Araştırma Makalesi
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Structural Equation Modeling Approach to Determine the Effect of Attitude towards Statistics on Statistical Self-efficacy Belief

Yıl 2022, Cilt: 11 Sayı: 3, 836 - 845, 30.09.2022
https://doi.org/10.17798/bitlisfen.1123197

Öz

In this study, it is aimed to examine the relationship between students' statistical self-efficacy beliefs and their attitudes towards statistics and to propose a structural equation model by identifying the factors affecting them. IBM SPSS and AMOS package program were used in the data analysis. Data were collected from 330 university students who took statistics and biostatistics lessons to form the sample of the study. As a result of the analysis, it was concluded that the self-efficacy beliefs and attitudes towards to statistics lesson of students were at a moderate level. A positive and significant correlation was obtained between statistical self-efficacy belief and attitude. It was determined that statistical attitude explains 33% of the statistical self-efficacy belief. We propose to use modified multi-factor first-order and multi-factor first-order models for statistical self-efficacy belief and attitude levels, respectively. This result was supported with the values of goodness of fit indices.

Kaynakça

  • [1] J. M. Shaughnessy and M. Pfannkuch, “How faithful is old faithful? statistical thinking: a story of variation and prediction,” Math. Teach., vol. 95, no.4, pp. 252–259, 2004.
  • [2] K. Makar and A. Rubin, “A framework for thinking about informal statistical inference,” Stat. Educ. Res. J., vol. 8, no. 1, pp. 82–105, 2022.
  • [3] A. Bandura, “Self-efficacy: toward a unifying theory of behavioral change,” Psychol. Rev., vol. 84, no. 2, pp. 191–215, 1977.
  • [4] B. Akkoyunlu, F. Orhan and A. Umay, “A study on developıng teacher self-efficacy scale for computer teachers,” Hacettepe Univ. J. Educ., vol. 29, no. 29, pp. 1-8, 2005.
  • [5] Z. Gan, G. Hu, W. Wang, H. Nang, and Z. An, “Feedback behaviour and preference in university academic English courses: associations with English language self-efficacy,” Assess. Eval. High. Educ., vol. 46, no. 5, pp. 740–755, 2021.
  • [6] M. B. Smith, Attitude Change International Encyclopedia of the Social Sciences. Crowell Collier and Mac Millan, 1968.
  • [7] E. Aydın and N. E. Sevimli, “An investigation of preservice mathematics teachers’ self-efficacy beliefs and attitudes toward statistics,” Istanbul Sabahattin Zaim Univ. J. Fac. Educ., vol. 1, no. 1, pp. 159–174, 2019.
  • [8] Z. Çam, K. Z. Deniz, A. Kurnaz, and L. Marten, “School burnout: Testing a structural equation model based on percieved social support, perfectionism and stress variables,” Educ. Sci., vol. 39, no. 173, pp. 312–327, 2019.
  • [9] J. Ballantine, X. Guo, and P. Larres, “Psychometric evaluation of the Student Authorship Questionnaire: a confirmatory factor analysis approach,” Stud. High. Educ., vol. 40, no. 4, pp. 596–609, 2015.
  • [10] M. Boyacı and M. B. Özhan, “The role of hope and family relations of school burnout among secondary school students: A structural equation modeling,” Educ. Sci., vol. 43, no. 195, pp. 137-150, 2018.
  • [11] S. A. Kıray, İ. Çelik, and M. H. Çolakoğlu, “TPACK self-efficacy perceptions of science teachers: A structural equation modeling study,” Educ. Sci., vol. 43, no. 195, pp. 253-268, 2018.
  • [12] A. Ç. Kılınç, M. Polatcan, T. Atmaca, and M. Koşar, “Teacher self-efficacy and individual academic optimism as predictors of teacher professional learning: A structural equation modeling,” Educ. Sci., vol. 46, no. 205, pp. 373-394, 2020.
  • [13] M. Aydogmus, “Investigation of the effect of social entrepreneurship on professional attitude and self-efficacy perception: a research on prospective teachers,” Stud. High. Educ., vol. 46, no. 7, pp. 1462–1476, 2021.
  • [14] E. Aydın and N.E. Sevimli, “The adaptation of the “statistics self- efficacy scale to the Turkish,” J. Educ. Humanit., vol. 8, no.16, pp. 44–57, 2017.
  • [15] S. J. Finney and G. Schraw, “Self-efficacy beliefs in college statistics courses,” Contemp. Educ. Psychol., vol. 28, no. 2, pp. 161–186, 2003.
  • [16] M. Yaşar, “İstatistiğe Yönelik Tutum Ölçeği: Geçerlilik ve Güvenirlik Çalışması,” Pamukkale Univ. J. Educ., vol. 02, no. 36, pp. 59–59, 2014.
  • [17] T. Koparan, “Development of an attitude scale towards statistics: a study on reliability and validity,” Karaelmas J. Educ. Sci., vol. 3, pp. 76–86, 2015.
  • [18] A.Altunçekiç, S. Yaman and Ö. Koray, “The research on prospective teachers’ selfefficacy belief level and problem solving skills,” Kastamonu Educ. J., vol. 13, no.1, pp. 93-102, 2005.
  • [19] E. Çakıroğlu and M. Işıksal, “Preservice elementary teachers' attitudes and self-efficacy beliefs toward mathematics,” Educ. Sci., vol. 34, no.151, pp. 132–139, 2009.
  • [20] İ. Uysal and S. Kösemen, “Analysis of the preservice teachers’ general self-esteem beliefs,” J. Res. Educ. Teach., vol. 2, no. 2, pp. 217–226, 2013.
  • [21] R. Aydın, Y. E. Ömür and T. Argon, “Pre-service teachers’ perception of self-efficacy and academic delay of gratification,” J. Educ. Sci., vol. 40, pp. 1–12, 2014.
  • [22] N. Gündüz, “An investigation of the relationship between statistical literacy of primary mathematics teachers and their attitudes towards statistics,” MsC diss., Kocaeli University, Kocaeli. 2014.
  • [23] D. L. Bandalos, K. Yates, and T. Thorndike-Christ, “Effects of math self-concept, perceived self-efficacy, and attributions for failure and success on test anxiety,” J. Educ. Psychol., vol. 87, no. 4, pp. 611–623, 1995.
  • [24] N. Girginer, A. G. Z. Kaygısız and A. G. A. Yalama, “Doğrusal olmayan kanonik korelasyon analizi ile istatistiğe yönelik tutumlarda üniversite öğrencileri arasındaki bireysel farklılıkların incelenmesi,” Istanbul Univ. Economet. Stat., vol. 6, pp. 29–40, 2007, (In Turkish).
  • [25] M. Eskici, “The effectiveness of statistic class averages unit teaching program,” Trakya J. Educ., vol. 3, no. 2, pp. 44–52, 2013.
  • [26] S. Salihova and V. Memmedova, “Students attitudes toward statistics lesson: validity and reliability study,” Academic Sight Int. Refer. Online J., vol. 59, pp. 116–127, 2017.
  • [27] E. Emmioglu Sarikaya, A. Ok, Y. Capa Aydin, and C. Schau, “Turkish version of the Survey of Attitudes toward Statistics: Factorial structure invariance by gender,” Int. J. High. Educ., vol. 7, no. 2, p. 121, 2018.
  • [28] R. Alkan, “Reflections of different practices in introductory statistics courses on the changes in students' attitudes towards statistics,” MsC diss., Tokat Gaziosmanpaşa University, Tokat, 2019.
  • [29] K. Sümbüloğlu and V. Sümbüloğlu, “Sağlık Bilimlerinde Araştırma Yöntemleri,” Hatipoğlu Yayınevi, Ankara, 2013, (In Turkish).
  • [30] M. Norris and L. Lecavalier, “Evaluating the use of exploratory factor analysis in developmental disability psychological research,” J. Autism Dev. Disord., vol. 40, no. 1, pp. 8–20, 2010.
  • [31] Ö. Çokluk, G. Şekercioğlu, Ş. Büyüköztürk, “Sosyal Bilimler İçin Çok Değişkenli İstatistik SPSS ve LISREL Uygulamaları,” Pegem Akademi Yayıncılık, Ankara, 2012.
  • [32] B. M. Byrne, Structural equation modeling with AMOS: Basic concepts, applications, and programming, third edition, 3rd ed. London, England: Routledge, 2016.
  • [33] H. Ayyıldız and E. Cengiz, “Pazarlama modellerinin testinde kullanılabilecek yapısal eşitlik modeli (YEM) üzerine kavramsal bir inceleme,” Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, vol. 11, no. 2, pp. 67-80, 2006.
  • [34] S. Saraçlı and A. Erdoğmuş, “Determining the effects of information security knowledge on information security awareness via structural equation modelings,” Hacet. J. Math. Stat., vol. 48, no. 4, 2018.
  • [35] G. G. Şimşek and F. Noyan, “Structural equation modeling with ordinal variables: a large sample case study,” Qual. Quant., vol. 46, no. 5, pp. 1571–1581, 2012.
  • [36] V. Yilmaz and E. Ari, “The effects of service quality, image, and customer satisfaction on customer complaints and loyalty in high-speed rail service in Turkey: a proposal of the structural equation model,” Transp. Transp. Sci., vol. 13, no. 1, pp. 67–90, 2017.
  • [37] K. A. Bollen, Structural Equations with Latent Variables: Bollen/structural equations with latent variables, 1st ed. Nashville, TN: John Wiley & Sons, 2014.
  • [38] M. E. Civelek, “Essentials of Structural Equation Modeling,” Zea E-Books, 2018.
  • [39] C. Lleras, “Path analysis,” Encyclopedis of Social Measurement, vol. 3, pp. 25-30, 2005.
  • [40] Ö. İ. Güneri, A. Göktaş, and U. Kayalı, “Path analysis and determining the distribution of indirect effects via simulation,” J. Appl. Stat., vol. 44, no. 7, pp. 1181–1210, 2017.
  • [41] K. Schermelleh-Engel, H. Moosbrugger and H. Muller, “Evaluating the fit of structural equation models: tests of significance and descriptive goodness-of-fit measures,” Meth. Psychol. Res. Online, vol. 8, no. 2, pp. 23–74, 2003.
Yıl 2022, Cilt: 11 Sayı: 3, 836 - 845, 30.09.2022
https://doi.org/10.17798/bitlisfen.1123197

Öz

Kaynakça

  • [1] J. M. Shaughnessy and M. Pfannkuch, “How faithful is old faithful? statistical thinking: a story of variation and prediction,” Math. Teach., vol. 95, no.4, pp. 252–259, 2004.
  • [2] K. Makar and A. Rubin, “A framework for thinking about informal statistical inference,” Stat. Educ. Res. J., vol. 8, no. 1, pp. 82–105, 2022.
  • [3] A. Bandura, “Self-efficacy: toward a unifying theory of behavioral change,” Psychol. Rev., vol. 84, no. 2, pp. 191–215, 1977.
  • [4] B. Akkoyunlu, F. Orhan and A. Umay, “A study on developıng teacher self-efficacy scale for computer teachers,” Hacettepe Univ. J. Educ., vol. 29, no. 29, pp. 1-8, 2005.
  • [5] Z. Gan, G. Hu, W. Wang, H. Nang, and Z. An, “Feedback behaviour and preference in university academic English courses: associations with English language self-efficacy,” Assess. Eval. High. Educ., vol. 46, no. 5, pp. 740–755, 2021.
  • [6] M. B. Smith, Attitude Change International Encyclopedia of the Social Sciences. Crowell Collier and Mac Millan, 1968.
  • [7] E. Aydın and N. E. Sevimli, “An investigation of preservice mathematics teachers’ self-efficacy beliefs and attitudes toward statistics,” Istanbul Sabahattin Zaim Univ. J. Fac. Educ., vol. 1, no. 1, pp. 159–174, 2019.
  • [8] Z. Çam, K. Z. Deniz, A. Kurnaz, and L. Marten, “School burnout: Testing a structural equation model based on percieved social support, perfectionism and stress variables,” Educ. Sci., vol. 39, no. 173, pp. 312–327, 2019.
  • [9] J. Ballantine, X. Guo, and P. Larres, “Psychometric evaluation of the Student Authorship Questionnaire: a confirmatory factor analysis approach,” Stud. High. Educ., vol. 40, no. 4, pp. 596–609, 2015.
  • [10] M. Boyacı and M. B. Özhan, “The role of hope and family relations of school burnout among secondary school students: A structural equation modeling,” Educ. Sci., vol. 43, no. 195, pp. 137-150, 2018.
  • [11] S. A. Kıray, İ. Çelik, and M. H. Çolakoğlu, “TPACK self-efficacy perceptions of science teachers: A structural equation modeling study,” Educ. Sci., vol. 43, no. 195, pp. 253-268, 2018.
  • [12] A. Ç. Kılınç, M. Polatcan, T. Atmaca, and M. Koşar, “Teacher self-efficacy and individual academic optimism as predictors of teacher professional learning: A structural equation modeling,” Educ. Sci., vol. 46, no. 205, pp. 373-394, 2020.
  • [13] M. Aydogmus, “Investigation of the effect of social entrepreneurship on professional attitude and self-efficacy perception: a research on prospective teachers,” Stud. High. Educ., vol. 46, no. 7, pp. 1462–1476, 2021.
  • [14] E. Aydın and N.E. Sevimli, “The adaptation of the “statistics self- efficacy scale to the Turkish,” J. Educ. Humanit., vol. 8, no.16, pp. 44–57, 2017.
  • [15] S. J. Finney and G. Schraw, “Self-efficacy beliefs in college statistics courses,” Contemp. Educ. Psychol., vol. 28, no. 2, pp. 161–186, 2003.
  • [16] M. Yaşar, “İstatistiğe Yönelik Tutum Ölçeği: Geçerlilik ve Güvenirlik Çalışması,” Pamukkale Univ. J. Educ., vol. 02, no. 36, pp. 59–59, 2014.
  • [17] T. Koparan, “Development of an attitude scale towards statistics: a study on reliability and validity,” Karaelmas J. Educ. Sci., vol. 3, pp. 76–86, 2015.
  • [18] A.Altunçekiç, S. Yaman and Ö. Koray, “The research on prospective teachers’ selfefficacy belief level and problem solving skills,” Kastamonu Educ. J., vol. 13, no.1, pp. 93-102, 2005.
  • [19] E. Çakıroğlu and M. Işıksal, “Preservice elementary teachers' attitudes and self-efficacy beliefs toward mathematics,” Educ. Sci., vol. 34, no.151, pp. 132–139, 2009.
  • [20] İ. Uysal and S. Kösemen, “Analysis of the preservice teachers’ general self-esteem beliefs,” J. Res. Educ. Teach., vol. 2, no. 2, pp. 217–226, 2013.
  • [21] R. Aydın, Y. E. Ömür and T. Argon, “Pre-service teachers’ perception of self-efficacy and academic delay of gratification,” J. Educ. Sci., vol. 40, pp. 1–12, 2014.
  • [22] N. Gündüz, “An investigation of the relationship between statistical literacy of primary mathematics teachers and their attitudes towards statistics,” MsC diss., Kocaeli University, Kocaeli. 2014.
  • [23] D. L. Bandalos, K. Yates, and T. Thorndike-Christ, “Effects of math self-concept, perceived self-efficacy, and attributions for failure and success on test anxiety,” J. Educ. Psychol., vol. 87, no. 4, pp. 611–623, 1995.
  • [24] N. Girginer, A. G. Z. Kaygısız and A. G. A. Yalama, “Doğrusal olmayan kanonik korelasyon analizi ile istatistiğe yönelik tutumlarda üniversite öğrencileri arasındaki bireysel farklılıkların incelenmesi,” Istanbul Univ. Economet. Stat., vol. 6, pp. 29–40, 2007, (In Turkish).
  • [25] M. Eskici, “The effectiveness of statistic class averages unit teaching program,” Trakya J. Educ., vol. 3, no. 2, pp. 44–52, 2013.
  • [26] S. Salihova and V. Memmedova, “Students attitudes toward statistics lesson: validity and reliability study,” Academic Sight Int. Refer. Online J., vol. 59, pp. 116–127, 2017.
  • [27] E. Emmioglu Sarikaya, A. Ok, Y. Capa Aydin, and C. Schau, “Turkish version of the Survey of Attitudes toward Statistics: Factorial structure invariance by gender,” Int. J. High. Educ., vol. 7, no. 2, p. 121, 2018.
  • [28] R. Alkan, “Reflections of different practices in introductory statistics courses on the changes in students' attitudes towards statistics,” MsC diss., Tokat Gaziosmanpaşa University, Tokat, 2019.
  • [29] K. Sümbüloğlu and V. Sümbüloğlu, “Sağlık Bilimlerinde Araştırma Yöntemleri,” Hatipoğlu Yayınevi, Ankara, 2013, (In Turkish).
  • [30] M. Norris and L. Lecavalier, “Evaluating the use of exploratory factor analysis in developmental disability psychological research,” J. Autism Dev. Disord., vol. 40, no. 1, pp. 8–20, 2010.
  • [31] Ö. Çokluk, G. Şekercioğlu, Ş. Büyüköztürk, “Sosyal Bilimler İçin Çok Değişkenli İstatistik SPSS ve LISREL Uygulamaları,” Pegem Akademi Yayıncılık, Ankara, 2012.
  • [32] B. M. Byrne, Structural equation modeling with AMOS: Basic concepts, applications, and programming, third edition, 3rd ed. London, England: Routledge, 2016.
  • [33] H. Ayyıldız and E. Cengiz, “Pazarlama modellerinin testinde kullanılabilecek yapısal eşitlik modeli (YEM) üzerine kavramsal bir inceleme,” Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, vol. 11, no. 2, pp. 67-80, 2006.
  • [34] S. Saraçlı and A. Erdoğmuş, “Determining the effects of information security knowledge on information security awareness via structural equation modelings,” Hacet. J. Math. Stat., vol. 48, no. 4, 2018.
  • [35] G. G. Şimşek and F. Noyan, “Structural equation modeling with ordinal variables: a large sample case study,” Qual. Quant., vol. 46, no. 5, pp. 1571–1581, 2012.
  • [36] V. Yilmaz and E. Ari, “The effects of service quality, image, and customer satisfaction on customer complaints and loyalty in high-speed rail service in Turkey: a proposal of the structural equation model,” Transp. Transp. Sci., vol. 13, no. 1, pp. 67–90, 2017.
  • [37] K. A. Bollen, Structural Equations with Latent Variables: Bollen/structural equations with latent variables, 1st ed. Nashville, TN: John Wiley & Sons, 2014.
  • [38] M. E. Civelek, “Essentials of Structural Equation Modeling,” Zea E-Books, 2018.
  • [39] C. Lleras, “Path analysis,” Encyclopedis of Social Measurement, vol. 3, pp. 25-30, 2005.
  • [40] Ö. İ. Güneri, A. Göktaş, and U. Kayalı, “Path analysis and determining the distribution of indirect effects via simulation,” J. Appl. Stat., vol. 44, no. 7, pp. 1181–1210, 2017.
  • [41] K. Schermelleh-Engel, H. Moosbrugger and H. Muller, “Evaluating the fit of structural equation models: tests of significance and descriptive goodness-of-fit measures,” Meth. Psychol. Res. Online, vol. 8, no. 2, pp. 23–74, 2003.
Toplam 41 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Araştırma Makalesi
Yazarlar

Hayriye Esra Akyüz 0000-0002-1784-5910

Duygu Topcu 0000-0002-1373-2732

Yayımlanma Tarihi 30 Eylül 2022
Gönderilme Tarihi 30 Mayıs 2022
Kabul Tarihi 23 Eylül 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 11 Sayı: 3

Kaynak Göster

IEEE H. E. Akyüz ve D. Topcu, “Structural Equation Modeling Approach to Determine the Effect of Attitude towards Statistics on Statistical Self-efficacy Belief”, Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, c. 11, sy. 3, ss. 836–845, 2022, doi: 10.17798/bitlisfen.1123197.



Bitlis Eren Üniversitesi
Fen Bilimleri Dergisi Editörlüğü

Bitlis Eren Üniversitesi Lisansüstü Eğitim Enstitüsü        
Beş Minare Mah. Ahmet Eren Bulvarı, Merkez Kampüs, 13000 BİTLİS        
E-posta: fbe@beu.edu.tr