With the development of computer technology and Internet, e-Learning has become more and more important to support student¡¦s learning. Novice students usually lack adequate assisting tools especially in programming learning. Therefore, we propose the problem-based Python programming learning system with extendable item-bank. The system can generate program debugging exercise by using mutation testing technology. Additionally, for enhancing student¡¦s problem-exploration and reasoning capacity, the system provide another practice - Programming Exercise Creating Practice. In this kind of practice, every student can create his own programming exercise using question template and answer code template. This practice not only can enhance student¡¦s capacity but also can rich enrich the system¡¦s item-bank by using this strategy. Different from other programming learning systems, our system provide a more complete trainings on programming capacities, and building with Web2.0 concept. So, student who learns programming on this system will not only do exercise, but he also can help other students. So, student can get more kind of learning chance in this way. Additionally, we also hope that teacher¡¦s loading will be decreased and quality of course will be increased by using this system.

Wh-indefinites in Chinese have received great attention and discussion in the literature. This thesis investigates the status of Chinese wh-indefinites and their behaviors in the so-called donkey sentence. A typical example of wh-indefinite will be like the following: (4) Ta bu xiang zai shuo shenme le he not want again say what LE ¡¥He does not want to say anything again.¡¦ ¥L¤£·Q¦A»¡¤°»ò¤F¡C In this thesis, accounts of wh-indefinites as variables, polarity items and quantifiers from Huang (1982), Li (1992), Cheng (1991, 1994) and Lin (1996, 1998) are provided and this thesis discusses the problems each account presents. Countering Li¡¦s (1992) work, this work argue that wh-indefinite like zenmeyang ¡¦how¡¦ and weishenme ¡¥why¡¦ cannot be directly treated as variables since they feature variables only if they appear after an auxiliary (under which situation they will express purpose or method) in a donkey sentence according to Tsai (1999, 2000), see the following examples: (5) a. Akiu hui wei (le) shenme cizhi wo jiu hui wei (le) shenme cizhi¡@ Akiu will for LE what resign I then will for LE what resign ¡¥If Akiu will resign for the purpose x, I will then also resign for the purpose x.¡¦ ªüQ·|¬°¡]¤F¡^¤°»òÃ㾡A§Ú´N·|¬°¡]¤F¡^¤°»òÃ㾡C b. *Akiu wei (le) shenme hui cizhi wo jiu wei (le) shenme hui cizhi Akiu for LE what will resign I then will LE what will resign Intended ¡¥If Akiu will resign because of the reason x, I will then also resign because of the reason x. *ªüQ¬°¤F¤°»ò·|Ã㾡A§Ú´N¬°¤F¤°»ò·|Ã㾡C (Tsai¡¦s 2000, 15 glossed and translated by the author) Avoiding treating wh-indefinites as variables, we may treat them as quantifiers according to Huang¡¦s observation. But Huang¡¦s (1982) quantifier account of wh-indefinites is also rejected because I observe that wh-indefinites do not exhibit island sensitivity. Then we are led to another treatment: treating wh-indefinites as polarity items because they are sensitive to polarity environment. Aside from the sensitivity to polarity environment, Lin¡¦s (1996) work argues that wh-indefinites are licensed as polarity items if the sentence is subject to NEEC- non-entailment of existence condition. NEEC tells us that if (part of) a sentence does not have the existential import of object; wh-words can be licensed as wh-indefinites. This faces challenge because there are cases presupposing existential import yet the wh-indefinite is licensed. In chapter 3, two types of donkey sentences are identified in Cheng and Huang¡¦s (1996) work and are accounted with different approaches-Unselective Binding and E-type analysis. Though accepting their viewpoint generally, Lin (1996) makes a distinction between one-case and multi-case reading and opens the possibility of universal interpretation in ruguo-conditionals. Later I introduce Indirect binding approach to account both types of donkey sentences. Indirect Binding argues that some quantified expression plays the role as associating the indefinite with the anaphoric element in donkey sentences: (6) [Everyone who ti keeps a dogj]i like itj. The example here captures the very basic idea of Indirect Binding: the chunk of expression, which has the indefinite a dog in its scope, c-commands the pronoun it and hence relates it to the indefinite. I extend it to the analysis of Chinese donkey sentences and discover that although Indirect Binding does not target at a particular status, the condition that the indirect binder must c-command the indefinite seems to suggest that c-commanding is the way of licensing a wh-indefinite, which echoes Li¡¦s and Cheng¡¦s analyses. In Chapter 4, I introduce wh-indefinites in Japanese and Korean respectively and conclude that quantificational force comes from the environment but not from wh-indefinites themselves, countering Huang (1982). Finally, I suggest that licensing a wh-word as a wh-indefinite is through being c-commanded by the relevant operators. It is so because of Li¡¦s and Cheng¡¦s observation of wh-indefinites licensing and also of a condition in Indirect Binding that indirect binders must c-command the indefinite in order to have it as in its scope, as I have mentioned. This thesis then provides a viewpoint that perhaps, wh-indefinites can be treated uniformly as polarity items considering that Indirect Binding approach explains their behavior in donkey sentences. This thesis also opens the door for analyzing wh-indefinites in donkey sentences under Indirect Binding in other languages. Keywords¡G Wh-indefinite, polarity item, variable, quantifier, donkey phenomenon, Indirect Binding

<p>Two aspects of cognitive control were investigated using the item-recognition task and the verb generation task. The item-recognition task had two conditions, high and low interference. The verb generation task was manipulated in three ways, for different levels of interference and time interval. The intention was to more deeply investigate one aspect of the item-recognition task, comparing response times for different trial types in different conditions, and to investigate a fatigue effect between the item-recognition and verb generation task. Thirty-two participants were tested at two occasions, in a within-subjects design. Results for the verb generation task revealed effects for levels of interference and time interval, although there was no difference in the manipulation. Results for the item-recognition task revealed effects for condition and trial type, as well as an interaction effect between these. The non-familiar trials in the high interference condition resulted in faster response times compared to the same kind of trials in the low condition. The result from the item-recognition task extends those from previous studies, revealing details for differences between trial types. This finding demonstrates a carry-over facilitation effect.</p>

Thesis (Ph. D.)--University of Texas at Austin, 2003. / Vita. Includes bibliographical references. Available also from UMI Company.

The assessment of noncognitive constructs poses a number of challenges that set it apart from traditional cognitive ability measurement. Of particular concern is the influence of response biases and response styles that can influence the accuracy of scale scores. One strategy to address these concerns is to use alternative item presentation formats (such as multidimensional forced choice (MFC) pairs, triads, and tetrads) that may provide resistance to such biases. A variety of strategies for constructing and scoring these forced choice measured have been proposed, though they often require large sample sizes, are limited in the way that statements can vary in location, and (in some cases) require a separate precalibration phase prior to the scoring of forced-choice responses. This dissertation introduces new item response theory models for estimating item and person parameters from rank-order responses indicating preferences among two or more alternatives representing, for example, different personality dimensions. Parameters for this new model, called the Hyperbolic Cosine Model for Rank order responses (HCM-RANK), can be estimated using Markov chain Monte Carlo (MCMC) methods that allow for the simultaneous evaluation of item properties and person scores. The efficacy of the MCMC parameter estimation procedures for these new models was examined via three studies. Study 1 was a Monte Carlo simulation examining the efficacy of parameter recovery across levels of sample size, dimensionality, and approaches to item calibration and scoring. It was found that estimation accuracy improves with sample size, and trait scores and location parameters can be estimated reasonably well in small samples. Study 2 was a simulation examining the robustness of trait estimation to error introduced by substituting subject matter expert (SME) estimates of statement location for MCMC item parameter estimates and true item parameters. Only small decreases in accuracy relative to the true parameters were observed, suggesting that using SME ratings of statement location for scoring might be a viable short-term way of expediting MFC test deployment in field settings. Study 3 was included primarily to illustrate the use of the newly developed IRT models and estimation methods with real data. An empirical investigation comparing validities of personality measures using different item formats yielded mixed results and raised questions about multidimensional test construction practices that will be explored in future research. The presentation concludes with a discussion of MFC methods and potential applications in educational and workforce contexts.

Not available / text

Differential item functioning (DIF) can occur across age, gender, ethnic, and/or linguistic groups of examinee populations. Therefore, whenever there is more than one group of examinees involved in a test, a possibility of DIF exists. It is important to detect items with DIF with accurate and powerful statistical methods. While finding a proper DIP method is essential, until now most of the available methods have been dominated by applications to large scale testing contexts. Since the early 1990s, Ramsay has developed a nonparametric item response methodology and computer software, TestGraf (Ramsay, 2000). The nonparametric item response theory (IRT) method requires fewer examinees and items than other item response theory methods and was also designed to detect DIF. However, nonparametric IRT's Type I error rate for DIF detection had not been investigated. The present study investigated the Type I error rate of the nonparametric IRT DIF detection method, when applied to moderate-to-small-scale testing context wherein there were 500 or fewer examinees in a group. In addition, the Mantel-Haenszel (MH) DIF detection method was included. A three-parameter logistic item response model was used to generate data for the two population groups. Each population corresponded to a test of 40 items. Item statistics for the first 34 non-DIF items were randomly chosen from the mathematics test of the 1999 TEVISS (Third International Mathematics and Science Study) for grade eight, whereas item statistics for the last six studied items were adopted from the DIF items used in the study of Muniz, Hambleton, and Xing (2001). These six items were the focus of this study.

In DIF studies, a Type I error refers to the mistake of identifying non-DIF items as DIF items, and a Type I error rate refers to the proportion of Type I errors in a simulation study. The possibility of making a Type I error in DIF studies is always present and high possibility of making such an error can weaken the validity of the assessment. Therefore, the quality of a test assessment is related to a Type I error rate and to how to control such a rate. Current DIF studies regarding a Type I error rate have found that the latter rate can be affected by several factors, such as test length, sample size, test group size, group mean difference, group standard deviation difference, and an underlying model. This study focused on another undiscovered factor that may affect a Type I error rate; the effect of multiple testing. DIF analysis conducts multiple significance testing of items in a test, and such multiple testing may increase the possibility of making a Type I error at least once. The main goal of this dissertation was to investigate how to control a Type I error rate using adjustment procedures for multiple testing which have been widely used in applied statistics but rarely used in DIF studies. In the simulation study, four DIF methods were performed under a total of 36 testing conditions; the methods were the Mantel-Haenszel method, the logistic regression procedure, the Differential Functioning Item and Test framework, and the Lord’s chi-square test. Then the Bonferroni correction, the Holm’s procedure, and the BH method were applied as an adjustment of multiple significance testing. The results of this study showed the effectiveness of three adjustment procedures in controlling a Type I error rate.

No description available.

No description available.