The research and innovation in the field of computer and technology has made significant contribution for the development of new pedagogical strategies in all levels of education. The use of digital tools like animation has changed the way of providing education, especially in primary school level, adding an element of entertainment to the process of teaching and learning. It is assumed that the use of animated instructional material can help to present a complex concept in a simple form, create more interest about the subject, motivate the pupil for better learning, increase the accuracy of the message and play a crucial role in improving the students’ academic performance. Against this background, the present paper attempts to assess the efficacy of animation on different subjects in primary education. Here, in the study, an experiment has been conducted using animation to teach three subjects Mathematics, Language and Science; and students’ performance was compared and analyzed using fuzzy statistical tools.
References
[1]
Akbari, M. G., & Rezaeim, A. (2009). Bootstrap Statistical Inference for the Variance Based on the Data. Austrian Journal of Statistics, 38, 121-130.
[2]
Arnold, B. F. (1998). Testing Fuzzy Hypothesis with Crisp Data. Fuzzy Sets and Systems, 94, 323-333.
http://dx.doi.org/10.1016/S0165-0114(96)00258-8
[3]
Betrancourt, M., & Chassot, A. (2008). Making Sense of Animation: How Do Children Explore Multimedia Instruction? In R. Lowe, & W. Schnotz, (Eds.), Learning with Animation: Research Implications for Design (pp. 149-164). New York: Cambridge UP.
[4]
Casals, M. R., & Gil, M. A. (1989). A Note on Operativeness of Neyman-Pearson Tests with Fuzzy Information. Fuzzy Sets and Systems, 30, 215-220. http://dx.doi.org/10.1016/0165-0114(89)90082-1
[5]
Chizmar, J., & Walbert, M.(1999). Web-Based Learning Environments Guided by Principles of Good Teaching Practice. The Journal of Economic Education, 30, 248-259. http://dx.doi.org/10.1080/00220489909595985
[6]
Easingwood, N. (2000). Electronic Communication in the Twenty-First-Century Classroom. In N. Gamble, & N. Easingwood (Eds.), ICT and Literacy (pp. 45-58). New York: Continnum.
[7]
Fine, C., & Thornbury, M. L. (2006). ICT Play and Exploration. In M. Hayes, & D. Whitebread (Eds.), ICT in Years (pp. 21-37). New York: Open University Press.
[8]
Grzegorzewski, P. (1998). Statistical Inference about the Median from Vague Data. Control and Cybernatics, 27, 447-464.
[9]
Grzegorzewski, P. (2004). Distribution-Free Tests for Vague Data. Soft Methodology and Random Information Systems (pp. 495-502). Heidelberg: Springer. http://dx.doi.org/10.1007/978-3-540-44465-7_61
[10]
Hegarty, M., & Kriz, S. (2008). Effects of Knowledge and Spatial Ability on Learning from Animation. In R. Lowe, & W. Schnotz (Eds.), Learning with Animation: Research Implications for Design (pp. 1-27). New York: Cambridge UP.
[11]
Mayer, R. E. (2008). Research Based Principles for Learning with Animation. In L. Richard, & W. Schnotz (Eds.), Learning with Animation: Research Implications for Design (pp. 30-46). New York: Cambridge UP.
[12]
Molenda, M., & Sullivan, M. (2003). Issues and Trends in Instructional Technology. In Branch, & R. Marbie (Eds.), Education and Media Technology Year Book (pp. 3-21). London: Libraries Unlimited.
[13]
Montenegro, M., Casals, M. R., Lubiano, M. A., & Gil, M. A. (2001). Two-Sample Hypothesis Tests of Means of a Fuzzy Random Variable. Information Sciences, 133, 89-100. http://dx.doi.org/10.1016/S0020-0255(01)00078-0
[14]
Narayanan, N. H., & Hegarty, M. (1998). On Designing Comprehensible Hypermedia Manuals. International Journal of Human Computer Studies, 48, 267-301. http://dx.doi.org/10.1006/ijhc.1997.0169
[15]
Parchami, A., Mashinchi, M., Yavari, A. R., & Reza, H. (2005). Process Capability Indices as Fuzzy Numbers. Austrian Journal of Statistics, 34, 391-402.
[16]
Pearson J. C., Nelson, P. E., Titsworth, S., & Harter, L. (2011). Human Communication (4th ed.). New York: Macgrow.
[17]
Rogers, Y. (2008). A Comparison of How Animation Has Been Used to Support Formal, Informal, and Playful Learning. In L. Richard, & W. Schnotz (Ed.), Learning with Animation: Research Implications for Design (pp. 286-303). New York: Cambridge UP.
[18]
Schontz, W., & Rasch, T. (2008). Functions of Animation in Comprehension and Learning. In L. Richard, & W. Schnotz (Ed.), Learning with Animation: Research Implications for Design (pp. 92-113). New York: Cambridge UP.
[19]
Tyagi, S. K., & Akram, M. (2013). Human Reliability Evaluation for Offshore Platform Musters Using Intuitionistic Fuzzy Sets. IEEE Transactions on Fuzzy Systems, 21, 1115-1122. http://dx.doi.org/10.1109/TFUZZ.2013.2243734
[20]
Wrench, J. S., Virginia, P. R., & Joan (2009). Communication, Affect & Learning in the Classroom (3rd ed.). CA: Virginia Peck Richmond.
[21]
Younger, T., & Narayanan, H. (2008). Turning the Table: Investigating Characteristics and Efficacy of Student Authored Animations and Multimedia Representations. In L. Richard, & W. Schnotz (Ed.), Learning with Animation: Research Implications for Design (pp. 263-268). New York: Cambridge UP.
[22]
Zadeh, L. A. (1965). Fuzzy Sets. Information and Control, 8, 338-353. http://dx.doi.org/10.1016/S0019-9958(65)90241-X