Item Sequence on Test Performance: Easy Items First?
نویسندگان
چکیده
منابع مشابه
The Effect of Item Modality and Note-taking on EFL Learners’ Performance on a Listening Test
The pivotal role of listening comprehension in second/foreign language learning requires that researchers conduct studies which investigate factors that affect test takers’ performances. The present study was set out to examine whether item modality (i.e., written vs. oral items) affects listening comprehension test performance. In addition, it investigated whether allowing test takers to take ...
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طراحی فرم های گوناگون از یک آزمون از جنبه ی ترتیب قرار گیری سوالات به موجب جلوگیری از تقلب امری رایج میان مدرسین زبان به کار می آید. این گونه پنداشته می شود که در چنین زمینه هایی ترتیب سوالات تأثیری بر عملکرد و ویژگی های روانشناختی آزمون ندارد. در این تحقیق بر این هستیم تا میزان تأثیر ترتیب گوناگون سوالات یک آزمون را بر عملکرد در آزمون بررسی کنیم و محاسبه تأثیر آن در آزمون واژگان زبان انگلیسی ...
Retrospective bias in test performance: Providing easy items at the beginning of a test makes students believe they did better on it.
We examined the effect of three variables (test list structure, report option, and framing) on retrospective bias in global evaluations of test performance (postdictions). Participants answered general knowledge questions and estimated correctness of their performance after each block. The ordering of the questions within a block affected bias: Participants believed they had answered more quest...
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Declaration All sentences or passages quoted in this dissertation from other people's work have been specifically acknowledged by clear cross-referencing to author, work and page(s). I understand that failure to do these amounts to plagiarism and will be considered grounds for failure in this dissertation and the degree examination as a whole. Abstract Norman Fenton states in his book Software ...
متن کاملFrequent Item-set Mining without Ubiquitous Items
Frequent Item-set Mining (FIM), sometimes called Market Basket Analysis (MBA) or Association Rule Learning (ARL), are Machine Learning (ML) methods for creating rules from datasets of transactions of items. Most methods identify items likely to appear together in a transaction based on the support (i.e. a minimum number of relative co-occurrence of the items) for that hypothesis. Although this ...
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ژورنال
عنوان ژورنال: Language Testing in Asia
سال: 2011
ISSN: 2229-0443
DOI: 10.1186/2229-0443-1-3-46