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Examining Factors That Influence the Effectiveness of Learning Objects in Mathematics Classrooms

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Abstract

Learning objects are interactive online tools that support the acquisition of specific concepts. Limited research has been conducted on factors that affect the use of learning objects in K-12 mathematics classrooms. The current study examines the influence of student characteristics (gender, age, computer comfort level, subject comfort level, and mathematics grade), instructional design (structured vs. open ended), and teaching strategy (teacher led vs. student based) on student attitudes toward the use of learning objects and learning performance. Data in the form of surveys and pre- and posttests were collected from 286 middle and secondary school students. Higher computer and subject area comfort ratings were significantly correlated with more positive student attitudes about learning objects. Older students in higher grades learned more than younger students in lower grades after using learning objects. Learning performance was significantly higher for students who used structured (vs. open-ended) learning objects and participated in teacher-led (vs. student-based) lessons. It is speculated that younger students might need more scaffolding when using mathematics-based learning objects.

Résumé

Les objets d’apprentissages sont des outils en ligne qui facilitent l’acquisition de certains concepts spécifiques. Il y a peu de recherches sur les facteurs qui affectent l’utilisation des objets d’apprentissage dans les cours de mathématiques en cinquième année de secondaire. La présente étude se penche sur l’influence des caractéristiques individuelles des étudiants (sexe, âge, habiletés informatiques, connaissance de la matière et notes obtenues en mathématiques), le type de matériel pédagogique (structuré ou ouvert) et les stratégies d’enseignement (enseignement dirigé par les enseignant ou basé sur les apprenants) sur les attitudes à l’égard de l’utilisation des objets d’apprentissage et la performance. Les données, sous forme d’enquêtes et de pré-tests et post-tests, ont été recueillies à partir des réponses de 286 étudiants de niveau élémentaire (deuxième cycle) et secondaire. Il y a une corrélation significative entre d’une part les habiletés informatiques ainsi que le niveau de connaissance de la matière, et d’autre part l’attitude positive devant les objets d’apprentissage. Les étudiants plus âgés et ceux des niveaux supérieurs ont mieux appris grâce à l’utilisation des objets d’apprentissage que les élèves les plus jeunes et ceux des niveaux inférieurs. La performance d’apprentissage est significativement plus élevée chez les étudiants qui ont utilisé des objets d’apprentissage structurés et chez ceux qui ont participé à des cours dirigés par les enseignants. Nous avançons l’hypothèse que les élèves les plus jeunes ont besoin d’un soutien plus marqué lorsqu’ils se servent des objets d’apprentissage en mathématiques.

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References

  • Agostinho, S., Bennett, S., Lockyear, L., & Harper, B. (2004). Developing a learning object metadata application profile based on LOM suitable for the Australian higher education market. Australasian Journal of Educational Technology, 20(2), 191–208. Retrieved from http://www.ascilite.org.au/ajet/ajet20/agostinho.html

    Article  Google Scholar 

  • Alonso, F., Lopez, G., Manrique, D., & Vines, J. M. (2005). An instructional model for Web-based e-learning education with a blended learning process approach. British Journal of Educational Technology, 36(2), 217–235. doi:10.1111/j.1467-8535.2005.00454.x

    Article  Google Scholar 

  • American Association of University Women. (2000). Tech-savvy: Educating girls in the new computer age. Washington, DC: Author. Retrieved from http://www.aauw.org/member_center/publications/TechSavvy/TechSavvy.pdf

    Google Scholar 

  • Anderson, L. W., & Krathwohl, D. R. (Eds.). (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom’s taxonomy of educational objectives. New York, NY: Longman.

    Google Scholar 

  • Barkley, E. F. (2010). Student engagement techniques. San Francisco, CA: John Wiley & Sons.

    Google Scholar 

  • Bower, M. (2005). Online assessment feedback: Competitive, individualistic, or … preferred form! Journal of Computers in Mathematics and Science Teaching, 24(2), 121–147.

    Google Scholar 

  • Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.). (2000). How people learn. Washington, DC: National Academy Press.

    Google Scholar 

  • Bruner, J. (1986). Actual minds, possible worlds. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Butson, R. (2003). Learning objects: weapons of mass instruction. British Journal of Educational Technology, 34(5), 667–669. doi:10.1046/j.0007-1013.2003.00359.x

    Article  Google Scholar 

  • Clark, R. V. (2008). Building expertise: Cognitive methods for training and performance improvement. San Francisco, CA: John Wiley & Sons.

    Google Scholar 

  • Clarke, O., & Bowe, L. (2006a). The Learning Federation and the Victorian Department of Education and Training trial of online curriculum content with Indigenous students. Retrieved from http://www.sofweb.vic.edu.au/edulibrary/public/teachlearn/ict/TLF_DETVIC_indig_trial_mar06.pdf

    Google Scholar 

  • Clarke, O., & Bowe, L. (2006b). The Learning Federation and the Victorian Department of Education and Training trial of online curriculum content with ESL students. Retrieved from http://www.thelearningfederation.edu.au/verve/_resources/report_esl_final.pdf

    Google Scholar 

  • Cohen, J. (1988). Statistical power analysis for the behavioural sciences (2nd ed.). New York, NY: Academic Press.

    Google Scholar 

  • Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. doi:10.1037/0033-2909.112.1.155

    Article  Google Scholar 

  • Concannon, F., Flynn, A., & Campbell, M. (2005). What campus-based students think about the quality and benefits of e-learning. British Journal of Educational Technology, 36(3), 501–512. doi:10.1111/j.1467-8535.2005.00482.x.

    Article  Google Scholar 

  • Cronbach, L. J., & Snow, R. E. (1977). Aptitudes and instructional methods: A handbook for research on interactions. New York, NY: Irvington.

    Google Scholar 

  • De Salas, K., & Ellis, L. (2006). The development and implementation of learning objects in a higher education. Interdisciplinary Journal of Knowledge and Learning Objects, 2, 1–22. Retrieved from http://www.ijello.org/Volume2/v2p001-022deSalas.pdf.

    Google Scholar 

  • Grouws, D. A. (2004). Handbook of research on mathematics teaching and learning. Reston, VA: National Council for Teachers of Mathematics.

    Google Scholar 

  • Haughey, M., & Muirhead, B. (2005). Evaluating learning objects for schools. Australasian Journal of Educational Technology, 21(4), 470–490. Retrieved from http://www.ascilite.org.au/ajet/ajet21/haughey.html.

    Article  Google Scholar 

  • Kay, R. H. (2009). Understanding factors that influence of the effectiveness of learning objects in secondary school classrooms. In L. T. W. Hin & R. Subramaniam (Eds.), Handbook of research on new media literacy at the K-12 level: Issues and challenges (pp. 419–435). Hershey, PA: Information Science Reference.

    Chapter  Google Scholar 

  • Kay, R. H. (2011a). Appendix A—List of learning objects used in mathematics study. Retrieved from http://faculty.uoit.ca/kay/res/math/.

    Google Scholar 

  • Kay, R. H. (2011b). Appendix B—Learning object survey for students. Retrieved from http://faculty.uoit.ca/kay/res/math/ss_math.pdf.

    Google Scholar 

  • Kay, R. H. (2011c). Exploring the influence of context on attitudes toward Web-Based Learning Tools (WBLTs) and learning performance. Journal of E-Learning and Learning Objects, 7, 125–142. Retrieved from http://www.ijello.org/Volume7/IJELLOv7p125-142Kay748.pdf

    Google Scholar 

  • Kay, R. H., & Knaack, L. (2005). Developing learning objects for secondary school students: A multicomponent model. Interdisciplinary Journal of E-Learning and Learning Objects, 1, 229–254. Retrieved from http://www.ijello.org/Volume1/v1p229-254Kay_Knaack.pdf

    Article  Google Scholar 

  • Kay, R. H., & Knaack, L. (2007a). Evaluating the learning in learning objects. Open Learning, 22(1), 5–28. doi:10.1080/02680510601100135

    Article  Google Scholar 

  • Kay, R. H., & Knaack, L. (2007b). Evaluating the use of learning objects for secondary school science. Journal of Computers in Mathematics and Science Teaching, 26(4), 261–289.

    Google Scholar 

  • Kay, R. H., & Knaack, L. (2008a). A formative analysis of individual differences in the effectiveness of learning objects in secondary school. Computers & Education, 51(3), 1304–1320.

    Article  Google Scholar 

  • Kay, R. H., & Knaack, L. (2008b). A multi-component model for assessing learning objects: The learning object evaluation metric (LOEM). Australasian Journal of Educational Technology, 24(5), 574–591. Retrieved from http://www.ascilite.org.au/ajet/ajet24/kay.pdf.

    Article  Google Scholar 

  • Kay, R. H., & Knaack, L. (2008c). An examination of the impact of learning objects in secondary school. Journal of Computer Assisted Learning, 24(6), 447–461. doi:10.1111/j.1365-2729.2008.00278.x

    Article  Google Scholar 

  • Kay, R. H., & Knaack, L. (2008d). Investigating the use of learning objects in secondary school mathematics. Interdisciplinary Journal of E-Learning and Learning Objects, 4, 269–289. Retrieved from http://ijello.org/Volume4/IJELLOv4p269-289Kay.pdf

    Article  Google Scholar 

  • Kay, R.H., & Knaack, L. (2009a). Analyzing the effectiveness of learning objects for secondary school science classrooms. Journal of Educational Multimedia and Hypermedia, 18(1), 113–135.

    Google Scholar 

  • Kay, R. H., & Knaack, L. (2009b). Assessing learning, design and engagement in learning objects: The learning object evaluation scale for students (LOES-S). Education Technology Research and Development, 57(2), 147–168. doi:10.1007/s11423-008-9094-5

    Article  Google Scholar 

  • Kay, R. H., Knaack, L., & Muirhead, B. (2009). A formative analysis of instructional strategies for using learning objects. Journal of Interactive Learning Research, 20(3), 295–315.

    Google Scholar 

  • Kilpatrick, J., Martin, W. G., & Schifter, D. (2003). A research companion to principles and standards for school mathematics. Reston, VA: National Council for Teachers of Mathematics.

    Google 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(2), 75–86. doi:10.1207/s15326985ep4102 1

    Article  Google Scholar 

  • Kong, S. C., & Kwok, L. F. (2005). A cognitive tool for teaching the addition/subtraction of common fractions: A model of affordances. Computers and Education, 45(2), 245–265. doi:10.1016/j.compedu.2004.12.002

    Article  Google Scholar 

  • Lim, C. P., Lee, S. L., & Richards, C. (2006). Developing interactive learning objects for a computing mathematics models. International Journal on E-Learning, 5(2), 221–244.

    Google Scholar 

  • Liu, M., & Bera, S. (2005). An analysis of cognitive tool use patterns in a hypermedia learning environment. Educational Technology, Research and Development, 51(3), 5–21. doi:10.1007/BF02504854

    Article  Google Scholar 

  • Lopez-Morteo, G., & Lopez, G. (2007). Computer support for learning mathematics: A learning environment based on recreational learning objects. Computers and Education, 48(4), 618–641. doi:10.1016/j.compedu.2005.04.014

    Article  Google Scholar 

  • Lowe, K., Lee, L., Schibeci, R., Cummings, R., Phillips, R., & Lake, D. (2010). Learning objects and engagement of students in Australian and New Zealand schools. British Journal of Educational Technology, 41(2), 227–241. doi:10.1111/j.1467-8535.2009.00964.x

    Article  Google Scholar 

  • Mason, R., Pegler, C., & Weller, M. (2005). A learning object success story. Journal of Asynchronous Learning Networks, 9(1), 97–105. Retrieved from http://oro.open.ac.uk/6624/1/v9n1_mason.pdf

    Google Scholar 

  • Mayer, R. (2004). Should there be a three-strikes rule against pure discovery learning? The case for guided methods of instruction. American Psychologist, 59(1), 14–19. doi:10.1037/0003-066X.59.1.1

    Article  Google Scholar 

  • McCormick, R., & Li, N. (2005). An evaluation of European learning objects in use. Learning, Media and Technology, 31(3), 213–231. doi:10.1080/17439880600893275

    Article  Google Scholar 

  • McGreal, R. (2004). Learning objects: A practical definition. International Journal of Instructional Technology and Distance Learning, 1(9). Retrieved from http://www.itdl.org/journal/sep 04/article02.htm

  • Montgomery, K. C. (2009). Generation digital. Cambridge, MA: MIT Press.

    Google Scholar 

  • National Council of Teachers of Mathematics. (2011). Principles and standards for school mathematics. Retrieved from http://www.nctm.org/uploadedFiles/Math_Standards/12752_exec_pssm.pdf

    Google Scholar 

  • Nurmi, S., & Jaakkola, T. (2006). Effectiveness of learning objects in various instructional settings. Learning, Media, and Technology, 31(3), 233–247. doi:10.1080/17439880600893283

    Article  Google Scholar 

  • Palfrey, J., & Gasser, U. (2008). Born digital. New York, NY: Basic Books.

    Google Scholar 

  • Parrish, P. E. (2004). The trouble with learning objects. Educational Technology Research & Development, 52(1), 49–67. doi:10.1007/BF02504772

    Article  Google Scholar 

  • Reimer, K., & Moyer, P. S. (2005). Third-graders learning about fractions using virtual manipulatives: A classroom study. Journal of Computers in Mathematics and Science Teaching, 24(1), 5–25.

    Google Scholar 

  • Sanders, J. (2006). Gender and technology: A research review. In C. Skelton, Francis, & L. Smulyan (Eds.), Handbook of gender and education (pp. 307–322). London, England: Sage.

    Chapter  Google Scholar 

  • Schoner, V., Buzza, D., Harrigan, K., & Strampel, K. (2005). Learning objects in use: “Lite” assessment for field studies. Journal of Online Learning and Teaching, 1(1), 1–18.

    Google Scholar 

  • Sedig, K., & Liang, H. (2006). Interactivity of visual mathematical representations: Factors affecting learning and cognitive processes. Journal of Interactive Learning Research, 17(2), 179–212.

    Google Scholar 

  • Sowder, J., & Schappelle, B. (2002). Lessons learned from research. Reston, VA: National Council for Teachers of Mathematics.

    Google Scholar 

  • Steffe, L., & Gale, J. (Eds.). (1995). Constructivism in education. Hillsdale, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. doi:10.1207/s15516709cog1202 4.

    Article  Google Scholar 

  • Tapscott, D. (2008). Grown up digital: How the Net generation is changing your world. New York, NY: McGraw-Hill.

    Google Scholar 

  • van Merrienboer, J. J. G., & Ayres, P. (2005). Research on cognitive load theory and its design implications for e-learning. Education Technology Research and Development, 53(3), 1042–1629. doi:10.1007/BF02504793

    Google Scholar 

  • Vannatta, R. A., & Beyerbach, B. (2000). Facilitating a constructivist vision of technology integration among education faculty and preservice teachers. Journal of Research on Computing in Education, 33(2), 132–148.

    Article  Google Scholar 

  • Vygotsky, L. S. (1978). Mind in society. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Whitley, B. E., Jr. (1997). Gender differences in computer-related attitudes and behaviors: A meta-analysis. Computers in Human Behavior, 13(1), 1–22. doi:10.1016/S0747-5632(96)00026-X

    Article  Google Scholar 

  • Wiley, D., Waters, S., Dawson, D., Lambert, B., Barclay, M., & Wade, D. (2004). Overcoming the limitations of learning objects. Journal of Educational Multimedia and Hypermedia, 13(4), 507–521.

    Google Scholar 

  • Willingham, D. T. (2009). Why don’t students like school? San Francisco, CA: Jossey-Bass.

    Google Scholar 

  • Wlodkowski, R. J. (2008). Enhancing adult motivation to learn: A comprehensive guide for teaching all adults. San Francisco, CA: Jossey-Bass.

    Google Scholar 

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Kay, R.H. Examining Factors That Influence the Effectiveness of Learning Objects in Mathematics Classrooms. Can J Sci Math Techn 12, 350–366 (2012). https://doi.org/10.1080/14926156.2012.732189

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