سنجش درک فراگیران از مدل‌های‌ مفهومی و رابطه آن با مهارت استدلال علّی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار گروه علوم تربیتی، دانشگاه شهید چمران اهواز، اهواز، ایران

2 دانشجوی دکتری تخصصی یادگیری الکترونیکی در آموزش پزشکی، گروه آموزش الکترونیکی در علوم پزشکی، دانشگاه علوم پزشکی شیراز، شیراز، ایران

3 کارشناس ارشد تحقیقات آموزشی، دانشگاه شهید چمران اهواز، اهواز، ایران

چکیده

هدف: استدلال‌های مبتنی بر مدل مانند استدلال علّی از مهم‌ترین مهارت‌های شناختی شاگردان در درس علوم است، هرچند روش‌های تدریس مبتنی بر مدل به‌ویژه مدل‌های رایانه‌ای بر استدلال و تفکر تأثیر مثبت دارند، اما آشنایی و درک از مدل نیز می‌تواند در کاربست و سودمندی آن تأثیرگذار باشد. هدف این پژوهش تعیین رابطه بین فهم شاگردان از مدل و مدل‌سازی علمی و میزان مهارت استدلال علّی آنان است. این رابطه هنگام انجام مدل‌سازی دو کانونی با موضوع حرکت‌شناسی بررسی شد.
روش: نمونه‌ای 85 نفری (در دسترس) از شاگردان دوره دوم متوسطه اهواز انتخاب و از آن‌ها خواسته شد حین مدل‌‌سازی به چهار سؤال مرتبط با حرکت‌شناسی به‌طور تشریحی پاسخ داده و استدلال خود را بنویسند. برای پاسخ‌ها ابتدا کد تعریف شد و براساس کدها، نمره‌گذاری شدند. پس از مدل‌سازی، شاگردان به پرسشنامه درک از مدل پاسخ دادند و بر اساس آن و به کمک تحلیل خوشه‌ای به دو دسته درک مطلوب از مدل و درک خام از مدل طبقه‌بندی شدند.
یافته­ها: یافته‌ها نشان داد شاگردانی که درک مطلوبی از مدل و فرآیند مدل‌سازی داشته‌اند، به‌جز در بعد شناسایی عناصر استدلال که همه عملکرد مشابهی داشتند، در سایر ابعاد استدلال علّی نسبت به شاگردانی که درک خام از مدل‌ها داشتند، موفق‌تر عمل کردند.
نتیجه­گیری:  پژوهش‌گران توجه بیشتر برنامه‌های درسی رسمی به مدل‌سازی علمی، و آگاه‌سازی معلمان نسبت به ماهیت مدل‌ها، و تشویق آنان برای تدریس مبتنی بر مدل در کلاس را بر بهبود درک فراگیر از مدل‌ مؤثر دانسته و آن را موجب تقویت مهارت‌های شناختی مثل تفکر، از جمله استدلال علّی می‌دانند. 

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Assessing Learners' Understanding of Conceptual Models and its Relationship with Causal Reasoning Skills

نویسندگان [English]

  • Mojtaba Jahanifar 1
  • Bahareh Ghavami Hosein Pour 2
  • Fateme Dehghani 3
1 Assistant Professor, Department of Education, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
2 Ph. D student of E-learning in Medical Sciences, Department of E-learning in Medical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran.
3 M.Sc. in Educational Research, Shahid Chamran University of Ahvaz, Ahvaz, Iran
چکیده [English]

Objective: Model-based reasoning, such as causal reasoning, is one of the most important cognitive skills in science education, although model-based teaching, especially computer models, have a positive effect on reasoning, but model understanding can also affect its application and usefulness. The purpose of this research is to investigate the relationship between students' models' understanding and the level of causal reasoning skills.
Method: This relationship was investigated when performing bifocal modeling with the subject of mechanics. A sample of 85 secondary high school students in Ahvaz was selected, and were asked to answer four questions related to mechanic descriptively during modeling and write their reasoning. Codes were first defined and answers were scored based on the codes.
Results: After modeling, the students answered the model understanding questionnaire and based on that, with the cluster analysis, they were classified into two categories: "model ideal understanding" and "model raw understanding". The findings showed that the students who had a good understanding of the model and the modeling process, except in the reasoning identifying the elements, which all performed similarly, were more successful in other dimensions of causal reasoning than the students who had a raw model understanding
Conclusion:  Researchers have found that paying more attention to scientific modeling in official curricula, informing teachers about the models' nature, and encouraging them to teach based on models in the classroom are effective in improving students' models' understanding, and it strengthens thinking, including scientific reasoning.

کلیدواژه‌ها [English]

  • Science Education
  • Modeling
  • Bifocal Models
  • Nature of Models
  • Causal Reasoning

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راهبردهای شناختی در یادگیری
دوره 12، شماره 22 - شماره پیاپی 22
بهار و تابستان 1403
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