رویکرد شبکه عصبی مصنوعی برای پیش‌بینی درگیری تحصیلی بر اساس جو کلاس درس و تنظیم هیجان تحصیلی در دانش‌آموزان

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استاد گروه روانشناسی، دانشگاه محقق اردبیلی، اردبیل، ایران

2 متخصص اطفال، گروه پزشکی، دانشکده علوم پزشکی، دانشگاه علوم پزشکی اردبیل، اردبیل، ایران

چکیده

هدف: مشارکت فعال در مدرسه برای موفقیت تحصیلی دانش‌آموزان بسیار مهم است. پژوهش حاضر با هدف رویکرد شبکه عصبی مصنوعی برای پیش‌بینی درگیری تحصیلی بر اساس جو کلاس درس و تنظیم هیجان تحصیلی در دانش‌آموزان انجام گرفت.
روش‌ها: روش پژوهش حاضر توصیفی و از نوع همبستگی بود. جامعه آماری شامل دانش‌آموزان دوره دوم متوسطه شهر اردبیل در سال 1402 بود. تعداد 250 نفر از این افراد با استفاده از نمونه‌گیری در دسترس از بین جامعه آماری فوق انتخاب و به پرسشنامه‌های درگیری تحصیلی، جوکلاس درس و تنظیم هیجان تحصیلی پاسخ دادند. داده‌ها با شبکه عصبی مصنوعی با روش پرسپترون چندلایه (MPL) در نرم‌افزار SPSS.25 تحلیل شد.
یافته‌ها: نتایج تحلیل نشان داد که نقش جو کلاس درس و تنظیم هیجان تحصیلی در پیش‌بینی درگیری تحصیلی در نوجوانان با شبکه عصبی مصنوعی دارای یک لایه ورودی با پنج گره و یک لایه پنهان با سه گره است و شبکه عصبی مصنوعی قادر است به خوبی پرش‌ها و روند درگیری تحصیلی را از روی متغیرهای جو کلاس درس و تنظیم هیجان تحصیلی پیش‌بینی نماید.
نتیجه‌گیری: به طور کلی می‌توان گفت اجرای برنامه آموزشی شامل آموزش مهارت‌های مدیریت هیجان، ایجاد فضاهای مثبت و حامی توسط معلمان و کادر آموزشی، جهت ارتقاء درگیری تحصیلی توصیه می‌شود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

An artificial neural network approach for predicting academic engagement based on classroom atmosphere and Academic Emotion Regulation in students

نویسندگان [English]

  • mohammad narimani 1
  • azin narimani 2
1 Professor of Psychology, Faculty of Educational Sciences and Psychology, University of Mohaghegh Ardabili, Ardabil, Iran
2 Pediatrician, Department of Medicine, Faculty of Medical Sciences, Ardabil University of Medical Sciences, Ardabil, Iran
چکیده [English]

Objective: Active participation in school is very important for students' academic success. The present research was conducted with the aim of artificial neural network approach to predict academic engagement based on classroom atmosphere and Academic Emotion Regulation in students.
Method: The present research method was descriptive and correlational. The statistical population included students of the second year of secondary school in Ardabil city in 2023. 250 of these people were selected from the above statistical population using available sampling and answered the questionnaires of academic engagement, class jockey and academic emotion regulation. The data were analyzed with artificial neural network using Multilayer Perceptron (MPL) method in SPSS.25 software.
Results: The results of the analysis showed that the role of classroom atmosphere and academic emotion regulation in predicting academic engagement in adolescents with an artificial neural network has an input layer with five nodes and a hidden layer with three nodes, and the artificial neural network is able to well Predict the jumps and process of academic engagement based on the variables of classroom atmosphere and academic excitement regulation.
Conclusion: In general, it can be said that the implementation of an educational program including teaching emotion management skills, creating positive and supportive environments by teachers and educational staff is recommended to improve academic engagement.

کلیدواژه‌ها [English]

  • academic engagement
  • classroom atmosphere
  • academic excitement regulation
  • students
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سلمانی، منصور، خامسان، احمد، اسدی یونسی، محمدرضا. (1396). نقش واسطه­ای باورهای انگیزشی در رابطه­ی ادراک از جوّ کلاس و تعلل ورزی دانشجویان، فصلنامه روانشناسی تربیتی، 13 (43)، 167-139. doi: 10.22054/jep.2017.7765
مرتضی‌پور، محدثه؛ جناآبادی، حسین و مرزیه، افسانه. (1403). نقش انتظارات معلم ادراک شده در پیش‌بینی درگیری شناختی و خودکارآمدی تحصیلی دانش آموزان دارای اختلالات یادگیری. مجله ناتوانی‌های یادگیری،  13(3)، 58-69. https://doi.org/10.22098/jld.2024.14774.2157
 
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