Predictive criterion validity comparing problem solving scenarios and intelligence tests in VS .NET

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Table 81 Predictive criterion validity comparing problem solving scenarios and intelligence tests
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Quality of problem solving behaviour and intellectual Partial correlations, controlling for behaviour in daily Job performance: job performance Intelligence Problem solving Knowledge cooperative ability Intelligence Problem solving Knowledge 039** 037** 030* 033** 029* 023 023 032** 032** 007 019 006
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Source: From Kersting (2001) Diagnostica, 47, 67 76
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COMPUTER-BASED TESTING AND THE INTERNET
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For all predictors the assessment of cooperative ability demonstrated discriminant validity Additionally, partial correlations were computed It is immediately obvious that the different variables predict similar variance to a large extent This leads to the question of whether a combination of predictors is able to raise the validity of the prediction, ie incremental validity This was tested by a hierarchical regression analysis In the rst step, based on the highest bivariate correlation, intelligence was included, yielding an R of 039 By also including system speci c knowledge about the tailorshop as a second predictor, R was raised to 046 This equals an incremental percentage of explained variance of 7% Another increment in prediction was achieved by including the third predictor, control performance on the tailorshop , but was signi cant only at the 10% level After inclusion of all predictors a multiple correlation of R 0:50 was obtained Considering a predictor above and beyond intelligence thus provides a substantive contribution to predictive power On purely statistical terms control performance and knowledge proved to be similarly adequate in achieving signi cant prediction increments The variable that was added to intelligence on the second step led to a statistically signi cant increase of the multiple R The variable that was included on the third step did not The sequence in which the predictors were included in the hierarchical regression shown here was based on the theoretical assumption that the systematic variance in control performance on problem solving scenarios can essentially be attributed to intelligence and knowledge Accordingly, based on these theoretical assumptions, intelligence and knowledge were given priority in the hierarchical regression analysis Problem solving scenarios are diagnostically interesting, because it is not only intelligence but also knowledge that is required for managing these scenarios Inclusion of knowledge in job performance may yield an increment in overall validity For practical purposes it may be worthwhile to use both intelligence and knowledge assessment Problem solving scenarios will be helpful in this regard, because managing complex problem solving scenarios demands acquiring knowledge, which could subsequently be tested Signi cant progress in the domain of problem solving assessment cannot be expected until both the operationalization of problem solving quality and the psychometric quality of assessment instruments are improved Above all, it is essential to classify the ability tapped by the performance measures within an existing nomological network Studies are required in which suf ciently reliable measures are implemented by means of different computer-based scenarios, and differentiated measures of intelligence are administered in suf ciently large samples At the same time, tests of additional theoretically relevant constructs such as knowledge also need to be administered In investigations of this kind (see Wittmann & Su , 1999) it was shown that the systematic variance captured by problem solving scenarios can mainly be attributed to intelligence and prior knowledge There is no empirical evidence for the existence of something like a problem solving ability as an independent construct
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Returning to the initial argument for a controlled psycho-diagnostic experiment, it seems obvious that the test environment for unsupervised web-based testing in particular is quite uncontrolled There may be background proctors such as friends and relatives if testing is done at home Moreover, participants may use books, information materials, or the internet as an aid in responding, not to mention unobserved effects resulting from emotional and physiological states such as fatigue, boredom, and so on Even the differences in technical equipment, browsers, operating systems, and displays may cause variations in results that are error variance Participants may fake , repeat tests, or return to previous items, if no precautions are taken This can be remedied to some degree by sophisticated software, but ultimately full control is only possible by using professional testing centres as is done by ETS and other big test delivery companies Even in self-assessments for vocational and educational purposes, some minimal standards for controlling the testing situation must be ensured It should be mentioned here that simulations and games have their own drawbacks and lack of proper control too Typical problems include misunderstanding instructions and lack of personal contact or emotional rapport with assessors, which is hardly compensated by an impersonal FAQ list, wordy reports based on few items, impersonal transfer of results, no personal feedback in case of unfavourable results, lack of acceptance of the psychometric procedures, security of data transmission, anonymity, and test fairness, to name just a few All the various drawbacks and problems of control discussed in this chapter are nothing but a challenge to improve quality It is essential that several qualitative and quantitative studies are carried out to identify and remove aws With modern IRT it is not only possible to reach an economical score estimate, but also to use statistical t indices in order to gauge whether the participant is responding in line with a theoretical model Whenever there is a low t for a series of responses, it becomes imperative to nd out how to improve the test administration algorithm The same holds true for timing controls and protocols They tell, on an item by item basis, how long a participant has been working on each task They provide the basis for detecting aberrant response patterns Having a cup of tea during the test may be ne, but a ten minutes interruption of a cognitive task lowers validity and reliability! Intelligent programming of computer and web based test administration routines for the future poses a big challenge Group testing in the past showed that participants did not always function at the level for which the test was designed, frequently leading to false decisions To overcome such problems in the open environment of web testing is the challenge that lies ahead of us ETS, for example, have used video cameras to monitor participants in order to safeguard against false test takers and helpers Modern technology will bring further support in this respect
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