نقش ریاضیات در کالج و آمادگی شغلی
ترجمه نشده

نقش ریاضیات در کالج و آمادگی شغلی

عنوان فارسی مقاله: نقش ریاضیات در کالج و آمادگی شغلی: شواهدی از PISA
عنوان انگلیسی مقاله: The role that mathematics plays in college- and career-readiness: evidence from PISA
مجله/کنفرانس: مجله مطالعات برنامه آموزشی - Journal of Curriculum Studies
رشته های تحصیلی مرتبط: علوم تربیتی
گرایش های تحصیلی مرتبط: مدیریت و برنامه ریزی آموزشی، تکنولوژی آموزشی
کلمات کلیدی فارسی: سواد ریاضی، محتوای ریاضیات، فرصت یادگیری، آمادگی شغلی، آمادگی کالج
کلمات کلیدی انگلیسی: Mathematics literacy، mathematics content، opportunity to learn، career ready، college ready
نمایه: Master Journal List - JCR - Scopus
شناسه دیجیتال (DOI): https://doi.org/10.1080/00220272.2018.1533998
دانشگاه: Michigan State University, East Lansing, MI, USA
ناشر: تیلور و فرانسیس - Taylor & Francis
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2018
ایمپکت فاکتور: 1/337 در سال 2017
شاخص H_index: 47 در سال 2019
شاخص SJR: 0/834 در سال 2017
شناسه ISSN: 1366-5839
شاخص Quartile (چارک): Q1 در سال 2017
فرمت مقاله انگلیسی: PDF
تعداد صفحات مقاله انگلیسی: 25
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: بله
کد محصول: E10927
فهرست انگلیسی مطالب

Abstract


Background


Methodology


Results


Discussion and conclusion


References

نمونه متن انگلیسی مقاله

Abstract


Many studies have found a strong relationship between the mathematics students study in school and their performance on an academic or school mathematics assessment but not on an assessment of mathematics literacy (ML). With many countries, like the USA, placing emphasis on finishing secondary education being mathematically literate and prepared for college or career, this raises the question about the relationship between the mathematics studied in school and any ML students may have. The Programme for International Student Assessment (PISA) ML assessment is embedded in real-world contexts that provide an important window on how ready students are to tackle the situations and problems that await them whether they intend to pursue further education beyond high school or intend to go directly into the labour force. In this paper, we draw upon the PISA 2012 data to investigate the extent to which the cumulative exposure to rigorous mathematics content, such as that embedded in college- and career-ready standards, is associated with ML as assessed in PISA. Results reveal that both exposure to rigorous school mathematics and experiencing the instruction of this mathematics through real-world applications are significantly related to all the real-world contextualized PISA ML scores.


Background


The common sense notion that the exposure students experience related to a topic is related to what they learn about that topic has played an important role in education research for over a century. This psychological perspective on OTL is an idea that was evident in the writings of psychologists Edward Thorndike and William James as far back as around the turn of the last century (Cogan & Schmidt, in press; James, 1983; Thorndike, 1913). OTL describes a focal aspect of schooling—the coverage of content in the classroom that is directly related to what a student learns. Learning theories have a long and rich heritage in the psychological and education literatures but Carroll’s (1963) model was among the first to specifically address classroom learning. It defines classroom learning as an interaction between the instruction provided and what is needed by the student in order to learn, e.g. aptitude, ability and perseverance. Bloom and his colleagues made use of Carroll’s theory in the OTL measures developed and used in the First International Mathematics Study which became, in turn, the example for relating OTL to learning for much education research over the past 50 years especially in the international comparative literature (Cogan & Schmidt, 2015). Typically teachers are the ones providing the information on OTL; however, obtaining such information from students has the benefit of reflecting the student’s perception which is likely affected by the student factors included in Carroll’s model. Nonetheless, the focus of most of the research that has investigated the relationship of OTL to what students know has been conducted with measures of students’ learning of the formal/ academic mathematics taught in school. The emphasis of this paper on literacy and the application of mathematics knowledge to real-world, everyday situations raises the question as to what specifically occurs in schools that might support the development of ML (de Lange, 2003)? This uncertainty about what type of OTL in schooling may be related to the development of literacy is related to at least two issues. One has to do with the nature of learning and the other has to do with the nature of instruction.

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