We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

The Effect of Presentation Variety of Interactive Multimedia Learning to the Learning Result

by Muhammad Ruslia
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 122 - Number 10
Year of Publication: 2015
Authors: Muhammad Ruslia
10.5120/21734-4921

Muhammad Ruslia . The Effect of Presentation Variety of Interactive Multimedia Learning to the Learning Result. International Journal of Computer Applications. 122, 10 ( July 2015), 7-12. DOI=10.5120/21734-4921

@article{ 10.5120/21734-4921,
author = { Muhammad Ruslia },
title = { The Effect of Presentation Variety of Interactive Multimedia Learning to the Learning Result },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 122 },
number = { 10 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 7-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume122/number10/21734-4921/ },
doi = { 10.5120/21734-4921 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:10:11.212384+05:30
%A Muhammad Ruslia
%T The Effect of Presentation Variety of Interactive Multimedia Learning to the Learning Result
%J International Journal of Computer Applications
%@ 0975-8887
%V 122
%N 10
%P 7-12
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This research aims to investigate the impact of many kinds of computer-based interactive multimedia learning presentation to the learning result by controlling the student's prior knowledge. The kinds of learning presentation consist of multimedia learning with high interactivity ([animation visualization + narration] and [static visualization + clue + narration]) and multimedia learning with low interactivity ([animation visualization + narration] and [static visualization + clue + narration]). The research method used quasi experimental approach, with the kinds of multimedia learning presentation act as independent variable with 4 kinds of treatment, the student's learning result as the dependent variable, and student's prior knowledge as the covariate variable. The research was conducted in STMIK STIKOM Bali with the research subject is the students of even semester 2013/2014, and the analysis method used the Covariance Analysis. Based on the analysis results, it can be concluded that by controlling the student's prior knowledge of high interactivity multimedia learning group (built by Adobe Flash) is more effective than the low interactivity multimedia learning group (built by PowerPoint and Screencast-O-Matic). Besides that, on the high interactivity multimedia learning group, the effectiveness of the visualization content through animation+narration is equal with the content visualization through static visualization+clue+narration. This condition is also applied with the low interractivity multimedia learning.

References
  1. Clark, R. C. (2008). Developing Technical Training: A Structured Approach for Developing Classroom and Computer-Based Instructional Materials. Third Edition. San Francisco: John Wiley & Sons, Inc.
  2. Clark, R. C. & Mayer, R. E. (2008). E-Learning and The Science Of Instruction. Second Edition. San Francisco: In Print of Wiley.
  3. Mayer, R. E. & Moreno, R. (2002). Animation as an Aid to Multimedia Learning. Educational Psychology Review; 14,1; 87-99.
  4. Hasler, B. S. , Kersten, B. & Sweller, J. (2007). Learner Control, Cognitive Load and Instructional Animation. Applied Cognitive Psychology Journal; 21; 713-729.
  5. McCann, B. M. (2006). The Relationship between Learning Styles, Learning Environments, and Student Success. Journal of Agricultural Education; 47,3; 14-23.
  6. Guttormsen Schär, S. G. & Zimmermann, P. G. (2007). Investigating Means to Re-duce Cognitive Load from Animations Applying Differentiated Measures of Knowledge Representations. Journal of Research on Technology in Education; 40,1; 64.
  7. Passerini, K. (2007). Performance and Behavioral Outcomes in Technology-Supported Learning: The Role of Interactive Multimedia. Journal of Educational Multimedia and Hypermedia; 16,2; 183-211.
  8. Lin, H. & Dwyer, F. M. (2010). The Effect of Static and Animated Visualization: a Perspective of Instructional Effectiveness and efficiency. Educational Technology, Research and Development; 58; 155-174.
  9. Vaughan, T. (2006). Multimedia: Making It Work. Yogyakarta: Andi.
  10. Mayer, R. E. & Moreno, R. (2003). Nine Ways to Reduce Cognitive Load in Multimedia Learning. Educational Psychologist; 38,1; 43-52.
  11. Santrock, J. W. (2008). Psikologi Pendidikan. Edisi Kedua. Jakarta: Kencana.
  12. Rusli, M. , Ardhana, I. W. , Degeng, I. N. S & Kamdi, W. (2014). The Effect of Presentation Strategy on Multimedia Learning—Animation vs Static Visualization—and Learning Style to Learning Result. Journal of Academic Research International; 5,1; 216-226.
  13. Sien, V. Y. 2009. BIT 201 Object-Oriented Modelling using UML. Lecture 1-8, lecturing items of Dual-Degree Program. STMIK-STIKOM Bali Denpasar and HELP University College Kualalumpur.
  14. Hair, J. F. Jr. , Black, W. C. , Babin, B. J. , Anderson, R. E. & Tatham, R. L. 2006. Multivariate Data Analysis. Sixth Edition. Upper Saddle River, New Jersey: Pearson Education, Inc.
  15. Field, A. (2012). Analysis of Covariance. www. discoveringstatistics. com. Accessed date: June 28, 2014.
Index Terms

Computer Science
Information Sciences

Keywords

Multimedia learning animation high interactivity low interactivity prior knowledge learning result.

Powered by PhDFocusTM