significant differences in ability estimates or in estimated measurement error and provided no trustworthy evidence that test anxiety moderated the effects of review on those indexes. Most examinees desired review, but permitting it increased testing time by 41%.     

计算机自适应考试系统研究

本文结合专家经验确定法和项目反应理论,设计出一种简明、实用的计算机自适应考试系统的试题难度确定方法,同时重点分析计算机自适应考试系统的测试起点、终点选择,选题策略和能力值估计方法。最后列举了一个自适应测试的步骤实例。本系统能够根据不同能力被试者随机选择试题项目,减少了测试长度,与传统在线考试系统相比提高了考试效率。     

Can Examinees Use a Review Option to Obtain Positively Biased Ability Estimates on a Computerized Adaptive Test?

Part of the controversy about allowing examinees to review and change answers to previous items on computerized adaptive tests (CATs) centers on a strategy for obtaining positively biased ability estimates attributed to Wainer (1993) in which examinees intentionally answer items incorrectly before review and to the best of their abilities upon review. Our results, based on both simulated and live testing data, showed that there were instances in which the Wainer strategy yielded inflated ability estimates as well as instances in which it yielded deflated ability estimates. The success of the strategy in inflating ability estimates depended on the ability estimation method used (maximum likelihood versus Bayesian), the examinee's true ability level, the standard error of the ability estimate, the examinee's ability to implement the strategy, and the type of decision made from the ability estimate. We discuss approaches to dealing with the Wainer strategy in operational CAT settings.     

Limiting Answer Review and Change on Computerized Adaptive Vocabulary Tests: Psychometric and Attitudinal Results

Previous simulation studies of computerized adaptive tests (CATs) have revealed that the validity and precision of proficiency estimates can be maintained when review opportunities are limited to items within successive blocks. Our purpose in this study was to evaluate the effectiveness of CATs with such restricted review options in a live testing setting. Vocabulary CATs were compared under four conditions: (a) no item review allowed, (b) review allowed only within successive 5-item blocks, (c) review allowed only within successive lO-item blocks, and (d) review allowed only after answering all 40 items. Results revealed no trust-worthy differences among conditions in vocabulary proficiency estimates, measurement error, or testing time. Within each review condition, ability estimates and number correct scores increased slightly after review, more answers were changed from wrong to right than from right to wrong, most examinees who changed answers improved proficiency estimates by doing so, and nearly all examinees indicated that they had an adequate opportunity to review their previous answers. These results suggest that restricting review opportunities on CATs may provide a viable way to satisfy examinee desires, maintain validity and measurement precision, and keep testing time at acceptable levels.     

PROGRESS MONITORING WITH COMPUTER ADAPTIVE ASSESSMENTS: THE IMPACT OF DATA COLLECTION SCHEDULE ON GROWTH ESTIMATES

Although extensive research exists on the use of curriculum‐based measures for progress monitoring, little is known about using computer adaptive tests (CATs) for progress‐monitoring purposes. The purpose of this study was to evaluate the impact of the frequency of data collection on individual and group growth estimates using a CAT. Data were available for 278 fourth‐ and fifth‐grade students. Growth estimates were obtained when five, three, and two data collections were available across 18 weeks. Data were analyzed by grade to evaluate any observed differences in growth. Further, root mean square error values were obtained to evaluate differences in individual student growth estimates across data collection schedules. Group‐level estimates of growth did not differ across data collection schedules; however, growth estimates for individual students varied across the different schedules of data collection. Implications for using CATs to monitor student progress at the individual or group level are discussed.     

Effects of Practical Constraints on Item Selection Rules at the Early Stages of Computerized Adaptive Testing

The purpose of this study was to compare the effects of four item selection rules—(1) Fisher information (F), (2) Fisher information with a posterior distribution (FP), (3) Kullback-Leibler information with a posterior distribution (KP), and (4) completely randomized item selection (RN)—with respect to the precision of trait estimation and the extent of item usage at the early stages of computerized adaptive testing. The comparison of the four item selection rules was carried out under three conditions: (1) using only the item information function as the item selection criterion; (2) using both the item information function and content balancing; and (3) using the item information function, content balancing, and item exposure control. When test length was less than 10 items, FP and KP tended to outperform F at extreme trait levels in Condition 1. However, in more realistic settings, it could not be concluded that FP and KP outperformed F, especially when item exposure control was imposed. When test length was greater than 10 items, the three nonrandom item selection procedures performed similarly no matter what the condition was, while F had slightly higher item usage.