Skip to main content
Multistudy Report

Students’ Perceived Constructivist Learning Environment

Empirical Examples of the Comparison Between Facet Theory with Smallest Space Analysis and Confirmatory Factor Analysis

Published Online:https://doi.org/10.1027/1015-5759/a000358

Abstract. Theoretical classifications suggest three key tenets of the constructivist learning environment: constructivist task, teacher-student interaction, and social activity. This study assessed two scales, measuring the perceptions of high school and college students of their constructivist learning environment. Facet theory (FT) approach with smallest space analysis (SSA) as well as confirmatory factor analysis (CFA) were used to confirm the structure of the constructivist learning theory and to test the structural validity of scores on two scales. In the first study, data were gathered by using the Constructivist Learning Environment Survey (CLES). In this study, compared with the CFA result, the SSA gave additional information showing the existence of the three theoretical key tenets which were absent from the factor analysis. This facet was derived from the constructivist learning theory, framed in the mapping sentence, purposely designed as part of the FT research strategy. In the second study, students’ perceptions of the occurrence of constructivist practices in higher education learning environments were assessed. The comparison between SSA and CFA showed that the CFA was limited to capture merely one facet at a time and failed to illustrate the correspondence between the content facets of the mapping sentence.

References

  • Albright, J. J. & Hun, M. P. (2009). Confirmatory factor analysis using Amos, LISREL, Mplus, and SAS/STAT CALIS. Working Paper. The University Information Technology Services (UITS) Center for Statistical and Mathematical Computing, Indiana University. First citation in articleGoogle Scholar

  • Alt, D. (2014). The construction and validation of a new scale for measuring features of constructivist learning environments in higher education. Frontline Learning Research, 2, 1–28. doi: 10.14786/flr.v2i2.68 First citation in articleCrossrefGoogle Scholar

  • Alt, D., Cohen, A. & Maslovaty, N. (2009). The dimensionality of right-wing authoritarianism structured through structural equation modeling and smallest space analysis. In D. ElizurE. YanivEds., Theory construction and multivariate analysis: Applications of Facet Theory approach (pp. 279–290). Israel: FTA Publications. First citation in articleGoogle Scholar

  • Altemeyer, B. (1981). Right-wing authoritarianism. Winnipeg, MB: University of Manitoba Press. First citation in articleGoogle Scholar

  • Amar, R. & Toledano, S. (2001). HUDAP manual. Jerusalem, Israel: The Hebrew University of Jerusalem. First citation in articleGoogle Scholar

  • Apple, Z., Elizur, D. & Cohen, A. (2001). Facet of differentiation of self. In D. ElizurEd., Facet theory: Integrating theory construction with data Analysis (pp. 353–366). Prague, Czech Republic: Karlovy University of Prague. First citation in articleGoogle Scholar

  • Bentler, P. M. (2006). EQS 6 structural equations program manual. Encino, CA: Multivariate Software, Inc. First citation in articleGoogle Scholar

  • Berven, N. L. & Scofield, M. E. (1982). Nonmetric data-reduction techniques in rehabilitation research. Rehabilitation Counseling Bulletin, 25, 297–311. First citation in articleGoogle Scholar

  • Borg, I. & Lingoes, J. C. (1987). Multidimensional similarity structure analysis. New York, NY: Springer. First citation in articleCrossrefGoogle Scholar

  • Borg, I. & Shye, S. (1995). Facet theory: Form and content. Newbury Park, CA: Sage. First citation in articleGoogle Scholar

  • Brooks, J. G. & Brooks, M. G. (1999). In search of understanding: The case for constructivist classrooms. Alexandria, VA: Association for Supervision and Curriculum Development. First citation in articleGoogle Scholar

  • D. Canter (1985). Facet theory: Approaches to social research. New York, NY: Springer-Verlag. First citation in articleCrossrefGoogle Scholar

  • Cohen, A. (2003). The identification of underlying dimensionality in social sciences: Differences between factor analysis and smallest space analysis. In S. LevyD. ElizurEds., Facet theory: Towards cumulative social science (pp. 61–72). Ljubljana, Slovenia: University of Ljubljana, Faculty of Arts, Center for Educational Development. First citation in articleGoogle Scholar

  • Creswell, J. W. (2007). Educational research (3rd ed.). Thousand Oaks, CA: Sage. First citation in articleGoogle Scholar

  • Davidov E.Schmidt P.Billiet J.Eds.. (2011). Cross-cultural analysis: Methods and applications. New York, NY: Routledge. First citation in articleGoogle Scholar

  • De Clercq, M., Galand, B. & Frenay, M. (2014). Learning processes in higher education: Providing new insights into the effects of motivation and cognition on specific and global measures of achievement. In D. GijbelsV. DoncheJ. T. E. RichardsonJ. D. VermuntEds., Learning patterns in higher education: Dimensions and research perspectives (pp. 141–162). London, UK/New York, NY: Routledge/EARLI. First citation in articleGoogle Scholar

  • De Kock, A., Sleegers, P. & Voeten, M. J. M. (2004). New learning and the classification of learning environments in secondary education. Review of Educational Research, 74, 141–170. First citation in articleCrossrefGoogle Scholar

  • Dochy, F. J. R. C. & Alexander, P. A. (1995). Mapping prior knowledge: A framework for discussion among researchers. European Journal of Psychology of Education, 10, 225–242. First citation in articleCrossrefGoogle Scholar

  • Dong, H. (1985). Non-Gramian and singular matrices in maximum likelihood factor analysis. Applied Psychological Measurement, 9, 363–366. First citation in articleCrossrefGoogle Scholar

  • Erstad, O. (2011). Weaving the context of digital literacy. In S. LudvigsenA. LundI. RasmussenR. SäljöEds., Learning across sites: New tools, infrastructures and practices (pp. 295–310). London, UK: Routledge. First citation in articleGoogle Scholar

  • Evans, C. (2014). Exploring the use of a deep approach to learning with students in the process of learning to teach. In D. GijbelsV. DoncheJ. T. E. RichardsonJ. D. VermuntEds., Learning patterns in higher education: Dimensions and research perspectives (pp. 187–213). London, UK/New York, NY: Routledge/EARLI. First citation in articleGoogle Scholar

  • Funke, F. (2005). The dimensionality of right-wing authoritarianism: Lessons from the dilemma between theory and measurement. Political Psychology, 26, 195–218. First citation in articleCrossrefGoogle Scholar

  • Greenbaum, C. W. (2009). The past, present and future of Facet Theory and related approaches to data analysis in the social science. In D. ElizurE. YanivEds., Theory construction and multivariate analysis: Applications of Facet Approach (pp. 1–10). Israel: FTA Publications. First citation in articleGoogle Scholar

  • Guttman, L. (1954). A new approach to factor analysis: The radex. In P. LazarsfeldEd., Mathematical thinking in the social sciences (pp. 258–348). Glencove, IL: The Free Press. First citation in articleGoogle Scholar

  • Guttman, L. (1957). Empirical verification of the radex structure of mental abilities and personality traits. Educational and Psychological Measurement, 17, 391–407. First citation in articleCrossrefGoogle Scholar

  • Guttman, L. (1959). Introduction to facet design and analysis. In Proceedings of the Fifteenth International Congress of Psychology. Amsterdam, Netherlands: North-Holland. First citation in articleCrossrefGoogle Scholar

  • Guttman, L. (1965). The structure of interrelations among intelligence tests. Proceedings of the 1964 invitational conference on testing problems. Princeton, NJ: Educational Testing Service, 25–36. First citation in articleGoogle Scholar

  • Guttman, L. (1968). A general nonmetric technique for finding the smallest coordinate space for a configuration of points. Psychometrika, 33, 469–506. First citation in articleCrossrefGoogle Scholar

  • Guttman, L. (1982a). “What is not what” in theory construction. In R. M. HauserD. MechanicH. HallerEds., Social structure and behavior (pp. 331–348). New York, NY: Academic Press. First citation in articleGoogle Scholar

  • Guttman, L. (1982b). Facet theory, smallest space analysis, and factor analysis. Perceptual and Motor Skills, 54, 491–493. First citation in articleCrossrefGoogle Scholar

  • Guttman, L. & Levy, S. (1991). Two structural lanes for intelligence tests. Intelligence, 15, 79–103. First citation in articleCrossrefGoogle Scholar

  • Guttman, R. & Greenbaum, C. W. (1998). Facet theory: Its development and current status. European Psychologist, 3, 13–36. First citation in articleLinkGoogle Scholar

  • Hackett, P. M. W. (2014). Facet theory and the mapping sentence. Evolving philosophy, use and application. London, UK/New York, NY: Palgrave Pivot. First citation in articleCrossrefGoogle Scholar

  • Hakkarainen, K., Lipponen, L. & Järvelä, S. (2002). Epistemology of inquiry and computer supported collaborative learning. In T. KoschmannN. MiyakeR. HallEds., CSCL2: Carrying forward the conversation (pp. 129–156). Mahwah, NJ: Erlbaum. First citation in articleGoogle Scholar

  • Henson, R. K. & Roberts, J. K. (2006). Use of exploratory factor analysis in published research: Common errors and some comment on improved practice. Educational and Psychological Measurement, 66, 393–416. First citation in articleCrossrefGoogle Scholar

  • Järvelä, S., Hurme, T.-R. & Järvenoja, H. (2011). Self-regulation and motivation in computer-supported collaborative learning environments. In S. LudvigsenA. LundI. RasmussenR. SäljöEds., Learning across sites: New tools, infrastructures and practices (pp. 330–345). London, UK: Routledge. First citation in articleGoogle Scholar

  • Johnson, B. & McClure, R. (2004). Validity and reliability of a shortened, revised version of the Constructivist Learning Environment Survey (CLES). Learning Environments Research, 7, 65–80. First citation in articleCrossrefGoogle Scholar

  • Kirschner, P. A., Sweller, J. & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based experiential and inquiry-based teaching. Educational Psychologist, 41, 75–86. First citation in articleCrossrefGoogle Scholar

  • Kruskal, J. B. (1964). Nonmetric multidimensional scaling: A numerical method. Psychometrika, 29, 115–129. First citation in articleCrossrefGoogle Scholar

  • S. Levy (1994). Louis Guttman on theory and methodology: Selected writings. Aldershot, UK: Dartmouth. First citation in articleGoogle Scholar

  • Levy, S. (2003). Facet theory in cumulative social science. In S. LevyD. ElizurEds., Facet theory: Towards cumulative social science (pp. 5–15). Ljubljana, Slovenia: University of Ljubljana, Faculty of Arts, Center for Educational Development. First citation in articleGoogle Scholar

  • Levy, S. (2005). Guttman, Louis. In Encyclopedia of social measurement, Vol 2, pp. 175–188). San Diego, CA: Elsevier. First citation in articleCrossrefGoogle Scholar

  • Lingoes, J. C. (1973). The Guttman-Lingoes nonmetric program series. Ann Arbor, MI: Mathesis Press. First citation in articleGoogle Scholar

  • Lund, A. & Hauge, T. E. (2011). Changing objects in knowledge-creation practices. In S. LudvigsenA. LundI. RasmussenR. SäljöEds., Learning across sites: New tools, infrastructures and practices (pp. 206–221). London, UK: Routledge. First citation in articleGoogle Scholar

  • Maslovaty, N. & Levy, S. (2001). A comparative approach in developing a structural value theory. In D. ElizurEd., Facet theory: Integrating theory construction with data analysis (pp. 21–32). Prague, Czech Republic: Karlovy University of Prague. First citation in articleGoogle Scholar

  • Maslovaty, N., Marshall, A. E. & Alkin, M. C. (2001). Teachers’ perceptions structured through facet theory: Smallest space analysis versus factor analysis. Educational and Psychological Measurement, 61, 71–84. First citation in articleCrossrefGoogle Scholar

  • Merton, R. K. (1968). Social theory and social structure. New York, NY: Free Press. First citation in articleGoogle Scholar

  • Nota, L., Soresi, S. & Zimmerman, B. J. (2004). Self-regulation and academic achievement and resilience: A longitudinal study. International Journal of Educational Research, 41, 198–215. First citation in articleCrossrefGoogle Scholar

  • Perret-Clermont, A.-N. & Perret, J.-F. (2011). A new artifact in the trade: Notes on the arrival of a computer supported manufacturing system in a technical school. In S. LudvigsenA. LundI. RasmussenR. SäljöEds., Learning across sites: New tools, infrastructures and practices (pp. 87–102). London, UK: Routledge. First citation in articleGoogle Scholar

  • Pett, M. A., Lackey, N. R. & Sullivan, J. J. (2003). Making sense of factor analysis: The use of factor analysis for instrument development in health care research. Thousand Oaks, CA: Sage. First citation in articleCrossrefGoogle Scholar

  • Pintrich, P. R. & De Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82, 33–40. First citation in articleCrossrefGoogle Scholar

  • Price, L. (2014). Modelling factors for predicting student learning outcomes in higher education. In D. GijbelsV. DoncheJ. T. E. RichardsonJ. D. VermuntEds., Learning patterns in higher education: Dimensions and research perspectives (pp. 56–77). London, UK/New York, NY: Routledge/EARLI. First citation in articleGoogle Scholar

  • Reise, S. P., Waller, N. G. & Comrey, A. L. (2000). Factor analysis and scale revision. Psychological Assessment, 12, 287–297. First citation in articleCrossrefGoogle Scholar

  • Schwarz, B. & De Groot, R. (2011). Breakdowns between teachers, educators and designers in elaborating new technologies as precursors of change in education to dialogic thinking. In S. LudvigsenA. LundI. RasmussenR. SäljöEds., Learning across sites: New tools, infrastructures and practices (pp. 261–277). London, UK: Routledge. First citation in articleGoogle Scholar

  • Shirom, A. (1991, June). A facet-theoretic approach toward theorizing in labor relations. Paper presented at the Third International Facet Theory Conference, Jerusalem, Israel. First citation in articleGoogle Scholar

  • Shye, S. (1998). Modern facet theory: Content design and measurement in behavioral research. European Journal of Psychological Assessment, 14, 160–171. First citation in articleLinkGoogle Scholar

  • Snowman, J. & Biehler, R. (2006). Psychology applied to teaching (11th ed.). Boston, MD: Houghton Mifflin. First citation in articleGoogle Scholar

  • Steenbergen, M. R. (2000). Item similarity in scale analysis. Political Analysis, 8, 261–283. First citation in articleCrossrefGoogle Scholar

  • Sternberg, A. & Elizur, D. (2001). Information technology and corporate culture: A facet analysis. In D. ElizurEd., Facet theory: Integrating theory construction with data Analysis (pp. 299–310). Prague, Czech Republic: Karlovy University of Prague. First citation in articleGoogle Scholar

  • Sternberg, R. J. (1984). Advances in the psychology of human intelligence. Hillsdale, NJ: Erlbaum. First citation in articleGoogle Scholar

  • Strauss, A. L. (1987). Qualitative analysis for social scientists. Cambridge, UK: Cambridge University Press. First citation in articleCrossrefGoogle Scholar

  • Swisher, L. L., Beckstead, J. W. & Bebeau, M. J. (2004). Factor analysis as a tool for survey analysis using a professional role orientation inventory as an example. Physical Therapy, 84, 784–799. First citation in articleGoogle Scholar

  • Taylor, P., Fraser, B. & Fisher, D. (1997). Monitoring constructivist classroom learning environments. International Journal of Educational Research, 27, 293–302. First citation in articleCrossrefGoogle Scholar

  • Tucker-Drob, E. M. & Salthouse, T. A. (2009). Confirmatory factor analysis and multidimensional scaling for construct validation of cognitive abilities. International Journal of Behavioral Development, 33, 277–285. First citation in articleCrossrefGoogle Scholar

  • Valle, A., Núñez, J. C., Cabanach, R. G., González-Pienda, J. A., Rodríguez, S., Rosário, P., … Muñoz-Cadavid, M. A. (2008). Self-regulated profiles and academic achievement. Psicothema, 20, 724–731. First citation in articleGoogle Scholar

  • Van Schuur, W. H. & Leeferink, A. J. (2001). Direct analysis of circumplex structures in survey data. In D. ElizurEd., Facet theory: Integrating theory construction with data Analysis (pp. 75–86). Prague, Czech Republic: Karlovy University of Prague. First citation in articleGoogle Scholar

  • Vermunt, J. D., Bronkhorst, L. H. & Martinez-Fernandez, J. R. (2014). The dimensionality of student learning patterns in different cultures. In D. GijbelsV. DoncheJ. T. E. RichardsonJ. D. VermuntEds., Learning patterns in higher education: Dimensions and research perspectives (pp. 33–55). London, UK/New York, NY: Routledge/EARLI. First citation in articleGoogle Scholar

  • Vygotsky, L. S. (1978). Mind and society: The development of higher mental processes. Cambridge, MA: Harvard University Press. First citation in articleGoogle Scholar

  • Walling, D. R. (1987). A model for teaching writing: Process and product. Bloomington, IN: Phi Delta Kappa Educational Foundation. First citation in articleGoogle Scholar

  • Wegerif, R. & De Laat, M. (2011). Using Bakhtin to re-think the teaching of higher-order thinking for the network society. In S. LudvigsenA. LundI. RasmussenR. SäljöEds., Learning across sites: New tools, infrastructures and practices (pp. 313–329). London, UK: Routledge. First citation in articleGoogle Scholar

  • White, R. T. & Gunstone, R. (1992). Probing understanding. London, UK: The Falmer Press. First citation in articleGoogle Scholar