نوع مقاله : مقاله پژوهشی
نویسنده
عضو هیات علمی دانشکده علوم تربیتی و روانشناسی دانشگاه شهید چمران اهواز،اهواز،ایران
چکیده
دراین‌مقاله سعی شده است تا نظریه جدید آزمون سازی موسوم به نظریه سؤال - پاسخ
(Item Response Theory) مورد بحث و بررسی قرار گیرد. این نظریه عمدتا" به دلیل اشکالاتی به وجود آمده است که روانسنجان جدید به نظریه کلاسیک آزمون، مطرح کرده‌اند. این نظریه نمره کل آزمون را برای تفسیر عملکرد آزمودنی مدنظر قرار نمی‌دهد. بلکه هر سؤال آزمون، به‌طور انفرادی مورد مطالعه قرار می‌گیرد. این نظریه از منحنی ویژگی سؤال و پارامترهایی چون دشواری و تمیز، برای برآورد احتمال پاسخ درست آزمودنی به هر سؤال آزمون استفاده می‌کند. به‌علاوه، این‌نظریه بر پایه دو فرض اساسی استقلال موضعی و تک‌بعدی بودن فضای خصیصه مکنون استوار است. و براین اساس، احتمال پاسخ درست هر سؤال آزمون به عنوان تابعی از دشواری سؤال و توانایی آزمودنی توسط منحنی تراکمی نرمال و اخیرا" توسط منحنی منطقی که ساده‌تر است، بررسی می شود.
عنوان مقاله [English]
Item Response Theory in Psychological and Educational Tests
نویسنده [English]
- H. Sepasi
Faculty member of the Faculty of Educational Sciences and Psychology, Shahid Chamran University, Ahvaz, Ahvaz, Iran
چکیده [English]
In this article attempt has been made to introduce the new test theory, i. e. item response theory, (IRT). The major reason for the development of this new theory was the criticism raised by new psychometrician against old one, i. e. The classical test theory (CTT). Traces of this theory can be found in the work of Lowely. In recent years, other test specialists like Lord, and Brinbuam have played a major role in introducing the IRT. In this theory the total test score does not appear to play a very significant role in interperting examinee performance, rather, the test items are studied individually. The theory uses item characteristics curve parameters such as difficulty and discrimination indices to estimate the probability of examinee’s correct response to each test item. This theory is based mainly on two basic assumptions: local independence and unidimensionality of latent trait space. Based on these two assumptions, the probability of correct answers to every test item was first investigated by cummulative normal ogive curve and then by logistic curve for its simpilicity to work with. Lord introduced normal ogive curve, then it was Brinbaum who replaced the normal ogive by logistic curve to facilitate computation. He also designed one-parameter model, (difficulty parameter), two-parameter model (difficulty and discrimination), and three parameter model (difficulty, discrimination, and, guess), all of which can be used in constructing psychological and educational tests.
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