Understanding the Relationship Among Self-efficacy, Utility Value, and the Community of Inquiry Framework in Preservice Teacher Education
School closures during the COVID-19 pandemic have shown the importance of distance education, and teachers have been tasked with designing and delivering online courses in a short amount of time without much preparation or deliberation. As the future generation of teachers, preservice teachers need to be prepared to teach online, and their motivation to do so is a key factor in how successfully they do it. The community of inquiry framework provides researchers and practitioners with a framework for designing and delivering online courses, while self-efficacy and utility value are important motivational constructs predicting future engagement and success in tasks. In this cross-sectional survey study, we investigated preservice teachers’ (n = 344) perceptions of their self-efficacy, utility value, the importance of the three components of the community of inquiry framework: teaching presence, social presence, and cognitive presence. Our results show that overall, preservice teachers had high motivation to teach online and high perceptions of the three presences. Our regression analyses indicated that while preservice teachers’ self-efficacy was a significant predictor of teaching presence, utility value only significantly predicted social presence. We discuss the implications of these findings for teacher education programs, including a holistic approach to teaching online learning and instructional design.
Akcaoglu, M., Rosenberg, J. M., Ranellucci, J., Schwarz, C. V. (2018). Outcomes from a self generated utility value intervention on fifth and sixth-grade students’ value and interest in science. International Journal of Educational Research. 87, 67-77. https://doi.org/10.1016/j.ijer.2017.12.001
Akyol, Z., & Garrison, D. R. (2011). Assessing metacognition in an online community of inquiry. The Internet and higher education, 14(3), 183–190. https://doi.org/10.1016/j.iheduc.2011.01.005
Anderson, S. E., Groulx, J. G., & Maninger, R. M. (2011). Relationships among preservice teachers’ technology-related abilities, beliefs, and intentions to use technology in their future classrooms. Journal of Educational Computing Research, 45(3), 321–338. https://doi.org/10.2190/EC.45.3.d
Anderson, T., Liam, R., Garrison, D. R., & Archer, W. (2001). Assessing teaching presence in a computer conferencing context. Journal of Asynchronous Learning Networks, 5(2), 1–17. https://doi.org/10.24059/olj.v5i2.1875
Arbaugh, J. B., Cleveland-Innes, M., Diaz, S. R., Garrison, D. R., Ice, P., Richardson, J. C., & Swan, K. P. (2008). Developing a community of inquiry instrument: Testing a measure of the community of inquiry framework using a multi-institutional sample. The Internet and Higher Education, 11(3–4), 133–136. https://doi.org/10.1016/j.iheduc.2008.06.003
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall. https://psycnet.apa.org/record/1985-98423-000
Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman. https://psycnet.apa.org/record/1997-08589-000
Bong, M. (2001). Role of self-efficacy and task-value in predicting college students’ course performance and future enrollment intentions. Contemporary Educational Psychology, 26(4), 553–570. https://doi.org/10.1006/ceps.2000.1048
Bozkurt, A., Akgun-Ozbek, E., Yilmazel, S., Erdogdu, E., Ucar, H., Guler, E., Sezgin, S., Karadeniz, A., Sen-Ersoy, N., Goksel-Canbek, N., Dincer, G. D., Ari, S., & Aydin, C. H. (2015). Trends in distance education research: A content analysis of journals 2009–2013. The International Review of Research in Open and Distributed Learning, 16(1), 330–363. https://doi.org/10.19173/irrodl.v16i1.1953
Burgess, M. L., Slate, J. R., Rojas-LeBouef, A., & LaPrairie, K. (2010). Teaching and learning in Second Life: Using the community of inquiry (CoI) model to support online instruction with graduate students in instructional technology. The Internet and Higher Education, 13(1–2), 84–88. https://doi.org/10.1016/j.iheduc.2009.12.003
Busch, T. (1996). Gender, group composition, cooperation, and self-efficacy in computer studies. Journal of Educational Computing Research, 15(2), 125–135. https://doi.org/10.2190/KQJL-RTW1-VVUY-BHLG
Dewey, J. (1959). My pedagogic creed. In L. A. Cremin (Ed.), Dewey on education: Selections. Teachers College Press. https://www.tcpress.com/dewey-on-education-9780807776353
Dewey, J. (1986). Experience and education. The Educational Forum, 50(3), 241–252. https://doi.org/10.1080/00131728609335764
Eccles, J. (1983). Expectancies, values and academic behaviors. Achievement and achievement motives. In J. T. Spence (Ed.), Achievement and Achievement Motives: Psychological and Sociological Approaches (pp. 75-136). W.H. Freeman and Company
Ertmer, P. A., Ottenbreit-Leftwich, A. T., Sadik, O., Sendurur, E., & Sendurur, P. (2012). Teacher beliefs and technology integration practices: A critical relationship. Computers & Education, 59(2), 423–435. https://doi.org/10.1016/j.compedu.2012.02.001
Ferede, T., Melese, E., Tefera, E., & Mossie, A. (2016). Students’ academic self-efficacy viz-a-viz their academic achievement: Jimma and Hawasa University students in focus. Ethiopian Journal of Education and Sciences, 11(2), 1–16. https://www.ajol.info/index.php/ejesc/article/view/153661
Fryer, L. K., & Ainley, M. (2019). Supporting interest in a study domain: A longitudinal test of the interplay between interest, utility-value, and competence beliefs. Learning and Instruction, 60, 252–262. https://doi.org/10.1016/j.learninstruc.2017.11.002
Garrison, D. R. (2009). Communities of inquiry in online learning. In P. L. Rogers, G. A. Berg, J. V. Boettcher, C. Howard, L. Justice, & K. D. Schenk (Eds.), Encyclopedia of distance learning (pp. 352–355). IGI Global.
Garrison, D. R., & Akyol, Z. (2013). The community of inquiry theoretical framework. In M. G. Moore (Ed.), Handbook of Distance Education (pp. 104–120). Routledge. https://www.routledgehandbooks.com/doi/10.4324/9780203803738.ch7
Garrison, D. R., Anderson, T., & Archer, W. (1999). Critical inquiry in a text-based environment: Computer conferencing in higher education. The Internet and Higher Education, 2(2–3), 87–105. https://doi.org/10.1016/S1096-7516(00)00016-6
Garrison, D. R., Anderson, T., & Archer, W. (2001). Critical thinking, cognitive presence, and computer conferencing in distance education. American Journal of Distance Education, 15(1), 7–23. https://doi.org/10.1080/08923640109527071
Garrison, D. R., & Arbaugh, J. B. (2007). Researching the community of inquiry framework: Review, issues, and future directions. The Internet and Higher Education, 10(3), 157–172. https://doi.org/10.1016/j.iheduc.2007.04.001
Garrison, D. R., & Archer, W. (2000). A transactional perspective on teaching and learning: A framework for adult and higher education. Pergamon. https://eric.ed.gov/?id=ED451371
Garrison, D. R., & Cleveland-Innes, M. (2005). Facilitating cognitive presence in online learning: Interaction is not enough. American Journal of Distance Education, 19(3), 133–148. https://doi.org/10.1207/s15389286ajde1903_2
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(1–2), 31–36. https://doi.org/10.1016/j.iheduc.2009.10.002
Hodges, C. B. (2008). Self‐efficacy in the context of online learning environments: A review of the literature and directions for research. Performance Improvement Quarterly, 20(3–4), 7–25. https://doi.org/10.1002/piq.20001
Hulleman, C. S., & Harackiewicz, J. M. (2009). Promoting interest and performance in high school science classes. Science, 326(5958), 1410–1412. https://doi.org/10.1126/science.1177067
Hulleman, C. S., Kosovich, J. J., Barron, K. E., & Daniel, D. B. (2017). Making connections: Replicating and extending the utility value intervention in the classroom. Journal of Educational Psychology, 109(3), 387–404. https://doi.org/10.1037/edu0000146
Joo, Y. J., Lim, K. Y., & Kim, E. K. (2011). Online university students’ satisfaction and persistence: Examining perceived level of presence, usefulness and ease of use as predictors in a structural model. Computers & Education, 57(2), 1654–1664. https://doi.org/10.1016/j.compedu.2011.02.008
Joo, Y. J., Park, S., & Lim, E. (2018). Factors influencing preservice teachers’ intention to use technology: TPACK, teacher self-efficacy, and technology acceptance model. Journal of Educational Technology & Society, 21(3), 48–59. https://www.jstor.org/stable/26458506
Kale U., & Akcaoglu, M. (2018). The role of relevance in future teachers' utility value and interest toward technology. Educational Technology Research & Development. 66(2), 283-311. https://doi.org/10.1007/s11423-017-9547-9.
Kazanidis, I., Pellas, N., Fotaris, P., & Tsinakos, A. (2018). Facebook and Moodle integration into instructional media design courses: A comparative analysis of students’ learning experiences using the community of inquiry (CoI) model. International Journal of Human–Computer Interaction, 34(10), 932–942. https://doi.org/10.1080/10447318.2018.1471574
Kim, G. C., & Gurvitch, R. (2020). Online education research adopting the community of inquiry framework: A systematic review. Quest, 72(4), 395–409. https://doi.org/10.1080/00336297.2020.1761843
Kwon, K., Ottenbreit-Leftwich, A. T., Sari, A. R., Khlaif, Z., Zhu, M., Nadir, H., & Gok, F. (2019). Teachers’ self-efficacy matters: Exploring the integration of mobile computing device in middle schools. TechTrends, 63(6), 682–692. https://doi.org/10.1007/s11528-019-00402-5
Lee, R., Hoe Looi, K., Faulkner, M., & Neale, L. (2020). The moderating influence of environment factors in an extended community of inquiry model of e-learning. Asia Pacific Journal of Education, 41(1), 1–15. https://doi.org/10.1080/02188791.2020.1758032
Linnenbrink, E. A., & Pintrich, P. R. (2003). The role of self-efficacy beliefs instudent engagement and learning in the classroom. Reading & Writing Quarterly, 19(2), 119–137. https://doi.org/10.1080/10573560308223
Love, J., Selker, R., Marsman, M., Jamil, T., Dropmann, D., Verhagen, A. J., Ly, A., Gronau, Q. F., Šmíra, M., Epskamp, S., Matzke, D., Wild, A., Knight, P., Rouder, J. N., Morey, R. D., & Wagenmakers, E.-J. (2019). JASP—Graphical statistical software for common statistical designs. Journal of Statistical Software, 88(2), 1–17. https://doi.org/10.18637/jss.v088.i02
Midgley, C., Maehr, M. L., Hruda, L. Z., Anderman, E., Anderman, L., Freeman, K. E., & Urdan, T. (2000). Manual for the patterns of adaptive learning scales. University of Michigan. http://websites.umich.edu/~pals/PALS%202000_V13Word97.pdf
Mishra, L., Gupta, T., & Shree, A. (2020). Online teaching-learning in higher education during lockdown period of COVID-19 pandemic. International Journal of Educational Research Open, 1, Article 100012. https://doi.org/10.1016/j.ijedro.2020.100012
Nagel, L., & Kotzé, T. G. (2010). Supersizing e-learning: What a CoI survey reveals about teaching presence in a large online class. The Internet and Higher Education, 13(1–2), 45–51. https://doi.org/10.1016/j.iheduc.2009.12.001
Pardo, A. M. S., & Peñalvo, F. J. G. (2008). Philosophical and epistemological basis for building a quality online training methodology. In F. J. G. Peñalvo (Ed.), Advances in e-learning: Experiences and methodologies (pp. 46–60). IGI Global. https://doi.org/10.4018/978-1-59904-756-0.ch003
Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e-learning. Journal of Educational Technology & Society, 12(3), 150–162. https://www.jstor.org/stable/jeductechsoci.12.3.150
Pecka, S. L. (2014). Evaluating higher order thinking in online discussions. University of Nebraska Medical Center. https://mydigitalpublication.com/publication/?i=236271&article_id=1872237&view=articleBrowser&ver=html5
Ponton, M., Derrick, G., Hall, J. M., Rhea, N., & Carr, P. (2005). The relationship between self-efficacy and autonomous learning: The development of new instrumentation. International Journal of Self-Directed Learning, 2(1), 50–61. https://www.researchgate.net/publication/281323039_The_relationship_between_self-efficacy_and_autonomous_learning_The_development_of_new_instrumentation
Popescu, E., & Badea, G. (2020). Exploring a community of inquiry supported by a social media-based learning environment. Educational Technology & Society, 23(2), 61–76. https://doi.org/10.2307/26921134
Priniski, S. J., Rosenzweig, E. Q., Canning, E. A., Hecht, C. A., Tibbetts, Y., Hyde, J. S., & Harackiewicz, J. M. (2019). The benefits of combining value for the self and others in utility-value interventions. Journal of Educational Psychology, 111(8), 1478–1497. https://doi.org/10.1037/edu0000343
Putarek, V., & Pavlin-Bernardić, N. (2020). The role of self-efficacy for self-regulated learning, achievement goals, and engagement in academic cheating. European Journal of Psychology of Education, 35(3), 647–671. https://doi.org/10.1007/s10212-019-00443-7
Rapanta, C., Botturi, L., Goodyear, P., Guàrdia, L., & Koole, M. (2020). Online university teaching during and after the COVID-19 crisis: Refocusing teacher presence and learning activity. Postdigital Science and Education, 2(3), 923–945. https://doi.org/10.1007/s42438-020-00155-y
Richardson, J. C., Besser, E., Koehler, A., Lim, J., & Strait, M. (2016). Instructors’ perceptions of instructor presence in online learning environments. The International Review of Research in Open and Distributed Learning, 17(4), 82–104. https://doi.org/10.19173/irrodl.v17i4.2330
Rubin, B., Fernandes, R., & Avgerinou, M. D. (2013). The effects of technology on the community of inquiry and satisfaction with online courses. The Internet and Higher Education, 17, 48–57. https://doi.org/10.1016/j.iheduc.2012.09.006
Song, L., & Hill, J. R. (2007). A conceptual model for understanding self-directed learning in online environments. Journal of Interactive Online Learning, 6(1), 27–42. http://www.ncolr.org/jiol/issues/pdf/6.1.3.pdf
Taipjutorus, W., Hansen, S., & Brown, M. (2012). Investigating a relationship between learner control and self-efficacy in an online learning environment. Journal of Open, Flexible, and Distance Learning, 16(1), 56–69. https://files.eric.ed.gov/fulltext/EJ1079899.pdf
Tan, H. R., Chng, W. H., Chonardo, C., Ng, M. T. T., & Fung, F. M. (2020). How chemists achieve active learning online during the COVID-19 pandemic: Using the community of inquiry (CoI) framework to support remote teaching. Journal of Chemical Education, 97(9), 2512–2518. https://doi.org/10.1021/acs.jchemed.0c00541
Teo, T., & Zhou, M. (2014). Explaining the intention to use technology among university students: A structural equation modeling approach. Journal of Computing in Higher Education, 26(2), 124–142. https://doi.org/10.1007/s12528-014-9080-3
Üner, A., Mouratidis, A., & Kalender, İ. (2020). Study efforts, learning strategies and test anxiety when striving for language competence: The role of utility value, self-efficacy, and reasons for learning English. Educational Psychology, 40(6), 781–799. https://doi.org/10.1080/01443410.2020.1736989
Valentine, J. C., DuBois, D. L., & Cooper, H. (2004). The relation between self-beliefs and academic achievement: A meta-analytic review. Educational Psychologist, 39(2), 111–133. https://doi.org/10.1207/s15326985ep3902_3
Valtonen, T., Kukkonen, J., Kontkanen, S., Sormunen, K., Dillon, P., & Sointu, E. (2015). The impact of authentic learning experiences with ICT on pre-service teachers’ intentions to use ICT for teaching and learning. Computers & Education, 81, 49–58. https://doi.org/10.1016/j.compedu.2014.09.008
Valverde-Berrocoso, J., Garrido-Arroyo, M. D. C., Burgos-Videla, C., & Morales-Cevallos, M. B. (2020). Trends in educational research about e-learning: A systematic literature review (2009–2018). Sustainability, 12(12), Article 5153. https://doi.org/10.3390/su12125153
Van Niekerk, M. P. (2015). Students’ perceptions on IWB through the lens of the community of inquiry framework. South African Journal of Education, 35(4), 1–10. https://doi.org/10.15700/saje.v35n4a1212
Vogel, F. R., & Human-Vogel, S. (2016). Academic commitment and self-efficacy as predictors of academic achievement in additional materials science. Higher Education Research & Development, 35(6), 1298–1310. https://doi.org/10.1080/07294360.2016.1144574
Wang, L., & Finch, H. (2018). Motivation variables mediate the relationship between socioeconomic status and academic achievement. Psychology and Education: An Interdisciplinary Journal, 55, 123–136. https://www.researchgate.net/publication/329516367_Motivation_Variables_Mediate_the_Relationship_between_Socioeconomic_Status_and_Academic_Achievement
Wigfield, A. (1994). Expectancy-value theory of achievement motivation: A developmental perspective. Educational Psychology Review, 6(1), 49–78. https://doi.org/10.1007/BF02209024
Wigfield, A., & Eccles, J. S. (2000). Expectancy–value theory of achievement motivation. Contemporary Educational Psychology, 25(1), 68–81. https://doi.org/10.1006/ceps.1999.1015
Wigfield, A., Tonks, S., & Eccles, J. S. (2004). Expectancy value theory in cross-cultural perspective. In D. M. McInerney & S. Van Etten (Eds.), Big Theories Revisited (pp. 165–198). Information Age Publishing.
Yavuzalp, N., & Bahcivan, E. (2020). The online learning self-efficacy scale: Its adaptation into Turkish and interpretation according to various variables. Turkish Online Journal of Distance Education, 21(1), 31–44. https://files.eric.ed.gov/fulltext/EJ1238987.pdf
This work is licensed under a Creative Commons Attribution 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International Licence. The copyright of all content published in IRRODL is retained by the authors.
This copyright agreement and use license ensures, among other things, that an article will be as widely distributed as possible and that the article can be included in any scientific and/or scholarly archive.
You are free to
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
The licensor cannot revoke these freedoms as long as you follow the license terms below:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.