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Loneliness and intrinsic motivation levels of distance learners in virtual environments

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Abstract

This study aims to determine the relationship between the loneliness levels and intrinsic motivation levels felt by distance learners in a virtual environment. To this end, predictive design was used as a quantitative research method. The results obtained from 330 distance learner participants revealed a medium level negative statistically significant relationship between the intrinsic motivation levels and loneliness levels of students. Additionally, a medium level positive statistically significant relationship was found between students’ intrinsic motivation levels and the sub-factors of virtual socializing and virtual sharing, while a medium level negative statistically significant relationship was found for the virtual seclusion sub-factor. The regression analysis conducted within the study revealed that 48.3% of the intrinsic motivation can be explained by the feeling of virtual loneliness. The analysis shows a medium level negative effect of virtual loneliness on intrinsic motivation. Furthermore, the regression model developed to explain the relationship between intrinsic motivation levels and virtual loneliness sub-factors explained the intrinsic motivation levels by 49.5%. As such, a statistically significant negative effect of the virtual seclusion variable on intrinsic motivation levels of students was observed. A statistically significant positive effect was found for the variables virtual sharing and virtual socializing. The findings of the study led to the conclusion that communication and interaction should be emphasized in order to minimize the feeling of virtual loneliness in learners.

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Data Availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

References

  • Arifin, W. N. (2015). The graphical assessment of multivariate normality using SPSS. Education in Medicine Journal, 7(2), 71–75. https://doi.org/10.5959/eimj.v7i2.361

    Article  Google Scholar 

  • Aydın, H. (2012). Felsefi temelleri ışığında yapılandırmacılık (2nd ed.). Nobel Publishing Distribution.

  • Barak, M., Watted, A., & Haick, H. (2016). Motivation to learn in massive open online courses: Examining aspects of language and social engagement. Computers & Education, 94(2016), 49–60. https://doi.org/10.1016/j. compedu.2015.11.010.

    Article  Google Scholar 

  • Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen, & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Sage. https://doi.org/10.1177/0049124192021002005

  • Çakır, V., & Çakır, V. (2011). Loneliness and television usage. Journal of Selcuk Communication, 7(1), 131–147. https://dergipark.org.tr/en/pub/josc/issue/19023/200598

    MathSciNet  Google Scholar 

  • Cerasoli, C. P., Nicklin, J. M., & Ford, M. T. (2014). Intrinsic motivation and extrinsic incentives jointly predict performance: A 40- year meta‐ analysis. Psychological Bulletin, 140(4), 980–1008. https://doi.org/10.1037/a0035661

    Article  Google Scholar 

  • Chen, K. C., & Jang, S. J. (2010). Motivation in online learning: Testing a model of self- determination theory. Computers in Human Behaviour, 26(4), 741–752. https://doi.org/10.1016/j.chb.2010.01.011

    Article  Google Scholar 

  • Cohen, J. (1988). Statistical power analysis for the social sciences. Erlbaum.

  • Creswell, J. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative research. Pearson.

  • Deimann, M., & Bastiaens, T. (2010). The role of volition in distance education: An exploration of its capacities. International Review of Research in Open and Distributed Learning, 11(1), 1–16. https://doi.org/10.19173/irrodl.V11i1.778

    Article  Google Scholar 

  • Demir, D. (2018). Examining the relationship between virtual loneliness, professional burnout and psychological well-being of informatics teachers. (Publication No. 521956). [Master’s thesis, Afyon Kocatepe University]. Higher Education Council Thesis Archive. https://tez.yok.gov.tr

  • Fer, S., & Cırık, İ. (2007). Yapılandırmacı öğrenme: Kuramdan uygulamaya. Morpa Publishing.

  • Field, A. (2009). Discovering statistics using IBM SPSS statistics. Sage.

  • Fırat, M., Kılınç, H., & Yüzer, T. V. (2018). Level of intrinsic motivation of distance education students in e-learning environments. Journal of Computer Assisted Learning, 34(1), 63–70. https://doi.org/10.1111/jcal.12214

    Article  Google Scholar 

  • Galikyan, I., & Admiraal, W. (2019). Students’ engagement in asynchronous online discussion: The relationship between cognitive presence, learner prominence, and academic performance. The Internet and Higher Education, 43(1), https://doi.org/10.1016/j.iheduc.2019.100692

  • Hartnett, M., George, A. S., & Dron, J. (2011). Examining motivation in online distance learning environments: Complex, multifaceted and situation-dependent. The International Review of Research in Open and Distributed Learning, 12(6), 20–38. https://doi.org/10.19173/irrodl.v12i6.1030

    Article  Google Scholar 

  • Hinkle, D. E., Wiersma, W., & Jurs, S. G. (2003). Applied statistics for the behavioral sciences (5th ed.). Houghton Mifflin.

  • Holmberg, B. (1995). The sphere of distance-education theory revisited. Zentrales Institut fiir Fernstudienforschung (ZIFF) Papiere 98, Hegen: FernUniversität. http://files.eric.ed.gov/fulltext/ED386578.pdf

  • Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118

    Article  Google Scholar 

  • Huck, S. W. (2012). Reading statistics and research (6th ed.). Pearson Education.

  • Jaramillo, J. A. (1996). Vygotsky’s sociocultural theory and contributions to the development of constructivist curriculum. Education, 117(1), 133–140.

    Google Scholar 

  • Jonassen, D. H. (1999). Designing constructivist learning environments. In C. M. Reigeluth (Ed.), Instructional design theories and models: A new paradigm of instructional theory (pp. 215–239). Lawrence Erlbaum Associates, Inc.

  • Kahraman, D. (2020). Determination of academic achievement, internet usage, addiction and virtual environment loneliness level relationships in science. (Publication No. 643618). [Master’s thesis, Muğla Sıtkı Kocman University]. Higher Education Council Thesis Archive. https://tez.yok.gov.tr

  • Karaoğlan-Yılmaz, F. G. (2019). Exploring the role of Facebook adoption and virtual environment loneliness on knowledge sharing behaviors in a Facebook learning community. Education and Information Technologies, 24, 1699–1714. https://doi.org/10.1007/s10639-018-09854-3

    Article  Google Scholar 

  • Keller, J. M. (1979). Motivation and instructional design: A theoretical perspective. Journal of Instructional Development, 2(4), 26–34. https://doi.org/10.1007/BF02904345

    Article  Google Scholar 

  • Keller, J. M. (2010). Motivational design for learning and performance: The ARCS model approach. Springer Publishing.

  • Kılınç, H. (2020). Examining the effect of online group discussions on learners in terms of various variables: The case of Anadolu University Open Education Faculty (Publication No. 627077). [Doctoral dissertation, Anadolu University]. Higher Education Council Thesis Archive. https://tez.yok.gov.tr

  • Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). The Guilford Press.

  • Knapp, H. (2018). Intermediate statistics using SPSS. Sage.

  • Korkmaz, Ö., Usta, E., & Kurt, İ. (2014). A validity and reliability study of the virtual environment loneliness scale (vels). Hacettepe University Journal of Education, 29(29 – 2), 144–159.

    Google Scholar 

  • Lee, J., & Martin, L. (2017). Investigating students’ perceptions of motivating factors of online class discussions. International Review of Research in Open and Distributed Learning, 18(5), 148–172. https://doi.org/10.19173/irrodl.v18i5.2883

    Article  Google Scholar 

  • Lim, J. R. N., Rosenthal, S., Sim, Y. J. M., Lim, Z. Y., & Oh, K. R. (2021). Making online learning more satisfying: The effects of online-learning self-efficacy, social presence and content structure. Technology Pedagogy and Education, 30(4), 543–556. https://doi.org/10.1080/1475939X.2021.1934102

    Article  Google Scholar 

  • McMillan, J. H., & Forsyth, D. R. (1991). What theories of motivation say about why learners learn. New Directions for Teaching and Learning, 1991(45), 39–52. https://doi.org/10.1002/tl.37219914507

    Article  Google Scholar 

  • Menard, S. (1995). Applied logistic regression analysis (2nd ed.). SAGE.

  • Moore, M. G. (1990). Self-directed learning and distance education. Journal of Distance Education, 1(1), 7–24.

    MathSciNet  Google Scholar 

  • Moore, M. G. (1993). 2 theory of transactional distance. Theoretical Principles of Distance Education, 1, 22–38.

    Google Scholar 

  • Moore, M. G., & Kearsley, G. (2012). Distance education: A systems view of online learning. Wadsworth-Cengage Learning.

  • Oh, H. J., Kim, J., Chang, J. J., Park, N., & Lee, S. (2023). Social benefits of living in the metaverse: The relationships among social presence, supportive interaction, social self-efficacy, and feelings of loneliness. Computers in Human Behavior, 139. https://doi.org/10.1016/j.chb.2022.107498

  • Özdemir, S., & Yalın, H. (2007). The effects of individual and collaborative problem based learning on critical thinking through a web based asynchronized learning tool. Ahi Evran University Journal of Kırşehir Faculty of Education, 8(1), 79–94. https://dergipark.org.tr/en/pub/kefad/issue/59535/856315

    Google Scholar 

  • Powell, K. C., & Kalina, C. J. (2009). Cognitive and social constructivism: Developing tools for an effective classroom. Education, 130(2), 241–250. https://docdrop.org/static/drop-pdf/Powell-and-Kalina-U6g4p.pdf

    Google Scholar 

  • Raffini, P. J. (1996). 150 ways to increase intrinsic motivation in the classroom. (2nd. Edition). Baston: Allyn and Bacon.

  • Rannikmäe, M., Holbrook, J., & Soobard, R. (2020). Social constructivism - Jerome Bruner. In B. Akpan, T. J. Kennedy (Eds.), Science education in theory and practice: An introductory guide to learning theory, 259–275. https://doi.org/10.1007/978-3-030-43620-9_18

  • Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. https://doi.org/10.1037/0003-066X.55.1.68

    Article  Google Scholar 

  • Ryan, R. M., & Deci, E. L. (2019). Supporting autonomy, competence, and relatedness: The coaching process from a self-determination theory perspective. In S. English, J. M. Sabatine, & P. Brownell (Eds.), Professional coaching: Principles and practice (pp. 231–245). Springer Publishing Company.

  • Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research Online, 8(2), 23–74. https://www.stats.ox.ac.uk/~snijders/mpr_Schermelleh.pdf

    Google Scholar 

  • Schunk, D. H., & DiBenedetto, M. K. (2020). Motivation and social cognitive theory. Contemporary Educational Psychology, 60, 101832. https://doi.org/10.1016/j.cedpsych.2019.101832

    Article  Google Scholar 

  • Schunk, D. H., & Usher, E. L. (2019). Social cognitive theory and motivation. In R. M. Ryan (Ed.), The Oxford handbook of human motivation (2nd ed., pp. 11–26). Oxford University Press.

  • Semmar, Y. (2006). Distance learners and academic achievement: The roles of self efficacy, self- regulation and motivation. Journal of Adult and Continuing Education, 12(2), 244–256. https://doi.org/10.7227/JACE.12.2.9

    Article  Google Scholar 

  • Singh, S., Singh, A., & Singh, K. (2012). Motivation levels among traditional and open learning undergraduate students in India. The International Review of Research in Open and Distributed Learning, 13(3), 19–40. https://doi.org/10.19173/irrodl.v13i3.1050

    Article  Google Scholar 

  • Sivrikaya, A. H. (2019). The relationship between academic motivation and academic achievement of the students. Asian Journal of Education and Training, 5(2), 309–315. https://eric.ed.gov/?id=EJ1216482

    Article  Google Scholar 

  • Vatansever-Bayraktar, H. (2015). Student motivation in classroom management and factors that affect motivation. Turkish Studies - International Periodical For the Languages, Literature and History of Turkish or Turkic, 10(3). 1079–1100. https://doi.org/10.7827/TurkishStudies.7788

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Authors and Affiliations

  1. Institute of Social Sciences, Anadolu University, Eskisehir, Türkiye

    Yusuf Yildirim & Gökhan Alptekin

  2. Faculty of Open Education, Anadolu University, Eskisehir, Türkiye

    Hakan Altinpulluk & Hakan Kilinc

  3. Department of Distance Education, Anadolu University, Eskisehir, 26480, Türkiye

    Hakan Altinpulluk

  4. Faculty of Communication Sciences, Anadolu University, Eskisehir, Türkiye

    Onur Yumurtaci

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  1. Yusuf Yildirim
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  2. Gökhan Alptekin
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  3. Hakan Altinpulluk
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  5. Onur Yumurtaci
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Correspondence to Hakan Altinpulluk.

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Yildirim, Y., Alptekin, G., Altinpulluk, H. et al. Loneliness and intrinsic motivation levels of distance learners in virtual environments. Educ Inf Technol (2023). https://doi.org/10.1007/s10639-023-12274-7

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