An Exploration of Student Attitudes towards Online Communication and Collaboration in Mathematics and Technology
Author :
Abstract
The idea of using online tools in face-to-face mathematics instruction aims to enhance student attitudes by providing more challenging problem-solving and knowledge-building platforms with more time and space flexibility. This study, which is a part of a larger study, was completed with four high school classes of two teachers. The data was collected through student and teacher interviews, teacher reflections, and the Mathematics and Technology Attitude Survey (Pierce, Stacey, and Barkatsas, 2007). Each teacher had two classes. One of each teacher’s classes was assigned as the Online- Tools class that was introduced and had access to online communication and collaboration tools; and the other class was assigned as the No- Tools class that was not introduced any online technologies. Statistical analysis of the attitude survey revealed significant differences between Online-Tools and No-Tools classes for the affective engagement subscale on 95% confidence level. For the other subscales there were some variations on the minimum, maximum, mean values and the standard deviations from pre- and post-survey; even if the difference between the overall mean values for the Online-Tools and No-Tool classes was not significant. Based on the student interviews, the majority of the students had positive attitudes towards the online tools, Voice Thread and the Google Documents, and using them in their mathematics class; and they had increased appreciation to mathematics as a field.
Keywords
Abstract
The idea of using online tools in face-to-face mathematics instruction aims to enhance student attitudes by providing more challenging problem-solving and knowledge-building platforms with more time and space flexibility. This study, which is a part of a larger study, was completed with four high school classes of two teachers. The data was collected through student and teacher interviews, teacher reflections, and the Mathematics and Technology Attitude Survey (Pierce, Stacey, and Barkatsas, 2007). Each teacher had two classes. One of each teacher’s classes was assigned as the Online- Tools class that was introduced and had access to online communication and collaboration tools; and the other class was assigned as the No- Tools class that was not introduced any online technologies. Statistical analysis of the attitude survey revealed significant differences between Online-Tools and No-Tools classes for the affective engagement subscale on 95% confidence level. For the other subscales there were some variations on the minimum, maximum, mean values and the standard deviations from pre- and post-survey; even if the difference between the overall mean values for the Online-Tools and No-Tool classes was not significant. Based on the student interviews, the majority of the students had positive attitudes towards the online tools, Voice Thread and the Google Documents, and using them in their mathematics class; and they had increased appreciation to mathematics as a field.
Keywords
- Bain, R. (1928). An attitude on attitude research. American Journal of Sociology, 33 (6) 940-957. Bandura, A. (1977). Social learning theory. Morristown, NJ: General Learning Press.
- Bandura, A. (1997). Self-efficacy: The exercise of control. New York, NY: W.H. Freeman.Blau, I., & Caspi, A. (2009). Sharing and collaborating with Google Docs: the influence of psychologicalownership, responsibility, and student’s attitudes on outcome quality. In T. Bastiaens et al. (Eds.),Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2009 (pp. 3329-3335). Chesapeake, VA: AACE. Retrieved from: http://www.editlib.org/p/32961.
- Bonk, C. J., & Graham, C. R. (2012). The handbook of blended learning: Global perspectives, local designs. San Francisco, CA. John Wiley & Sons.
- Breckler, S. J. (1984). Empirical validation of affect, behavior, and cognition as distinct components ofattitudes. Journal of Personality and Social Psychology, 47, 1191-1205. http://dx.doi.org/10.1037/0022- 3514.47.6.1191
- Breckler, S. J., & Wiggins, E. C. (1989). On defining attitude and attitude theory: One more with feeling. In A.R. Pratkanis, S. J. Breckler, & A. G. Greenwald (Eds.), Attitude, Structure and Function,(pp. 407-427). Hillsdale, NJ: Erlbaum.
- Brewe, E., Kramer, L., & O’Brien, G. (2009). Modeling instruction: Positive attitudinal shifts in introductoryphysics measured with CLASS. Physical Review Special Topics-Physics Education Research, 5(1), 013102. http://dx.doi.org/10.1103/PhysRevSTPER.5.013102
- Conner, N. (2008). Google Apps: The missing manual. Sebastopol, CA: O’Reilly Media.
- Crano W. D., & Prislin, R. (2008). Attitudes and attitude change. New York, NY: Psychology Press.
- Dillenbourg, P., Järvelä, S., & Fischer, F. (2009). The evolution of research on computer-supportedcollaborative learning: from design to orchestration. In N. Balacheff, S. Ludvigsen, T. de Jong, A.Lazonder, & S. Barnes (Eds.), Technology-Enhanced Learning: Principles and Products (pp. 3-19). Netherlands: Springer.
- Educause Learning Initiative (2008). 7 things you should know about Google Apps. Retrieved October 1, 2010, from http://net.educause.edu/ir/library/pdf/ELI7035.pdf
- Galbraith, P., & Haines, C. (1998). Disentangling the nexus: Attitudes to mathematics and technology in a computer learning environment. Educational Studies in Mathematics, 36, 275–290.
- Garcia, M. D. M. & Romero, I. M. (2009). The influence of new technologies on learning and attitudes inmathematics in secondary students. Electronic Journal of Research in Educational Psychology, 17(7), 369– 396.
- Glesne, C. (1999). Becoming qualitative researchers (2nd ed.). White Plains, NY: Longman Publishers.
- Goodnight, J. H. (1978). Tests of hypotheses in fixed effects linear models. SAS Technical Report R-101. Cary, NC: SAS Institute, Inc.
- Graham, C. R., & Dziuban, C. (2007). Blended learning environments. Handbook of Research on EducationalCommunications and Technology: A Project of the Association for Educational Communications and Technology, 2, 269.
- Gress, M. F., Hadwin, A., & Winne, P. (2010). Measurement and assessment in computer- supported collaborative learning. Computers in Human Behavior, 26 (5), 806-814. doi:10.1016/j.chb.2007.05.012
- Hannula, M. S. (2002). Attitude towards mathematics: Emotions, expectations and values. Educational Studies in Mathematics, 49, 25–46. doi: 10.1023/A:1016048823497
- Hoyles, C., & Lagrange, J.-B. (Eds.). (2009). Mathematics education and technology—rethinking the terrain. The 17th ICMI study. Heidelberg, New York: Springer.
- Krebs, M., Ludwig, M., & Müller, W. (2010). Learning mathematics using a wiki. Procedia -Social and Behavioral Sciences, 2(2), 1469–1476. doi: 10.1016/j.sbspro.2010.03.220
- Li, Q., & Ma, X. (2010). A meta-analysis of the effects of computer technology on school students’ mathematics learning. Educational Psychology Review, 22, 215–243. doi: 10.1007/s10648-010-9125-8
- Merriam, S. B. (2009). Qualitative research: A guide to design and implementation. San Francisco, CA: John Wiley & Sons.
- Mindset Project. (2014). Retrieved October 30, 2014, from http://www.mindsetproject.org/
- Nguyen, D M., Yi-Chuan J. H., & Allen, D. (2006). The impact of web-based assessment and practice onstudents’ mathematic learning attitudes. Journal of Computers in Mathematic & Science Teaching, 25(3), 251–279.
- Ozel, S., Yetkiner, Z. E., & Capraro, R. M. (2008). Technology in K-12 mathematics classrooms. School Science and Mathematics, 108(2), 80–85. doi: 10.1111/j.1949-8594.2008.tb17807.x
- Pape, L. (2010). Blended teaching & learning: Developing courses that combine face-to-face and virtual instruction in pursuit of 21st-century skills in classroom. The School Administrator, 4(67), 16–21.
- Picciano, A. G., Dziuban, C. D., & Graham, C. R. (Eds.). (2014). Research Perspectives in Blended Learning: Research Perspectives (Vol. 2). New York, NY: Routledge.
- Pierce, R., Stacey, K., & Barkatsas, A. (2007). A scale for monitoring students’ attitudes to learningmathematics with technology. Computers & Education, 48, 285–300. doi:10.1016/j.compedu.2005.01.006
- Reed, H. C., Drijvers, P., & Kirschner, P. A. (2010). Effects of attitudes and behaviors on learningmathematics with computer tools. Computers & Education, 55, 1–15. doi: 10.1016/j.compedu.2009.11.012
- Resta, P., & Laferrière, T. (2007). Technology in support of collaborative learning. Educational Psychology Review, 19(1), 65–83. doi: 10.1007/s10648-007-9042-7
- Ruffell, M., Mason, J., & Allen, B. (1998). Studying attitude to mathematics. Educational Studies in Mathematics, 35, 1–18.
- So, H. J., & Bonk, C. J. (2010). Examining the roles of blended learning approaches in computer-supportedcollaborative learning (CSCL) environments: A Delphi study. Educational Technology & Society, 13(3), 189–200.
- So, H. J. (2009). When groups decide to use asynchronous online discussions: collaborative learning andsocial presence under voluntary participation structure. Journal of Computer Assisted Learning, 25(2), 143– 160. doi: 10.1111/j.1365-2729.2008.00293.x
- Spradlin, K. D. (2009). The effectiveness of computer-assisted instruction in developmental mathematics. Doctoral Dissertations and Projects. (221)
- Vygotsky, L.S. (1978). Mind in society. Cambridge, MA: Harvard University Press.
- Wilson, P. (2008). Promoting positive attitudes. Mathematics Teaching Incorporating Micromath, 208, 14-16. Appendix A