کاربرد مدل طبقه پنهان چندبعدی مبتنی بر نظریه پاسخ سوال (LCMIRT) درمطالعه ابعاد شناختی و خوشه بندی سؤال های آزمون ریاضی: مطالعه موردی درس ریاضی کنکور سراسری ریاضی فیزیک

نوع مقاله: مقاله پژوهشی

نویسندگان

1 استادیار، تحقیقات آموزشی، دانشگاه خوارزمی، تهران، ایران

2 استادیار، تحقیقات آموزشی، دانشگاه خوارزمی، تهران، ایران.

3 کارشناسی ارشد، تحقیقات آموزشی، دانشگاه خوارزمی، تهران، ایران.

چکیده

مهارت ریاضی شامل حوزه های محتوایی و فرایندهای شناختی مختلف است که بیانگر پیچیدگی توانایی ریاضی و ویژگی های پنهان آن است. تاکنون مطالعه این پیچیدگی ها با روش های سنتی تحلیل داده ها یا به صورت ذهنی انجام شده است. بنابراین، پژوهش حاضر با استفاده از مدل چندبعدی طبقه پنهان پاسخ سوال (LCMIRT) به مطالعه ابعاد شناختی و متغیر های پنهان درس ریاضی آزمون سراسری ورود به دانشگاه پرداخت. در این راستا، داده های درس ریاضی آزمون سراسری سال های 87، 90 و 94 مورد مطالعه قرار گرفت. یافته ها نشان داد که آزمون ریاضی، به عنوان یکی از دروس سرنوشت ساز در آزمون سراسری ورود به دانشگاه، شامل مجموعه ای از ویژگی های شناختی چندبعدی است. نتایج روش تحلیل موازی وحدت یافته نشان داد که آزمون ها با مدل تک بعدی برازش ندارند و اضافه کردن ابعاد بیشتر، برازش مدل را به صورت معنی داری بهبود می بخشد. بعلاوه، حوزه های شناختی درک، حل مسئله و استدلال سه سازه اساسی در تبیین توانایی ریاضی شناسایی شدند که در خوشه بندی و تحلیل سؤالهای آزمون، اطلاعات دقیق تری از کیفیت سوال ها به دست می دهند. این ویژگی LCMIRT ، در مقایسه با سایر رویکردها، تعداد زیر خوشه های شناختی را افزایش می دهد. در نهایت توصیه می شود که در ساخت و تحلیل آزمون های روانی و تربیتی، مدل های LCMIRT مد نظر قرار گیرند تا آشکارسازی توانایی های شناختی پنهان آزمون ها از اعتبار بیشتری برخوردار باشد.

کلیدواژه‌ها


عنوان مقاله [English]

Application of Latent Class Multidimensional Item Response Theory (LCMIRT) on investigating cognitive dimensions and clustering math test items: A case study of the math test of national Konkur of physics and mathematics

نویسندگان [English]

  • Masoud Geramipour 1
  • Maryam Moghadasin 2
  • Reyhaneh Rezazadeh 3
1 Faculty member at faculty of psychology and education, Kharazmi university
2 Faculty member at faculty of psychology and education, Kharazmi university
3 MA of educational research, Kharazmi university
چکیده [English]

Math skills include different content and cognitive processes domains which indicate the complexity of math skill and its latent traits. Until now, Study of these complexities has been done through traditional data analysis or subjective methods. Therefore, present research studied cognitive dimensions and latent variables of the math test of national university entrance examination through the application of Latent Class Multidimensional Item Response Theory (LCMIRT). In doing so, the math test data of national examinations in 2008, 2011 and 2015 were studied. Results showed that the math test, as a high stakes test in the national university entrance examination, encompasses a set of multidimensional cognitive traits. Results of the unified parallel analysis method showed that the tests do not fit with the unidimensional model and adding additional dimensions can significantly improve model fit. Moreover, cognitive domains of comprehension, problem solving and reasoning were recognized as three essential constructs which account for math skills and give more detailed information about items quality in clustering and analysis of the test items. This property of LCMIRT, in comparison with other approaches, increases the number of cognitive sub-clusters. At last, it is recommended that LCMIRT models are considered in constructing and analyzing educational and psychological tests, in order to more validly detect latent cognitive skills of the tests.

کلیدواژه‌ها [English]

  • Cognitive Dimensions
  • Latent Class Multidimensional Item Response Theory (LCMIRT)
  • Test Items Clustering
  • Mathematics
  • High Stakes Tests
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