Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2023, Cilt: 20 Sayı: 55, 561 - 575, 29.09.2023
https://doi.org/10.26466/opusjsr.1345678

Öz

Bu araştırmanın amacı üniversite öğrencilerinin çevrimiçi öğrenme özyeterlikleri ile akademik özyeterlikleri arasındaki ilişkiyi yapısal eşitlik modellemesi kullanarak incelemek ve çevrimiçi öğrenme özyeterliği için istatistiksel olarak anlamlı bir model oluşturabilmektir. Araştırmada, nicel araştırma yöntemlerinden kesitsel tarama modeli kullanılmıştır. Araştırmanın örneklemi 2022-2023 eğitim öğretim yılında, eğitim fakültesinin çeşitli programlarında ve farklı sınıf düzeylerinde öğrenim gören 322 üniversite öğrencisi oluşmaktadır. Araştırmada veri toplama aracı olarak; demografik bilgi formu, akademik özyeterlik ölçeği, çevrimiçi öğrenme ortamlarında öğrenci bağlılık ölçeği, çevrimiçi öğrenme sistemleri kabul ölçeği ve çevrimiçi öğrenmeye yönelik öz-yeterlik ölçeği kullanılmıştır. Araştırmadan elde edilen sonuçlara göre akademik özyeterlik, çevrimiçi öğrenme ortamlarında öğrenci bağlılığı ve çevrimiçi öğrenme sistemleri kabulü üzerinde pozitif ve anlamlı bir etkiye sahipken çevrimiçi öğrenme ortamlarında öğrenci bağlılığı ve çevrimiçi öğrenme sistemleri kabulü ise çevrimiçi öğrenme özyeterliği üzerinde pozitif ve anlamlı bir etkiye sahiptir. Ayrıca akademik özyeterlik, çevrimiçi öğrenme ortamlarında öğrenci bağlılığı için çevrimiçi öğrenme ortamlarında öğrenci bağlılığı ise çevrimiçi öğrenme özyeterliği için daha güçlü bir yordayıcıdır.

Kaynakça

  • Alpaslan, M. M., & Ulubey, Ö. (2021). Examining the relations emotions, motivation, classroom engagement and achievement in mathematics. International Journal of Research in Education and Science 7(4), 1042-1057. https://doi.org/10.46328/ijres.1953
  • Allen, M., Bourhis, J., Burrell, N., & Mabry, E. (2002). Comparing student satisfaction with distance education to traditional classrooms in higher education: a meta-analysis. American Journal of Distance Education, 16(2), 83-97. https://doi.org/10.1207/S15389286AJDE1602_3
  • Alqurashi, E. (2016). Self-efficacy in online learning environments: A literature review. Contemporary Issues in Education Research (CIER), 9(1), 45-52. https://doi.org/10.19030/cier.v9i1.9549
  • Arbaugh, J. B. (2000). Virtual classroom characteristics and student satisfaction with internet-based MBA courses. Journal of management education, 24(1), 32-54. https://doi.org/10.1177/105256290002400104
  • Bakır, E. (2022). Modeling students' achievement emotions, emotion regulation strategies and engagement in online learning environments [Unpublished Doctoral Dissertation]. Hacettepe University.
  • Bandura, A. (1994). Self-efficacy. Ramachaudran, V. S. (Ed.). In Encyclopedia of human behavior (pp.71-81). Academic Press.
  • Bandura, A. (1997). Self-efficacy: The exercise of control. W.H. Freeman and Company.
  • Bandura, A. (2010). Self-Efficacy. The Corsini Encyclopedia of Psychology. https://doi.org/10.1002/9780470479216.corpsy0836
  • Calaguas, N. P., & Consunji, P. M. P. (2022). A structural equation model predicting adults’ online learning self-efficacy. Education and Information Technologies, 27, 6233-6249. https://doi.org/10.1007/s10639-021-10871-y
  • Carini, R. M., Kuh, G. D., & Klein, S. P. (2006). Student engagement and student learning: Testing the linkages. Research in Higher Education, 47(1), 1-32. https://doi.org/10.1007/s11162-005-8150-9
  • Chemers, M. M., Hu, L., & Garcia, B. F. (2001). Academic self-efficacy and the first-year college student performance and adjustment. Journal of Educational Psychology, 93(1), 55-64. https://doi.org/10.1037/0022-0663.93.1.55
  • Chang, D., & Cheng Chien, W. (2015, April). Determining the relationship between academic self-efficacy and student engagement by meta-analysis. In 2015 International Conference on Education Reform and Modern Management (pp. 142-145). Atlantis Press. https://doi.org/10.2991/ermm-15.2015.37
  • Chyung, S. Y., Moll, A. J., & Berg, S. A. (2010). The role of intrinsic goal orientation, self-efficacy, and e-learning practice in engineering education. Journal of Effective Teaching, 10(1), 22-37. https://files.eric.ed.gov/fulltext/EJ1092160.pdf
  • Creswell, J. W. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative research (4th ed.). Pearson.
  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Lawrence Erlbaum Associates.
  • Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2012). Sosyal bilimler için çok değişkenli istatistik: SPSS ve LISREL uygulamaları (2. baskı). Pegem Akademi.
  • Davis, F.D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results [Unpublished Doctoral Dissertation]. Massachusetts Institute of Technology.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 318-340. https://doi.org/10.2307/249008
  • Deng, W., Lei, W., Guo, X., Li, X., Ge, W., & Hu, W. (2022). Effects of regulatory focus on online learning engagement of high school students: The mediating role of self‐efficacy and academic emotions. Journal of Computer Assisted Learning, 38(3), 707-718. https://doi.org/10.1111/jcal.1264212
  • Ergün, E., & Koçak Usluel, Y. (2015). The Turkish adaptation of student’s engagements scale in online learning environment: A study of validity and reliability. Educational Technology Theory and Practice, 5(1), 20-33. https://toad.halileksi.net/sites/default/files/pdf/cevrimici-ogrenmeye-yonelik-oz-yeterlikolcegi-toad.pdf
  • Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175-191. https://www.psychologie.hhu.de/arbeitsgruppen/allgemeine-psychologie-und-arbeitspsychologie/gpower.html
  • Fraenkel, J. R., & Wallen, N. E. (2009). How to design and evaluate research in education (7th ed.). McGraw Hill Higher Education.
  • Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of educational research, 74(1), 59-109. https://doi.org/10.3102/00346543074001059
  • Freund, R., & Littell, R. (2000). SAS system for regression. John Wiley & Sons.
  • George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference: 11.0 update (4th ed.). Allyn & Bacon. Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E., & Tatham, R.L. (2005). Multivariate Data Analysis (6th ed.). Pearson Education.
  • Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414-433. https://doi.org/10.1007/s11747-011- 0261-6
  • Homoki, E., Nyitrai, T., & Makó, Z. (2023). Online educational experiences in some majors of Eszterházy Károly University. Acta Educationis Generalis, 13(2), 82-95. https://doi.org/10.2478/atd-2023-0015
  • Ilgaz, H. (2008). The contribution of technology acceptance and community feeling to learner satısfaction in distance education. [Unpublished Master's Dissertation]. Hacettepe University. https://toad.halileksi.net/sites/default/files/pdf/cevrimici-ogrenme-sistemleri-kabulolcegi-toad.pdf
  • Jerusalem, M., & Schwarzer, R. (1981). Fragebogen zur Erfassung von" Selbstwirksamkeit. Skalen zur Befindlichkeit und Persoenlichkeit. In R. Schwarzer (Hrsg.). (Forschungsbericht No. 5). Berlin: Freie Universitaet, Institut fuer Psychologie.
  • Jöreskog, K.G., & Sörbom D. (1988). LISREL 7: A guide to the program and applications. SPSS Inc.
  • Junco, R., Heiberger, G., & Loken, E. (2011). The effect of Twitter on college student engagement and grades. Journal of Computer Assisted Learning, 27(2), 119-132. https://doi.org/10.1111/j.1365-2729.2010.00387.x
  • Kalaycı, Ş. (2010). SPSS uygulamalı çok değişkenli istatistik teknikleri (5. baskı). Asil Yayın Dağıtım.
  • Khine, M. S. (Ed.) (2013). Application of structural equation modeling in educational research and practice. Sense Publishers.
  • Kline, R.B. (2016). Principles and practice of structural equation modeling (4th ed.). The Guilford Press.
  • Koca, M., & Koçak Usluel, Y. K. (2007). Teachers’ acceptance of and intention to use the information and communication technologies. Educational Science & Practice, 6 (11), 3-18. https://web.s.ebscohost.com/ehost/pdfviewer/pdfviewer? vid=0&sid=df302db8-e36f-4afd-bd00-af5400e0e970%40redis
  • Krause, K. L., & Coates, H. (2008). Students’ engagement in first‐year university. Assessment & Evaluation in Higher Education, 33(5), 493-505. https://doi.org/10.1080/02602930701698892 Lai, H. J. (2011). The influence of adult learners' self-directed learning readiness and network literacy on online learning effectiveness: A study of civil servants in Taiwan. Journal of Educational Technology & Society, 14(2), 98-106. https://www.jstor.org/stable/jeductechsoci.14.2.98
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A New Perspective to University Students' Online Learning Self-Efficacy: A Structural Equation Modeling

Yıl 2023, Cilt: 20 Sayı: 55, 561 - 575, 29.09.2023
https://doi.org/10.26466/opusjsr.1345678

Öz

The aim of this paper is to examine the relationship between university students' online learning self-efficacy and academic self-efficacy using structural equation modeling and to create a statistically significant model for online learning self-efficacy. In the study, the cross-sectional survey model, one of the quantitative research methods, was used. The sample of the study consists of 322 university students studying in various programs and at different grade levels in the faculty of education in the 2022-2023 academic year. Demographic information form, academic self-efficacy scale, student’s engagement scale in online learning environments, online learning systems acceptance scale and online learning self-efficacy scale were used as data collection tools. The results obtained from the study indicated that academic self-efficacy had a positive and significant effect on student’s engagement in online learning environments and online learning systems acceptance, while student’s engagement in online learning environments and online learning systems acceptance had a positive and significant effect on online learning self-efficacy. In addition, academic self-efficacy was a stronger predictor for student’s engagement in online learning environments, and student’s engagement in online learning environments was a stronger predictor for online learning self-efficacy.

Kaynakça

  • Alpaslan, M. M., & Ulubey, Ö. (2021). Examining the relations emotions, motivation, classroom engagement and achievement in mathematics. International Journal of Research in Education and Science 7(4), 1042-1057. https://doi.org/10.46328/ijres.1953
  • Allen, M., Bourhis, J., Burrell, N., & Mabry, E. (2002). Comparing student satisfaction with distance education to traditional classrooms in higher education: a meta-analysis. American Journal of Distance Education, 16(2), 83-97. https://doi.org/10.1207/S15389286AJDE1602_3
  • Alqurashi, E. (2016). Self-efficacy in online learning environments: A literature review. Contemporary Issues in Education Research (CIER), 9(1), 45-52. https://doi.org/10.19030/cier.v9i1.9549
  • Arbaugh, J. B. (2000). Virtual classroom characteristics and student satisfaction with internet-based MBA courses. Journal of management education, 24(1), 32-54. https://doi.org/10.1177/105256290002400104
  • Bakır, E. (2022). Modeling students' achievement emotions, emotion regulation strategies and engagement in online learning environments [Unpublished Doctoral Dissertation]. Hacettepe University.
  • Bandura, A. (1994). Self-efficacy. Ramachaudran, V. S. (Ed.). In Encyclopedia of human behavior (pp.71-81). Academic Press.
  • Bandura, A. (1997). Self-efficacy: The exercise of control. W.H. Freeman and Company.
  • Bandura, A. (2010). Self-Efficacy. The Corsini Encyclopedia of Psychology. https://doi.org/10.1002/9780470479216.corpsy0836
  • Calaguas, N. P., & Consunji, P. M. P. (2022). A structural equation model predicting adults’ online learning self-efficacy. Education and Information Technologies, 27, 6233-6249. https://doi.org/10.1007/s10639-021-10871-y
  • Carini, R. M., Kuh, G. D., & Klein, S. P. (2006). Student engagement and student learning: Testing the linkages. Research in Higher Education, 47(1), 1-32. https://doi.org/10.1007/s11162-005-8150-9
  • Chemers, M. M., Hu, L., & Garcia, B. F. (2001). Academic self-efficacy and the first-year college student performance and adjustment. Journal of Educational Psychology, 93(1), 55-64. https://doi.org/10.1037/0022-0663.93.1.55
  • Chang, D., & Cheng Chien, W. (2015, April). Determining the relationship between academic self-efficacy and student engagement by meta-analysis. In 2015 International Conference on Education Reform and Modern Management (pp. 142-145). Atlantis Press. https://doi.org/10.2991/ermm-15.2015.37
  • Chyung, S. Y., Moll, A. J., & Berg, S. A. (2010). The role of intrinsic goal orientation, self-efficacy, and e-learning practice in engineering education. Journal of Effective Teaching, 10(1), 22-37. https://files.eric.ed.gov/fulltext/EJ1092160.pdf
  • Creswell, J. W. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative research (4th ed.). Pearson.
  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Lawrence Erlbaum Associates.
  • Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2012). Sosyal bilimler için çok değişkenli istatistik: SPSS ve LISREL uygulamaları (2. baskı). Pegem Akademi.
  • Davis, F.D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results [Unpublished Doctoral Dissertation]. Massachusetts Institute of Technology.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 318-340. https://doi.org/10.2307/249008
  • Deng, W., Lei, W., Guo, X., Li, X., Ge, W., & Hu, W. (2022). Effects of regulatory focus on online learning engagement of high school students: The mediating role of self‐efficacy and academic emotions. Journal of Computer Assisted Learning, 38(3), 707-718. https://doi.org/10.1111/jcal.1264212
  • Ergün, E., & Koçak Usluel, Y. (2015). The Turkish adaptation of student’s engagements scale in online learning environment: A study of validity and reliability. Educational Technology Theory and Practice, 5(1), 20-33. https://toad.halileksi.net/sites/default/files/pdf/cevrimici-ogrenmeye-yonelik-oz-yeterlikolcegi-toad.pdf
  • Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175-191. https://www.psychologie.hhu.de/arbeitsgruppen/allgemeine-psychologie-und-arbeitspsychologie/gpower.html
  • Fraenkel, J. R., & Wallen, N. E. (2009). How to design and evaluate research in education (7th ed.). McGraw Hill Higher Education.
  • Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of educational research, 74(1), 59-109. https://doi.org/10.3102/00346543074001059
  • Freund, R., & Littell, R. (2000). SAS system for regression. John Wiley & Sons.
  • George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference: 11.0 update (4th ed.). Allyn & Bacon. Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E., & Tatham, R.L. (2005). Multivariate Data Analysis (6th ed.). Pearson Education.
  • Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414-433. https://doi.org/10.1007/s11747-011- 0261-6
  • Homoki, E., Nyitrai, T., & Makó, Z. (2023). Online educational experiences in some majors of Eszterházy Károly University. Acta Educationis Generalis, 13(2), 82-95. https://doi.org/10.2478/atd-2023-0015
  • Ilgaz, H. (2008). The contribution of technology acceptance and community feeling to learner satısfaction in distance education. [Unpublished Master's Dissertation]. Hacettepe University. https://toad.halileksi.net/sites/default/files/pdf/cevrimici-ogrenme-sistemleri-kabulolcegi-toad.pdf
  • Jerusalem, M., & Schwarzer, R. (1981). Fragebogen zur Erfassung von" Selbstwirksamkeit. Skalen zur Befindlichkeit und Persoenlichkeit. In R. Schwarzer (Hrsg.). (Forschungsbericht No. 5). Berlin: Freie Universitaet, Institut fuer Psychologie.
  • Jöreskog, K.G., & Sörbom D. (1988). LISREL 7: A guide to the program and applications. SPSS Inc.
  • Junco, R., Heiberger, G., & Loken, E. (2011). The effect of Twitter on college student engagement and grades. Journal of Computer Assisted Learning, 27(2), 119-132. https://doi.org/10.1111/j.1365-2729.2010.00387.x
  • Kalaycı, Ş. (2010). SPSS uygulamalı çok değişkenli istatistik teknikleri (5. baskı). Asil Yayın Dağıtım.
  • Khine, M. S. (Ed.) (2013). Application of structural equation modeling in educational research and practice. Sense Publishers.
  • Kline, R.B. (2016). Principles and practice of structural equation modeling (4th ed.). The Guilford Press.
  • Koca, M., & Koçak Usluel, Y. K. (2007). Teachers’ acceptance of and intention to use the information and communication technologies. Educational Science & Practice, 6 (11), 3-18. https://web.s.ebscohost.com/ehost/pdfviewer/pdfviewer? vid=0&sid=df302db8-e36f-4afd-bd00-af5400e0e970%40redis
  • Krause, K. L., & Coates, H. (2008). Students’ engagement in first‐year university. Assessment & Evaluation in Higher Education, 33(5), 493-505. https://doi.org/10.1080/02602930701698892 Lai, H. J. (2011). The influence of adult learners' self-directed learning readiness and network literacy on online learning effectiveness: A study of civil servants in Taiwan. Journal of Educational Technology & Society, 14(2), 98-106. https://www.jstor.org/stable/jeductechsoci.14.2.98
  • Law, K. M., Lee, V. C., & Yu, Y. T. (2010). Learning motivation in e-learning facilitated computer programming courses. Computers & Education, 55(1), 218-228. https://doi.org/10.1016/j.compedu.2010.01.007
  • Lee, J. W., & Mendlinger, S. (2011). Perceived self-efficacy and its effect on online learning acceptance and student satisfaction. Journal of Service Science and Management, 4(3), 243-252. https://doi.org/10.4236/jssm.2011.43029
  • Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 40(3), 191-204. https://doi.org/10.1016/S0378-7206(01)00143-4
  • Lim, K., Kang, M., & Park, S. Y. (2016). Structural relationships of environments, individuals, and learning outcomes in Korean online university settings. International Review of Research in Open and Distributed Learning, 17(4), 315-330. https://doi.org/10.19173/irrodl.v17i4.2500
  • Lu, Y., Hong, X., & Xiao, L. (2022). Toward high-quality adult online learning: A systematic review of empirical studies. Sustainability, 14(4), 2257. https://doi.org/10.3390/su14042257
  • Margolis, H., & McCabe, P. P. (2004). Self-efficacy: A key to improving the motivation of struggling learners. The Clearing House, 77(6), 241-249. https://doi.org/10.1080/10459880309603362
  • Means, B., Toyama, Y., Murphy, R., Bakia, M., & Jones, K. (2009). Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies. https://repository.alt.ac.uk/629/1/US_DepEdu_Final_report_2009.pdf
  • Ministry of National Education (MoNE) (2020, July 20). General competencies of the teaching profession. https://oygm.meb.gov.tr/meb_iys_dosyalar/2017_12/11115355_YYRETMENLYK_MESLEYY_GENEL_YETERLYKLERY.pdf
  • Nielsen, T., Dammeyer, J., Vang, M. L., & Makransky, G. (2018). Gender fairness in self-efficacy? A Rasch-based validity study of the General Academic Self-efficacy scale (GASE). Scandinavian Journal of Educational Research, 62(5), 664-681. https://doi.org/10.1080/00313831.2017.1306796
  • O’Brien, R. M. (2007). A caution regarding rules of thumb for variance inflation factors. Quality & quantity, 41(5), 673-690. https://doi.org/10.1007/s11135-006-9018-6
  • Oriol-Granado, X., Mendoza-Lira, M., Covarrubias-Apablaza, C. G., & Molina-Lopez, V. M. (2017). Positive emotions, autonomy support and academic performance of university students: The mediating role of academic engagement and self-efficacy. Revista de Psicodidactica, 22(1), 45-53. https://doi.org/10.1387/RevPsicodidact.14280
  • Pearl, J. (2012). The causal foundations of structural equation modeling. In R. H. Hoyle (Ed.), Handbook of structural equation modeling (pp. 68-91). The Guilford Press.
  • Peechapol, C., Na-Songkhla, J., Sujiva, S., & Luangsodsai, A. (2018). An exploration of factors influencing self-efficacy in online learning: A systematic review. International Journal of Emerging Technologies in Learning, 13(09), 64-86 https://onliejour.journals.publicknowledgeproject.org/index.php/i-jet/article/viewFile/8351/5150
  • Pintrich, P. R., & de Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82(1), 33-40. https://doi.org/10.1037/0022-0663.82.1.33
  • Prior, D. D., Mazanov, J., Meacheam, D., Heaslip, G., & Hanson, J. (2016). Attitude, digital literacy and self efficacy: Flow-on effects for online learning behavior. The Internet and Higher Education, 29, 91-97. https://doi.org/10.1016/j.iheduc.2016.01.001
  • Rodríguez-Muñoz, A., Antino, M., Ruiz-Zorrilla, P., & Ortega, E. (2021). Positive emotions, engagement, and objective academic performance: A weekly diary study. Learning and Individual Differences, 92, 102087. https://doi.org/10.1016/j.lindif.2021.102087
  • Schunk, D. H. (1985). Self-efficacy and classroom learning. Psychology in the Schools, 22(2), 208-223. https://doi.org/10.1002/1520-6807(198504)22:2<208::AID-PITS2310220215>3.0.CO;2-7
  • Schunk, D. H., & Pajares, F. (2009). Self-efficacy theory. In K. R. Wentzel & A. Wigfield (Eds.), Handbook of motivation at school (pp. 35-53). Routledge.
  • Shevlin, M., & Miles, J. N. (1998). Effects of sample size, model specification and factor loadings on the GFI in confirmatory factor analysis. Personality and Individual differences, 25(1), 85-90. https://doi.org/10.1016/S0191-8869(98)00055-5
  • Simándi, S. (2017). Study circles in online learning environment in the spirit of learning-centered approach. Acta Educationis Generalis,7(2), 96-104. https://doi.org/10.1515/atd-2017-0017
  • Solberg, V. S., O'Brien, K., Villareal, P., Kennel, R., & Davis, B. (1993). Self-efficacy and Hispanic college students: Validation of the college self-efficacy instrument. Hispanic Journal of Behavioral Sciences, 15(1), 80-95. https://doi.org/10.1177/07399863930151004
  • Skinner, E. A., & Belmont, M. J. (1993). Motivation in the classroom: Reciprocal effect of teacher behavior and student engagement across the school year. Journal of Educational Psychology, 85(4), 571-581. https://doi.org/10.1037/0022-0663.85.4.571
  • Sun, J. C.Y., & Rueda, R. (2012). Situational interest, computer self-efficacy and selfregulation: Their impact on student engagement in distance education. British Journal of Educational Technology, 43(2), 191-204. https://doi.org/10.1111/j.1467-8535.2010.01157.x
  • Şahin, I., & Shelley, M. (2008). Considering students’ perceptions: The distance education student satisfaction model. Educational Technology & Society, 11(3), 216-223. https://www.jstor.org/stable/jeductechsoci.11.3.216
  • Tabachnick, B. G., & Fidell, L.S. (2013). Using multivariate statistics (6th ed.). Pearson.
  • Tang, X., Wang, M. T., Parada, F., & Salmela-Aro, K. (2021). Putting the goal back into grit: Academic goal commitment, grit, and academic achievement. Journal of Youth and Adolescence, 50(3), 470-484. https://doi.org/10.1007/s10964-020-01348-1
  • Topal, M. (2020). The effect of online learning enhanced with gamification on student’s engagement to online learning environment, academic achievement and learning motivation. [Unpublished Doctoral Dissertation]. Sakarya University.
  • Tsai, C. C., Chuang, S. C., Liang, J. C., & Tsai, M. J. (2011). Self-efficacy in internet-based learning environments: A literature review. Journal of Educational Technology & Society, 14(4), 222-240. https://www.jstor.org/stable/pdf/jeductechsoci.14.4.222.Pdf
  • Yılmaz, M., Gürçay, D., & Ekici, G. (2007). Adaptation of the academic self-efficacy scale to Turkish. Hacettepe University Journal of Education, 33, 253-259. http://efdergi.hacettepe.edu.tr/shw_artcl-1047.html
  • Zimmerman, B. J. (1995). Self-efficacy and educational development. Self-efficacy in changing societies, 1(1), 202-231.
  • Zimmerman, B. J. (1995). Self-efficacy and educational development. Bandura, A. (Ed.), In Self-Efficacy in changing societies (pp.202-231). Cambridge University Press.
  • Zimmerman, W. A., & Kulikowich, J. M. (2016). Online learning self-efficacy in students with and without online learning experience. American Journal of Distance Education, 30(3), 180-191. https://doi.org/10.1080/08923647.2016.1193801
Toplam 68 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Eğitim Sosyolojisi, Eğitim Psikolojisi
Bölüm Research Articles
Yazarlar

Seda Demir 0000-0003-4230-5593

Erken Görünüm Tarihi 30 Eylül 2023
Yayımlanma Tarihi 29 Eylül 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 20 Sayı: 55

Kaynak Göster

APA Demir, S. (2023). A New Perspective to University Students’ Online Learning Self-Efficacy: A Structural Equation Modeling. OPUS Journal of Society Research, 20(55), 561-575. https://doi.org/10.26466/opusjsr.1345678