METACOGNITIVE AWARENESS, REFLECTIVE THINKING, PROBLEM SOLVING, AND COMMUNITY OF INQUIRY AS PREDICTORS OF ACADEMIC SELF-EFFICACY IN BLENDED LEARNING: A CORRELATIONAL STUDY

Year 2023, Volume: 24 Issue: 1, 20 - 36, 01.01.2023

Fatma Gizem Karaoglan-yılmaz Ahmet Berk Ustun , Ke Zhang Ramazan Yılmaz

https://doi.org/10.17718/tojde.989874

Cited By: 7

Abstract

Blended learning (BL) has been increasingly implemented in higher education, while more research is needed to investigate the role of metacognitive awareness, reflective thinking, problem solving and community of inquiry on academic self-efficacy in BL. This correlational study collected data from 217 undergraduate students in an introductory computer course, using five well-established instruments. The result showed that there was a strong and positive relationship between self-efficacy and metacognitive awareness, reflective thinking and problem solving skills, while there was also a positive moderate relationship between students’ academic self-efficacy and community of inquiry. In addition, the predictive models revealed that metacognitive awareness, reflective thinking, problem solving skills and community of inquiry were the predictors of academic self-efficacy as well as its subdimensions, such as learners’ engagement, social status and cognitive applications. According to the results, this article then discusses the practical and research implications of the study and suggests future research directions.

Keywords

Academic self-efficacy, metacognitive awareness, reflective thinking, problem solving, community of inquiry, blended learning

References

• Adams Becker, S., Cummins, M., Davis, A., Freeman, A., Hall Giesinger, C., and Ananthanarayanan, V. (2017). NMC Horizon Report: 2017 Higher Education Edition. Austin, Texas: The New Media Consortium.
• Agran, M., Blanchard, C., Wehmeyer, M. & Hughes, C. (2002). Increasing the Problem-Solving Skills of Students with Developmental Disabilities Participating in General Education, Remedial and Special Education, 23(5), 279-288.
• Akin, A., Abaci, R., & Cetin, B. (2007). The validity and reliability of the Turkish version of the metacognitive awareness inventory. Kuram ve Uygulamada Eğitim Bilimleri, 7(2), 671-678.
• Al-Qahtani, A. A., & Higgins, S. E. (2013). Effects of traditional, blended and e-learning on students' achievement in higher education. Journal of Computer Assisted Learning, 29(3), 220–234.
• Anderson, T., Rourke, L., Garrison, D. R., & Archer, W. (2001). Assessing teaching presence in a computer conferencing context. Journal of Asynchronous Learning Networks, 5(2), 1–17.
• Bahar, A., & Maker, C. J. (2015). Cognitive Backgrounds of Problem Solving: A Comparison of Open-ended vs. Closed Mathematics Problems. Eurasia Journal of Mathematics, Science & Technology Education, 11(6), 1531–1546.
• Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12: What is involved and what is the role of the computer science education community? ACM Inroads, 2(1), 48–54
• Boelens, R., De Wever, B., & Voet, M. (2017). Four key challenges to the design of blended learning: A systematic literature review. Educational Research Review, 22, 1–18. https://doi.org/10.1016/j.edurev.2017.06.001.
• Bradley, C., Erice, M., Halfer, D., Jordan, K., Lebaugh, D., Opperman, C., & Stephen, J. (2007). The impact of a blended learning approach on instructor and learner satisfaction with preceptor education. Journal for Nurses in Staff Development, 23, 164–170.
• Brown, A. L. (1987). Metacognition, executive control, self-regulation, and other more mysterious mechanisms. In F. E. Weinert, R. H. Kluwe (Eds.), Metacognition, motivation, and understanding (65-116). Hillsdale, New Jersey: Lawrence Erlbaum Associates.
• Cansoy, R., & Türkoglu, M. E. (2017). Examining the Relationship between Pre-Service Teachers' Critical Thinking Disposition, Problem Solving Skills and Teacher Self-Efficacy. International Education Studies, 10(6), 23-35.
• Choy, S. C., Yim, J. S. C., & Tan, P. L. (2020). A Metacognitive Knowledge, Metacognitive Experience, And Its Effects On Learning Outcomes For Stem And Non-Stem Malaysian Students. International Journal of Advanced Research in Education and Society, 2(1), 1-14.
• Çiğdem, H., & Kurt, A. A. (2012). Yansıtıcı düşünme ölçeğinin Türkçeye uyarlanması. Uludağ Üniversitesi Eğitim Fakültesi Dergisi, 25(2), 475-493.
• Creswell, J. W. (2012). Educational Research: Planning, Conducting and Evaluating Quantitative and Qualitative Research. Boston, MA: Pearson.
• Dehghani, M., Jafari-Sani, H., Pakmehr, H. & Malekzadeh, A. (2011). Relationship between Students Critical Thinking and Self-Efficacy Beliefs in Ferdowsi University Of Mashhad, Iran, Procedia Social and Behavioral Sciences, 15, 2952–2955.
• Dewey, J. (1933). How we think. Chicago: Henry Regnery.
• Dwiyogo, W. D. (2018). Developing a blended learning-based method for problem-solving in capability learning. Turkish Online Journal of Educational Technology, 17(1), 51-61.
• Dziuban, C., Graham, C. R., Moskal, P. D., Norberg, A., & Sicilia, N. (2018). Blended learning: the new normal and emerging technologies. International Journal Of Educational Technology in Higher education, 15(1), 1-16.
• Ekici, G. (2012). Akademik öz-yeterlik ölçeği: Türkçeye uyarlama, geçerlik ve güvenirlik çalışması. Hacettepe Üniversitesi Eğitim Fakültesi Dergisi, 2012(43), 174-185.
• Ersözlü, Z. N., & Arslan, M. (2009). The effect of developing reflective thinking on metacognitional awareness at primary education level in Turkey. Reflective Practice,10(5), 683-695. doi: 10.1080/14623940903290752.
• Flavell, J., 1979. Metacognition and cognitive monitoring: A new area of cognitive–developmental inquiry. American Psychologist, 34(10), pp. 906-911.
• Garrison, D. R., & Akyol, Z. (2013). The community of inquiry theoretical framework. In M. G. Moore (Ed.), Handbook of distance education. New York, NY: Routledge.
• Garrison, D. R., Anderson, T., & Archer, W. (2000). Critical inquiry in a text-based environment. The Internet and Higher Education, 2(2–3), 87–105.
• Garrison, D. R., Cleveland-Innes, M., & Fung, T. S. (2010). Exploring causal relationships among teaching, cognitive and social presence: Student perceptions of the community of inquiry framework. The Internet and Higher Education, 13, 31–36.
• Geng, S., Law, K. M., & Niu, B. (2019). Investigating self-directed learning and technology readiness in blending learning environment. International Journal of Educational Technology in Higher Education, 16(1), 17. https://doi.org/10.1007/s10798-018-9462-3
• Graham, C. R., Woodfield, W., & Harrison, J. B. (2013). A framework for institutional adoption and implementation of blended learning in higher education. The Internet and Higher Education, 18, 4-14.
• Jaleel, S. (2016). A Study on the Metacognitive Awareness of Secondary School Students. Universal Journal of Educational Research, 4(1), 165-172.
• Jokinen, P., & Mikkonen, I. (2013). Teachers' experiences of teaching in a blended learning environment. Nurse Education in Practice, 13, 524–528.
• Jonker, H., März, V., & Voogt, J. (2018). Teacher educators’ professional identity under construction: The transition from teaching face-to-face to a blended curriculum. Teaching and Teacher Education, 71, 120–133. https://doi.org/10.1016/j.tate.2017. 12.016.
• Jusoff, K., & Khodabandelou, R. (2009). Preliminary study on the role of social presence in blended learning environment in higher education. International Education Studies, 2(4), 79–83.
• Karaoglan Yilmaz, F. G. (2017). Predictors of community of inquiry in a flipped classroom model. Journal of Educational Technology Systems, 46(1), 87-102.
• Karaoglan Yilmaz, F.G. (2020). Modeling different variables in flipped classrooms supported with learning analytics feedback. Journal of Information and Communication Technologies, 1(2), 78-94.
• Karaoğlan Yılmaz, F. G., Olpak, Y. Z., & Yılmaz, R. (2018). The effect of the metacognitive support via pedagogical agent on self-regulation skills. Journal of Educational Computing Research, 56(2), 159-180.
• Karaoğlan-Yılmaz, F. G., Yılmaz, R., Üstün, A. B, & Keser, H. (2019). Examination of critical thinking standards and academic self-efficacy of teacher candidates as a predictor of metacognitive thinking skills through structural equation modelling. Journal of Theoretical Educational Science, 12(4), 1239-1256.
• Kozikoglu, I. (2019). Investigating Critical Thinking in Prospective Teachers: Metacognitive Skills, Problem Solving Skills and Academic Self-Efficacy. Journal of Social Studies Education Research, 10(2), 111-130.
• Lai, C-L., & G-J Hwang (2016). A self-regulated flipped classroom approach to improving students' learning performance in a mathematics course. Computers & Education, 100, 126-140. https://doi.org/10.1016/j.compedu.2016.05.006
• Lesh, R., & Zawojewski, J. (2007). Problem-solving and modeling. In F. Lester (Ed.), Second handbook of research on mathematics teaching and learning (pp. 763–804). Reston: NCTM.
• Li, C., He, J., Yuan, C., Chen, B., & Sun, Z. (2019). The effects of blended learning on knowledge, skills, and satisfaction in nursing students: A meta-analysis. Nurse education today, 82, 51-57.
• Maza, E. M. T., Lozano, M. T. G., Alarcón, A. C. C., Zuluaga, L. M., & Fadul, M. G. (2016). Blended learning supported by digital technology and competency-based medical education: a case study of the social medicine course at the Universidad de los Andes, Colombia. International Journal of Educational Technology in Higher Education, 13(1), 27. https://doi.org/10.1186/s41239-016- 0027-9
• Namaziandost, E., Çakmak, F. (2020). An account of EFL learners’ self-efficacy and gender in the Flipped Classroom Model. Education and Information Technology, 25, 4041–4055. https://doi.org/10.1007/s10639-020-10167-7
• Öztürk, E. (2009). Adaptation of the classroom community index: the validity and reliability study. Hacettepe University Journal of Education, 36, 193-252.
• Pallant, J. (2001). SPSS: Survival manual. Canberra: McPherson.
• Porter, W. W., Graham, C. R., Spring, K. A., & Welch, K. R. (2014). Blended learning in higher education: Institutional adoption and implementation. Computers & Education, 75, 185–195. https://doi.org/10.1016/j.compedu.2014.02.011.
• Rafiola, R., Setyosari, P., Radjah, C., & Ramli, M. (2020). The Effect of Learning Motivation, Self-Efficacy, and Blended Learning on Students’ Achievement in The Industrial Revolution 4.0. International Journal of Emerging Technologies in Learning, 15(8), 71-82.
• Ramirez-Arellano, A., Bory-Reyes, J., & Hernández-Simón, L. M. (2019). Emotions, motivation, cognitive–metacognitive strategies, and behavior as predictors of learning performance in blended learning. Journal of Educational Computing Research, 57(2), 491-512.
• Rasheed, R. A., Kamsin, A., & Abdullah, N. A. (2020). Challenges in the online component of blended learning: A systematic review. Computers & Education, 144, 103701.
• Robbins, S. B., Lauver, K., Le, H., Davis, D., Langley, R., & Carlstrom, A. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological bulletin, 130(2), 261.
• Roick, J., & Ringeisen, T. (2017). Self-efficacy, test anxiety, and academic success: A longitudinal validation. International Journal of Educational Research, 83, 84-93.
• Rovai, A. P. (2002). Sense of community, perceived cognitive learning, and persistence in asynchronous learning networks. The Internet and Higher Education, 5(4), 319–332.
• Sadeghi, R., Sedaghat, M. M., & Ahmadi, F. S. (2014). Comparison of the effect of lecture and blended teaching methods on students’ learning and satisfaction. Journal of advances in medical education & professionalism, 2(4), 146.
• Sahin, N., Sahin, N. H., & Heppner, P. P. (1993). Psychometric properties of the problem solving inventory in a group of Turkish university students. Cognitive Therapy and Research, 17(4), 379-396.
• Schön, D. (1987). Educating the reflective practitioner: Toward a new design for teaching and learning in the professions. San Francisco: Jossey Bass.
• Shea, P., & Bidjerano, T. (2010). Learning presence: Towards a theory of self-efficacy, self-regulation, and the development of a communities of inquiry in online and blended learning environments. Computers & Education, 55(4), 1721-1731.
• Uluçinar Sagir, S., Aslan, O., Bertiz, H., & Öner Armagan, F. (2016). Investigation of the Relationship between Pre-Service Science Teachers' Perceived Self-Efficacy in Science Teaching and Disposition toward Reflective Thinking. European Journal of Science and Mathematics Education, 4(3), 331-344.
• Ustun, A. B., & Tracey, M. W. (2020). An effective way of designing blended learning: A three phase design-based research approach. Education and Information Technologies, 25, 1529–1552. https://doi.org/10.1007/s10639-019-09999-9
• Ustun, A. B., & Tracey, M. W. (2021). An innovative way of designing blended learning through design-based research in higher education. Turkish Online Journal of Distance Education, 22(2), 126-146.
• Ustun, A. B., Karaoglan Yilmaz, F. G. K., & Yilmaz, R. (2021). Investigating the role of accepting learning management system on students’ engagement and sense of community in blended learning. Education and Information Technologies, 26, 4751–4769. https://doi.org/10.1007/s10639-021-10500-8
• Van der Schaaf, M., Baartman, L., Prins, F., Oosterbaan, A., & Schaap, H. (2013). Feedback dialogues that stimulate students' reflective thinking. Scandinavian Journal of Educational Research, 57(3), 227- 245. doi:10.1080/00313831.2011.628693.
• van Velzen, J. H. (2016). Measuring senior high school students’ self- induced self-reflective thinking. The Journal of Educational Research, 110 (5), 495-502. doi:10.1080/00220671.2015.1129596
• Yen, S. C., Lo, Y., Lee, A., & Enriquez, J. (2018). Learning online, offline, and in-between: Comparing student academic outcomes and course satisfaction in face-to-face, online, and blended teaching modalities. Education and Information Technologies, 23(5), 2141–2153.
• Yılmaz, R. (2020). Enhancing community of inquiry and reflective thinking skills of undergraduates through using learning analytics‐based process feedback. Journal of Computer Assisted Learning, 36(6), 909-921.