Development and Validation of a PLE Scale from the Learner and Learning Perspective in Tertiary Education
Abstract
The study's goal is to create and validate a Personal Learning Environment Scale (PLEs) from the learner and learning perspective (named PLEsS-LL) to ensure effective learning in Chinese tertiary education. 657 undergraduates participated in the study after completing scale development steps. Six factors were extracted from the PLEsS-LL using Exploratory Factor Analysis (EFA). Confirmatory Factor Analysis (CFA) supported the six-factor scale with 22 items. Furthermore, the PLEsS-LL was redesigned as a questionnaire to assess learners' readiness for PLE learning. The findings indicated that participants were comfortable learning in PLEs in general. They were mostly positive in terms of learning motivation and problem-solving abilities. They did, however, report less confidence in self-directed learning. Meanwhile, male participants outperformed female participants in all categories except learning motivation. The reasons were explained, and suggestions for future PLE design were made. The PLEsS-LL could be used as a resource or guide for learner preparation in the PLE context in higher education around the world.
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Alamri, H., Lowell, V., Watson, W., & Watson, S. L. (2020). Using personalized learning as an instructional approach to motivate learners in online higher education: Learner self-determination and intrinsic motivation. Journal of Research on Technology in Education, 52(3), 322–352. https://doi.org/10.1080/15391523.2020.172844947?277.
Alqurashi, E. (2016). Self-efficacy in online learning environments: A literature review. Contemporary Issues in Education Research, 9(1), 45–52. https://doi.org/10.1002/piq.20001
Anderson, T. (2003). Modes of interaction in distance education: Recent developments and research questions. In M. G. Moore & W. G. Anderson (Eds.), Handbook of distance education (pp. 129–144). Mahwah, NJ: Lawrence Erlbaum Associates Inc. https://doi.org/10.24059/olj.v16i4.229
Appleton, J. J., Christenson, S. L., & Furlong, M. J. (2008). Student engagement with school: Critical conceptual and methodological issues of the construct. Psychology in the Schools, 45(5), 369–386. https://doi.org/10.1002/pits.20303
Aslan, S. (2017). Learning by Teaching: Can It Be Utilized to Develop Inquiry Skills? Journal of Education and Training Studies.5(12),190-198. https://doi.org/10.11114/jets.v5i12.2781
Attwell, G. (2021). Personal Learning Environments: looking back and looking forward. Graham Attwell's Lab, https://doi.org/10.13140/RG.2.2.18802.63684
Banna, J., Lin, M.-F. G., Stewart, M., & Fialkowski, M. K. (2015). Interaction matters: Strategies to promote engaged learning in an online introductory nutrition course. Journal of Online Learning and Teaching, 11(2), 249–261.
Berg, V. D., Jan, Rahimi, Ebrahim, Veen, & Wim. (2015). Facilitating student-driven constructing of learning environments using Web 2.0 personal learning environments. Computers & Education, 81, 235-246. https://doi.org/10.1016/j.compedu.2014.10.012
Best, J.; Kahn, J. (2006). Research in Education. Pearson: Boston, MA, USA.
Blayone, T. (2018). Reexamining digital-learning readiness in higher education: Positioning digital competencies as key factors and a profile application as a readiness tool. International Journal on E-Learning, 17(4), 425–451. https://www.learntechlib.org/primary/p/178285/
Byrne, B.M. (2016). Structural equation modeling with AMOS: Basic concepts, applications and programming (multivariate applications series) (3rd ed.), Routledge, London.
Carneiro, R., Lefrere, P., & Steffens, K. (2011). Enhanced learning environment. Draft Version, 41(3-4), 353–379.https://doi.org/10.1007/978-94-6091-654-0_3
Castañeda, L., Tur, G., Torres-Kompen, R., & Attwell, G. (2022). The Influence of the Personal Learning Environment Concept in the Educational Research Field: A 2010-2020 Systematized Review. International Journal of Virtual and Personal Learning Environments (IJVPLE), 12(1), 1-16. https://doi.org/10.4018/IJVPLE.2022010102
Cheon J., Cheng J. & Cho M.H. (2021): Validation of the Online Learning Readiness Self-Check survey, Distance Education,1-21 https://doi.org/10.1080/01587919.2021.1986370
Cho, M.-H., Shen, D., & Laffey, J. (2010). Relationships between self-regulation and social experiences in asynchronous online learning environments. Journal of Interactive Learning Research, 21, 297–316.
Cho, M. H. (2012). Online student orientation in higher education: A developmental study. Educational Technology Research and Development, 60(6), 1051–1069. https://doi.org/10.1007/ s11423-012-9271-4
Cohen, J. . (1988). Statistical power analysis for the behavioral sciences (2nd ed.). L. Erlbaum Associates.
Crocker, L., & Algina, J. (1986). Introduction to Classical and Modern Test Theory. New York: CBS College Publishing.
Clark, V. L. P., & Creswell, J. W. (2010). Understanding research: a consumer’s guide. New Jersey: Prentice Hall-Merrill.
Czubaj, C. A. (2004). Literature review: reported educator concerns regarding cyberspace curricula. Education, 124(4), 676–683. https://link.gale.com/apps/doc/A121765620/AONE?u=anon~9b862333&sid=googleScholar&xid=14db429f
Dabbagh, N. (2007). The online learner: characteristics and pedagogical implications. Contemporary Issues in Technology and Teacher Education, 7(3), 217-226.
Dabbagh, N., & Castañeda, L. (2020). The PLE as a framework for developing agency in lifelong learning. Educational Technology Research and Development, 68(6), 3041-3055. https://doi.org/10.1007/s11423-020-09831-z
Dabbagh, N., & Kitsantas, A. (2005). Using web-based pedagogical tools as scaffolds for self-regulated learning. Instructional Science, 33, 513–540. https://doi.org/10.1007/s11251-005-1278-3
Deci, E., & Ryan, R. (1985). Intrinsic motivation and self-determination in human behavior. New York: Plenum Press.
Demir, Ö, & Yurdugül, H. (2015). The exploration of models regarding e-learning readiness: reference model suggestions. International Journal of Progressive Education,11,173-194.
Deng, R., Benckendorff, P., & Gannaway, D. (2019). Progress and new directions for teaching and learning in MOOCs. Computers & Education, 129, 48–60. https://doi.org/10.1016/j.compedu.2018.10.019
De Freitas, S., Morgan, J., & Gibson, D. (2015). Will MOOCs transform learning and teaching in higher education? Engagement and course retention in online learning provision. British Journal of Educational Technology. 46(3): 455-471. https://doi.org/10.1111/bjet.12268
Díaz-García, C., Sáez-Martínez, F., & Jiménez-Moreno, J. (2015). Assessing the impact of the “Entrepreneurs” education programme on participants’ entrepreneurial intentions. International Journal of Educational Technology in Higher Education, 12(3), 17-31. https://doi.org/10.7238/rusc.v12i3.2146
Dixson, M. D. (2010). Creating effective student engagement in online courses: What do students find engaging? Journal of the Scholarship of Teaching and Learning, 10(2), 1–13.
Dotterer, A. M., & Lowe, K. (2011). Classroom context, school engagement, and academic achievement in early adolescence. Journal of Youth and Adolescence, 40(12), 1649–1660. https://doi.org/10.1007/s10964-011-9647-5
Duckworth, A. L., & Yeager, D. S. (2015). Measurement matters: assessing personal qualities other than cognitive ability for educational purposes. Educational Researcher, 44(4), 237-251.https://doi.org/10.3102/0013189X15584327
Elfeky A. I. M. (2019) The effect of personal learning environments on participant’s higher order thinking skills and satisfaction. Innovations in Education and Teaching International 56, 505–516. https://doi.org/10.1080/14703297.2018.1534601
Fairchild, A. J., Jeanne Horst, S., Finney, S. J., & Barron, K. E. (2005). Evaluating existing and new validity evidence for the academic motivation scale. Contemporary Educational Psychology, 30(3), 331–358. https://doi.org/10.1016/j.cedpsych.2004.11.001
Field, A., Miles, J., Field, Z. (2012). Discovering Statistics Using R. SAGE Publications: Thousand Oaks, CA, USA.
Geels, F. (2004). From sectoral systems of innovation to socio-technical systems- Insights about dynamics and change from sociology and institutional theory. Res. Policy,33,897-920.https://doi.org/10.1016/j.respol.2004.01.015
Glassman, M., Kuznetcova, I., Peri, J., & Kim, Y. (2021). Cohesion, collaboration and the struggle of creating online learning communities: Development and validation of an online collective efficacy scale. Computers and Education Open, 2. https://doi.org/10.1016/j.caeo.2021.100031
Hair, J. F., Babin, B. J., Anderson, R. E., & W. C. Black. (2018). Multivariate data analysis. 8th ed. Boston: Cengage.
Henrie, C. R., Halverson, L. R., & Graham, C. R. (2015). Measuring student engagement in technology-mediated learning: A review. Computers & Education, 90, 36–53.https://doi.org/10.1016/j.compedu.2015.09.005
Henry, K. L., Knight, K. E., & Thornberry, T. P. (2012). School disengagement as a predictor of dropout, delinquency, and problem substance use during adolescence and early adulthood. Journal of Youth and Adolescence, 41(2), 156–166.https://doi.org/10.1007/s10964-011-9665-3
Hung, M. L., Chou, C., Chen, C. H., & Own, Z. Y. (2010). Learner readiness for online learning: Scale development and student perceptions. Computers & Education, 55(3),1080–1090. https://doi.org/ 10.1016/j.compedu.2010.05.004
Jansen, R. S., Van Leeuwen, A., Janssen, J., Kester, L., & Kalz, M. (2017). Validation of the self-regulated online learning questionnaire. Journal of Computing in Higher Education, 29(1), 6-27. https://doi.org/10.1007/s12528-016-9125-x
Kalkan, N. (2020). Investigation of e-learning readiness levels of university students studying in different departments. African Educational Research Journal, 8. 533-539. https://doi.org/10.30918/AERJ.83.20.110
Knowles, M. S. (1975). Self-directed learning: A guide for learners and teachers. New York: Association Press.
Kompen, R.T., Edirisingha, P., Canaleta, X., Alsina, M., Monguet, J.M., (2019) Personal learning environments based on web 2.0 services in higher education, Telematics and Informatics, 38,194-206. https://doi.org/ 10.1016/j.tele.2018.10.003
Lee, J. S. (2014). The relationship between student engagement and academic performance: Is it a myth or reality? The Journal of Educational Research, 107(3), 177–185. https://doi.org/ 10.1080/00220671.2013.807491
Li, C., Shi, X., &Dang, J. (2014). Online communication and subjective well-being in Chinese college students: the mediating role of shyness and social self-efficacy. Computers in Human Behavior, 34(may), 89-95. https://doi.org/10.1016/j.chb.2014.01.032
Martin, F., & Bolliger, D.U. (2018). Engagement matters: Student perceptions on the importance of engagement strategies in the online learning environment. Online Learning. 22(1), 205-222. https://doi.org/10.24059/olj.v22i1.1092
McMillan, J.; Schumacher, S. (2005). Investigación Educativa(5th ed.). Pearson Educación: Madrid, Spain.
McVay, M. (2000). Developing a web-based distance student orientation to enhance student success in an online bachelor’s degree completion program. Unpublished practicum report presented to the Ed.D. Program. Florida: Nova Southeastern University.
McVay, M. (2001). How to be a successful distance learning student: Learning on the Internet. New York: Prentice Hall.
Muilenburg, L. Y. & Berge, Z. L. (2005). Student barriers to online learning: a factor analytic study. Distance Education, 26(1), 29-48. https://doi.org/ 10.1080/01587910500081269.
Nystrand, M., & Gamoran, A. (1991). Instructional discourse, student engagement, and literature achievement. Research in the Teaching of English, 25(3), 261–290.
Pantziara, Marilena, and George N. Philippou. (2014). Students’ Motivation in the Mathematics Classroom. Revealing Causes and Consequences. International Journal of Science and Mathematics Education, 13(2), 385–411. https://doi.org/10.1007/s10763-013-9502-0.
Rasmussen, K.L., Davidson-Shivers, G.V.(1998). Hypermedia and learning styles: can performance be influenced?. Journal of Educational Multimedia and Hypermedia, 7(4), 291–308.
Rhode, J. (2009). Interaction equivalency in self-paced online learning environments: An exploration of learner preferences. The International Review of Research in Open and Distributed Learning, 10 (1). https://doi.org/10.19173/irrodl.v10i1.603
Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54–67. https://doi.org/10.1006/ceps.1999.1020
Smith, P. J., Murphy, K. L., & Mahoney, S. E. (2003). Towards identifying factors underlying readiness for online learning: An exploratory study. Distance Education, 24(1), 57–67. https://doi.org/10. 1080/01587910303043
Sun, J. C.-Y., & Rueda, R. (2012). Situational interest, computer self-efficacy and self-regulation: 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
Taragh Siemens, G. (2004). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, URL https://jotamac.typepad.com/jotamacs_weblog/files/Connectivism.pdf
Tochon, F. V., Karaman, A. C. and Ökten, C. E. (2014) Online Instructional Personal Environment for Deep Language Learning. International Online Journal of Education and Teaching, 1, 147–73. URL https://www.iojet.org/index.php/IOJET/article/view/32/52
Trowler, V., & Trowler, P. (2010). Student engagement evidence summary. York, England: Higher Education Academy.
Van Harmelen, M. (2008). Design trajectories: four experiments in PLE implementation, Interactive Learning Environments, 16(1), 35-46. http://doi.org/ 10.1080/10494820701772686.
Velicer, W.F., Fava, J.L.(1998). Effects of variable and subject sampling on factor pattern recovery. Psychol. Methods, 3, 231–251. [CrossRef] http://doi.org/10.1037/1082-989X.3.2.231
Warner, D., Christie, G., & Choy, S.(1998). Readiness of VET clients for flexible delivery including on-line learning. Brisbane: Australian National Training Authority.
Wang, Y. (2000). A study on factors influencing computer attitude and learning performance – a field experiment of web page design in high school. Journal of Information Management ,7 (1), 1–106.
Wang, J., Guo, D., & Jou, M. (2015). A study on the effects of model-based inquiry pedagogy on students’ inquiry skills in a virtual physics lab. Computers in Human Behaviour, 49, 658-669. https://doi.org/10.1016/j.chb.2015.01.043
Wang, M.T., & Fredricks, J. A. (2014). The reciprocal links between school engagement, youth problem behaviors, and school dropout during adolescence. Child Development, 85(2), 722–737. https://doi.org/10.1111/cdev.12138
Wladis, C., & Samuels, J. (2016). Do online readiness surveys do what they claim? Validity, reliability, and subsequent student enrollment decisions. Computers & Education, 98, 39–56. https://doi.org/ 10.1016/j.compedu.2016.03.001
Wu, C.(2000). Comparing the Student’s Learning Performance Between the Web- based Teaching and the Conventional Teaching – a Case of Word 2000. Unpublished master thesis, Tamkang University, Taipei, Taiwan.
Yen, C.Tuc，et al. (2019).Using personal learning environment（PLE）management to support digital lifelong learning. International Journal of Online Pedagogy and Course Design, 3, 13 -31. https://doi.org/10.4018/IJOPCD.2019070102
Yu, S.(2002). The effect of hypermedia structure and learning style on learning achievement about hypermedia. Unpublished master thesis, National Dong Hwa University, Hualien, Taiwan.
Yu, T. (2018). Examining construct validity of the student online learning readiness(SOLR) instrument using confirmatory factor analysis. Online Learning, 22(4), 277-288.https://doi.org/10.24059/olj.v22i4.1297
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