نقش فراشناخت، فراحافظه و فراهیجان در پیش‌بینی یادگیری خودراهبر دانش‌آموزان

محورهای موضوعی : روانشناسی تربیتی

مهسا اعلم‌الهدی ¹ , علی زینالی ²

1 - دانشجوی کارشناس ارشد روانشناسی تربیتی، گروه روانشناسی، واحد ارومیه، دانشگاه آزاد اسلامی، ارومیه، ایران
2 - دانشیار، گروه روانشناسی، واحد خوی، دانشگاه آزاد اسلامی، خوی، ایران

تاریخ دریافت : 1400/04/28 تاریخ پذیرش : 1400/04/28 تاریخ انتشار : 1400/03/01

کلید واژه: فراحافظه, فراشناخت, یادگیری خودراهبر, فراهیجان,

چکیده مقاله :

هدف این پژوهش تعیین نقش فراشناخت، فراحافظه و فراهیجان در پیش‌بینی یادگیری خودراهبر دانش‌آموزان بود. روش پژوهش مقطعی از نوع همبستگی بود. جامعه پژوهش همه دانش‌آموزان دوره دوم متوسطه شهر ارومیه در سال تحصیلی 99-1398 بودند. نمونه پژوهش 400 دانش‌آموز بودند که با روش نمونه‌گیری خوشه‌ای چندمرحله‌ای انتخاب شدند. ابزارهای پژوهش سیاهه فراشناخت اونیل و عابدی (1996)، پرسشنامه فراحافظه ترویر و ریچ (2002)، پرسشنامه فراهیجان میتمانسگروبر و همکاران (2009) و مقیاس یادگیری خودراهبر فیشر و همکاران (2001) بودند. داده‌ها با روش‌های ضرایب همبستگی پیرسون و رگرسیون چندگانه با مدل همزمان در نرم‌افزار SPSS-19 تحلیل شدند. یافته‌ها نشان داد که فراشناخت، فراحافظه و فراهیجان مثبت با یادگیری خودراهبر رابطه مثبت و معنادار و فراهیجان منفی با یادگیری خودراهبر رابطه منفی و معنادار داشت. همچنین، متغیرهای فراشناخت، فراحافظه و فراهیجان به‌طورمعناداری توانستند 8/40 درصد از تغییرات یادگیری خودراهبر دانش‌آموزان را پیش‌بینی کنند و در این پیش‌بینی نقش فراحافظه بیشتر از سایر متغیرها بود (01/0>P). با توجه به نتایج پژوهش حاضر، برای بهبود یادگیری خودراهبر دانش‌آموزان می‌توان برنامه‌هایی برای افزایش فراشناخت، فراحافظه و فراهیجان مثبت و کاهش فراهیجان منفی طراحی و از طریق کارگاه‌های آموزشی آنها را اجرا کرد.

چکیده انگلیسی:

The aim of this research was determine the role of metacognition, metamemory and meta-emotion in predicting students' self-directed learning. The research method was cross-sectional from type of correlation. The research population was all high school students of Urmia city in the 2019-2020 academic years. The research sample was 400 students who were selected by multi-stage cluster sampling method. The research tools were the O'Neill & Abedi metacognition inventory (1996), Troyer & Rich metamemory questionnaire (2002), Mitmansgruber & et al meta-emotion questionnaire (2009) and Fisher & et al self-directed learning scale (2001). Data were analyzed by Pearson correlation coefficient and multiple regression with enter model methods in SPSS-19 software. The findings showed that metacognition, metamemory and positive meta-emotion had a positive and significant relationship with self-directed learning and negative meta-emotion had a negative and significant relationship with self-directed learning. Also, the variables of metacognition, metamemory and meta-emotion significantly could predicted 40.8 percent of variance of students' self-directed learning and in this predicting the role of metamemory was higher than other variables (p < 0.01). According to the results of the present study, to improve students' self-directed learning, can be designed programs to increase metacognition, metamemory and positive meta-emotion and decrease negative meta-emotion and implement them through workshops.

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Cottini, M., Basso, D., & Palladino, P. (2018). The role of declarative and procedural metamemory in event-based prospective memory in school-aged children. Journal of Experimental Child Psychology, 166, 17-33.

Favaretto, E., Bedani, F., Offredi, A., Schroffenegger, M., Sassaroli, S., Ruggiero, G., & et al. (2020). Metacognitions and repetitive negative thinking in bipolar disorder and healthy controls: A comparative study. Journal of Affective Disorders, 276, 152-158.

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Kumar, J., Singh, A. K., & Buyya, R. (2021). Self-directed learning based workload forecasting model for cloud resource management. Information Sciences, 543: 345-366.

Lalitha, T. B., & Sreeja, P. S. (2020). Personalised self-directed learning recommendation system. Procedia Computer Science, 171: 583-592.

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O'neill, H. F., & Abedi. J. (1996). Reliability and validity of a state metacognitive inventory: Potential for alternative assessment. The Journal of EducationalResearch, 89(4): 234-245.

Price, J., & Harrison, A. (2017). Examining what prestudy and immediate judgments of learning reveal about the bases of metamemory judgments. Journal of Memory and Language, 94: 177-194.

Rager, K. B. (2009). I feel, therefore I learn: The role of emotion in self-directed learning. New Horizons in Adult Education and Human Resource Development, 23(2): 22-33.

Rahimi, M., & Dorbidi, M. (2018). The mediating role of cognitive engagement in the Effect of of students’ meta-memory dimensions on test anxiety in university students. Journal of New Educational Approaches, 13(2): 21-37 [In Persian]

Rezaei, N., Parsaei, I, Nejati, E., Nikamal, M., & Hashemi Rezini, S. (2014). Psychometric properties of students' meta-emotion scale. Psychological Research, 6(23): 1-12 [In Persian].

Saeid, N., Alinejad, M., & Godarzi, M. (2015). The effects of cognitive and meta-cognitive strategies training on self-directed learning readiness. MEDIA, 6(1): 39-47 [In Persian].

Saenz, G. D., Geraci, L., Miller, T. M., & Tirso, R. (2017). Metacognition in the classroom: The association between students’ exam predictions and their desired grades. Consciousness and Cognition, 51: 125-139.

Sangani, A., Makvandi, B., Asgari, P., & Bakhtiyarpour, S. (2019). Modeling structural relationships of meta-cognitive situations with tendency to virtual networks through mediating of emotional processing in gifted students. Journal of Medical Council of Iran, 37(4): 220-226 [In Persian].

Shaper, M. L., Kuhlmann, B. G., & Bayen, U. J. (2019). Metacognitive expectancy effects in source monitoring: Beliefs, in-the-moment experiences, or both? Journal of Memory and Language, 107: 95-110.

Shojaee, S., Jadidi, H., Moradi, O., & Akbari, M. (2019). Compilation of the test anxiety model based on self-directed learning and metacognitive awareness components by mediating cognitive-emotional ordering strategies. Journal of Analitical-Cognitive Psychology, 10(38): 61-76 [In Persian].

Schweder, S., & Raufelder, D. (2019). Positive emotions, learning behavior and teacher support in self-directed learning during adolescence: Do age and gender matter? Journal of Adolescence, 73: 73-84.

Troyer, A. K., & Rich, J. B. (2002). Psychometric properties of a new metamemory questionnaire for older adults. Journal of Gerontology: Psychological Sciences, 57(1): 19-27.

Vahedi, Sh., & Gharehaghaji, S. (2015). The Model of Self-regulated Learning strategies in Mathematics based on Motivational and Mediating Factors of Academic Emotions. Technology of Instruction and Learning, 1(1): 85-109 [In Persian].

Abili, Kh., Narenji Sani, F., & Mostafavi, Z. (2017). Explanation of self-directed learning based on ICT literacy rate of student's department of engineering sciences e-learning courses about: The university of MehrAlborz. Research in School and Virtual Learning, 5(1): 35-50 [In Persian].

Ahmed, W., Vander Werf, M. P. C., Kuyper, H., & Minnaert, A. (2013). Emotions, self-regulated learning, and achievement in mathematics: A growth curve analysis. Journal of Educational Psychology, 105(1): 150-161.

Bailen, N. H., Wu, H., & Thompson, R. J. (2019). Meta-emotions in daily life: Associations with emotional awareness and depression. Journal of Emotion, 19(5): 776-787.

Cottini, M., Basso, D., & Palladino, P. (2018). The role of declarative and procedural metamemory in event-based prospective memory in school-aged children. Journal of Experimental Child Psychology, 166, 17-33.

Favaretto, E., Bedani, F., Offredi, A., Schroffenegger, M., Sassaroli, S., Ruggiero, G., & et al. (2020). Metacognitions and repetitive negative thinking in bipolar disorder and healthy controls: A comparative study. Journal of Affective Disorders, 276, 152-158.

Fisher, M., King, J., & Tague, G. (2001). Development of a self-directed learning readiness scale for nursing education. Nurse Education Today, 21(7): 516-525.

Ghomi, M., Moslemi, Z., & Mohammadi, S, D. (2016). The relationship between metacognitive strategies with self-directed learning among students of Qom University of Medical Sciences. Educ Strategy Med Sci, 9(4): 248-259 [In Persian].

Havenga, M., Breed, B., Mentz, E., & Govender, D. (2013). Metacognitive and problem-solving skills to promote self-directed learning in computer programming: Teachers' experiences. SA-eDUC Journal, 10(2): 1-14.

Hurrell, K. E., Houwing, F. L., & Hudson, J. L. (2017). Parental meta-emotion philosophy and emotion coaching in families of children and adolescents with an anxiety disorder. Journal of Abnormal Child Psychology, 45(3): 569-582.

Isaacson, R. M., & Fujita, F. (2006). Metacognitive knowledge monitoring and self-regulated learning: Academic success and reflections on learning. Journal of the Scholarship of Teaching and Learning, 6(1): 39-55.

Katz, L. F., Maliken, A. C., & Stettler, N. M. (2012). Parental meta-emotion philosophy: A review of research and theoretical framework. Child Development Perspectives, 6(4): 417-422.

Kawaguchi-Suzuki, M., Fuentes, D. G., Gibbard, R. S., Backus, D., & Marcus, K. (2018). Integration of mentored self-directed learning (MSDL) through both group and individual presentations in an accelerated modified block program. Currents in Pharmacy Teaching and Learning, 10(7): 946-954.

Kim, J. Y., & Lim, K. Y. (2019). Promoting learning in online, ill-structured problem solving: The effects of scaffolding type and metacognition level. Computers & Education, 138: 116-129.

Kumar, J., Singh, A. K., & Buyya, R. (2021). Self-directed learning based workload forecasting model for cloud resource management. Information Sciences, 543: 345-366.

Lalitha, T. B., & Sreeja, P. S. (2020). Personalised self-directed learning recommendation system. Procedia Computer Science, 171: 583-592.

Louws, M. L., Meirink, J. A., VanVeen, K., & VanDriel, J. H. (2017). Teachers' self-directed learning and teaching experience: What, how, and why teachers want to learn. Teaching and Teacher Education, 66: 171-183.

Lundin, N. B., Hochheiser, J., Minor, K. S., Hetrick, W. P., & Lysaker, P. H. (2020). Piecing together fragments: Linguistic cohesion mediates the relationship between executive function and metacognition in schizophrenia. Schizophrenia Research, 215: 54-60.

Markant, D., DuBrow, S., Davachi, L., & Gureckis, T. M. (2014). Deconstructing the effect of self-directed study on episodic memory. Memory & Cognition, 42(8): 1211-1224.

Miceli, M., & Castelfranchi, C. (2019). Meta-emotions and the complexity of human emotional experience. New Ideas in Psychology, 55: 42-49.

Mitmansgruber, H., Beck, T. N., Hofer, S., & Schubler, G. (2009). When you don’t like what you feel: Experiential avoidance, mindfulness and meta-emotion in emotion regulation. Personality and Individual Differences, 46(4): 448-453.

Norman, E., & Furnes, B. (2016). The concept of “metaemotion”: What is there to learn from research on metacognition? Emotion Review, 8(2): 187-193.

O'neill, H. F., & Abedi. J. (1996). Reliability and validity of a state metacognitive inventory: Potential for alternative assessment. The Journal of EducationalResearch, 89(4): 234-245.

Price, J., & Harrison, A. (2017). Examining what prestudy and immediate judgments of learning reveal about the bases of metamemory judgments. Journal of Memory and Language, 94: 177-194.

Rager, K. B. (2009). I feel, therefore I learn: The role of emotion in self-directed learning. New Horizons in Adult Education and Human Resource Development, 23(2): 22-33.

Rahimi, M., & Dorbidi, M. (2018). The mediating role of cognitive engagement in the Effect of of students’ meta-memory dimensions on test anxiety in university students. Journal of New Educational Approaches, 13(2): 21-37 [In Persian]

Rezaei, N., Parsaei, I, Nejati, E., Nikamal, M., & Hashemi Rezini, S. (2014). Psychometric properties of students' meta-emotion scale. Psychological Research, 6(23): 1-12 [In Persian].

Saeid, N., Alinejad, M., & Godarzi, M. (2015). The effects of cognitive and meta-cognitive strategies training on self-directed learning readiness. MEDIA, 6(1): 39-47 [In Persian].

Saenz, G. D., Geraci, L., Miller, T. M., & Tirso, R. (2017). Metacognition in the classroom: The association between students’ exam predictions and their desired grades. Consciousness and Cognition, 51: 125-139.

Sangani, A., Makvandi, B., Asgari, P., & Bakhtiyarpour, S. (2019). Modeling structural relationships of meta-cognitive situations with tendency to virtual networks through mediating of emotional processing in gifted students. Journal of Medical Council of Iran, 37(4): 220-226 [In Persian].

Shaper, M. L., Kuhlmann, B. G., & Bayen, U. J. (2019). Metacognitive expectancy effects in source monitoring: Beliefs, in-the-moment experiences, or both? Journal of Memory and Language, 107: 95-110.

Shojaee, S., Jadidi, H., Moradi, O., & Akbari, M. (2019). Compilation of the test anxiety model based on self-directed learning and metacognitive awareness components by mediating cognitive-emotional ordering strategies. Journal of Analitical-Cognitive Psychology, 10(38): 61-76 [In Persian].

Schweder, S., & Raufelder, D. (2019). Positive emotions, learning behavior and teacher support in self-directed learning during adolescence: Do age and gender matter? Journal of Adolescence, 73: 73-84.

Troyer, A. K., & Rich, J. B. (2002). Psychometric properties of a new metamemory questionnaire for older adults. Journal of Gerontology: Psychological Sciences, 57(1): 19-27.

Vahedi, Sh., & Gharehaghaji, S. (2015). The Model of Self-regulated Learning strategies in Mathematics based on Motivational and Mediating Factors of Academic Emotions. Technology of Instruction and Learning, 1(1): 85-109 [In Persian].