پیش‌بینی روابط بین سبک های یادگیری، سبک های شناختی و پیشرفت تحصیلی در مدارس الکترونیکی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشیار گروه روان‌شناسی، دانشگاه آزاد اسلامی واحد ساری، ساری، ایران

2 مدرس دانشگاه آزاد اسلامی واحد بندرگز، بندرگز، ایران

چکیده

هدف پژوهش حاضر، پیش‌بینی روابط بین سبک‌ های یادگیری، سبک ‌های شناختی و پیشرفت تحصیلی در مدارس الکترونیکی می ‌باشد. روش پژوهش، توصیفی از نوع همبستگی است. در پژوهش حاضر، ۱۵۰ دانش‌آموز پسر سال اول دبیرستان مشغول به تحصیل در مدارس الکترونیکی شهر تهران در سال 1392، از طریق نمونه‌گیری تصادفی خوشه‌ای، به عنوان نمونه انتخاب شده و در پژوهش شرکت کردند. از پرسش‌نامه سبک‌های یادگیری کلب، آزمون شکل‌ های گروهی ویتکین و معدل پایان سال تحصیلی استفاده شد، تا چهار سبک یادگیری (همگرا، واگرا، جذب‌کننده و انطباقی) و دو سبک شناختی (وابسته به زمینه و مستقل از زمینه) و پیشرفت تحصیلی در آزمودنی ‌ها اندازه‌گیری شود. داده‌ ها با استفاده از رگرسیون گام به گام و ضریب همبستگی پیرسون مورد تحلیل قرار گرفت. یافته ‌ها نشان داد که بین سبک ‌های یادگیری و پیشرفت تحصیلی، و بین سبک‌های شناختی و پیشرفت تحصیلی ارتباط معنی‌داری وجود دارد. هم‌چنین، بیشترین سبک یادگیری در دانش‌آموزان، جذب‌کننده (3/51 درصد) و حداقل سبک ترجیح داده شده به عنوان سبک غالب انطباق‌یابنده (۶ درصد) بود. نتایج نشان داد، سبک های یادگیری و سبک‌ های شناختی افراد می ‌توانند به عنوان دو متغیر مهم شناختی در پیشرفت تحصیلی دانش‌آموزان نقش مهمی ایفا کند.

کلیدواژه‌ها


عنوان مقاله [English]

Predicting the Relationship between Learning Styles, Cognitive Styles and Academic Achievement in Electronic Schools

نویسندگان [English]

  • Ramzan Hassanzadeh 1
  • Soraya Ramzanzadeh 2
  • Ghodsieh Ebrahimpour 2
1 Associate Professor, Department of Psychology, Islamic Azad University, Sari Branch, Sari, Iran
2 Instructor, Islamic Azad University, Bandar Gaz Branch, Bandar Gaz, Iran
چکیده [English]

The purpose of this study was to predict the relationship between learning styles, cognitive styles and academic achievement in electronic schools. It was a descriptive correlational study. Participants of this research were 150 first year male students enrolled in electronic schools in Tehran in 2013, who were selected using random cluster sampling method.  They answered the Kolb learning style inventory measuring four learning styles (convergent, divergent, assimilation and adaptation) and Witkin's Group Embedded Figures Test (GEFT) measuring two cognitive styles (field dependence and field independence). The average scores of the students at the end of the school year were also used to measure academic achievement. The data were analyzed using Stepwise Regression and Pearson Correlation Coefficient. The findings revealed a significant relationship between participants' learning styles and academic achievement. There was also a highly positive and statistically significant relationship between their cognitive styles and academic achievement. The style mostly preferred by the students as the dominant style was absorber (51.3%) and the least preferred style was accommodation (6%). The findings also revealed that both learning and cognitive styles could play an important role, as two important variables, in students' academic achievement.

کلیدواژه‌ها [English]

  • learning styles
  • cognitive styles
  • academic achievement
  • electronic schools
  1. Bajraktarevic, N., Hall, W., & Fullick, P. (2003). Incorporating learning styles in hypermedia environment: Empirical evaluation. Proceedings of the workshop on adaptive hypermedia and adaptive web-based system. Nottingham, UK: Eindhoven University.
  2. Bassey, S. W., Umoren, G., & Udida. L. A. (2005). Cognitive style, secondary school student’s attitude and academic performance in chemistry in Akwa Ibom state-Nigeria. Cross River University of Technology, Nigeria., University of Calabar, Nigeria.
  3. Cassidy, S. (2004). Learning styles: An overview of theories, models and measures. Educational Psychology, 24(4), 419-444.
  4. Chen, C. M., Lee, H. M., & Chen, Y. H. (2005). Personalized e-learning system using item response theory. Computers and Education, 44(3), 237-255.
  5. Chen, L. H. (2010). Web-based learning programs: Use by learners with various cognitive styles. Computers & Education, 54, 1028-1035.
  6. Fahy, P., & Mohamed, A. (2006). Students learning style and asynchronous computer-mediated conference (CMC) interaction. American Journal of Agricultural Education, 40, 66-73.
  7. Garcia, P., Amandi, A., Schiaffino, S., & Campo, M. (2007). Evaluating Bayesian networks’ precision for detecting students’ learning styles. Computers & Education, 49(3), 794-808.
  8. Guisande, M. A., Paramo, M. F., Tinajero, C., & Almeida, L. S. (2007). Field Dependence-Independence (FDI) cognitive style an analysis of attentional functioning. Psiciothema, 4, 572-577.
  9. Kobal, D., & Musek, J. (2001). Self-concept & academic achievement: Slovenia and France. Personality and Individual Differences, 30, 887-899.
  10. Kolb, D. A. (1984). Experiential Learning. Englewood Cliffs, NJ. Prentice Hall.
  11. Ling-Hsiu, C. (2010). Web-based learning programs: Use by learners with various cognitive styles. Computers & Education, 54(4), 1028-1035.
  12. Luck, S. C. (1998). The relationship between cognitive style and academic achievement. British Journal of Educational Technology, 29(2), 137-147.
  13. Martin, S. C. (2006). Constructing and maintaining an effective hypertext-based learning environment: Web-based learning and cognitive style. Education Training, 43(2-3), 143-155.
  14. Sadler-Smith, E. (2010). The relationship between learning style and cognitive style. Computers and Education, 30, 609-616.
  15. Schnall, S., & Laird, J. (2007). Facing fear: Expression of fear facilitates processing of emotional information. Social Behavior and Personality, 35(4), 513-524.
  16. Schiaffino, S., Garcia, P., & Amandi, A. (2008). E-teacher: Providing personalized assistance to e-learning students. Computers and Education, 51(4), 1744-1754.
  17. Shahamat, F., Kadivar, P., & ValiAllah, V. (2008). Cognitive styles and self-regulation in computer-assisted learning environment, and its comparison with traditional environments. Education, 94, 41-85. (in Persian).
  18. Srivastava, P. (1997). Cognitive style in educational perspective. New Delhi: Anuol. Guisande
  19. Stash, N., Cristea, A., & de Bra, P. (2006). Adaptation to learning styles in e-learning: Approach evaluation. In T. Reeves & S. Yamashita (Eds.). Proceedings of World Conference on E-learning in Corporate, Government, Healthcare, & Higher Education (pp. 284-291). Chesapeake, VA: AACE Press.
  20. Tseng, C. R., Chu, H. C., Hwang, G. J., & Tsai, C. C. (2008). Development of an adaptive learning system with two sources of personalization information. Computers and Education, 51(2), 776-786.
  21. Wageeh, B., Pillay, H. K., & Raj, L. (1999). Matching cognitive style to computer- based instruction: An approach for enhanced learning in electrical engineering. European Journal of Engineering Education,24(4), 371-383.
  22. Witkin, H. A., Oltman, P. K., & Karp, S. A. (1971). Manual for the embedded figures test, children's embedded figures test, and group embedded figures test. Palo Alto, CA: Consulting Psychologists Press
  23. Yi-Chun, C., Wen-Yan, K., Chih-Ping C., & Chiung-Hui, C. (2009). A learning style classification mechanism for e-learning. Computers & Education, 53(2), 273-285.