JST Vol. 21 (1) Jan. 2013 - Pertanika Journal - Universiti Putra ...

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REFERENCES Yogan Jaya Kumar, Naomie Salim, Ahmed Hamza Osman and Albaraa Abuobieda Chang, C. C., & Lin C. J. (2011). LIBSVM: a library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 227(1-27), 27. Cristianini, N., & Shawe-Taylor, J. (2000). An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods. Cambridge: Cambridge University Press. Erkan, G., & Radev D. R. (2004). LexPageRank: Prestige in multi-document text summarization. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, 365-371. Jorge, M. L. C., & Pardo, T. S. (2010). Experiments with CST-based Multidocument Summarization. Workshop on Graph-based Methods for Natural Language Processing, ACL, 74–82. Miyabe, Y., Takamura, H., & Okumura, M. (2008). Identifying cross-document relations between sentences. In Proceedings of the 3 rd International Joint Conference on Natural Language Processing, 141–148. Radev, D. R. (2000). A Common Theory of Information Fusion from Multiple Text Sources Step One: Cross-Document Structure. Paper presented at the 1 st ACL SIGDIAL Workshop on Discourse and Dialogue, 10, pp.74-83. Radev, D. R., & Otterbacher, J. (2003). CSTBank Phase I. Retrieved at http://tangra.si.umich.edu/clair/ CSTBank/phase1.htm Taboada, M., & Mann, W. C. (2006). Rhetorical Structure Theory: Looking Back and Moving Ahead. Discourse Studies, 8, 423-459. Vapnik, V. (1995). The Nature of Statistical Learning Theory. New York: Springer Verlag. Zahri, N. A. H .B., & Fukumoto, F. (2011). Multi-document Summarization Using Link Analysis Based on Rhetorical Relations between Sentences. Paper presented at the 12 th International Conference on Computational Linguistics and Intelligent Text Processing, 2, pp.328-338. Zhang, Z., Blair-Goldensohn, S., & Radev, D. R. (2002). Towards CST-Enhanced Summarization. Paper presented at the 18th National Conference on Artificial Intelligence, pp.439-446. Zhang, Z., Otterbacher, J., & Radev, D. R. (2003). Learning cross-document structural relationships using boosting. Paper presented at the 12 th International Conference on Information and Knowledge Management, pp.124-130. 246 Pertanika J. Sci. & Technol. 21 (1): 283 - 298 (2013)
ISSN: 0128-7680 © 2013 Universiti Putra Malaysia Press. Pertanika J. Sci. & Technol. 21 (1): 247 - 260 (2013) SCIENCE & TECHNOLOGY Journal homepage: http://www.pertanika.upm.edu.my/ Usability of Educational Computer Game (UsaECG): A Quantitative Approach Hasiah Mohamed@Omar 1 *, Azizah Jaafar 2 and Rohana Yusoff 1 1 Faculty of Computer & Mathematical Sciences, Universiti Teknologi MARA, 23000 Dungun, Terengganu, Malaysia 2 Institute of Visual Informatics, Universiti Kebangsaan Malaysia , 43600 Bangi, Selangor, Malaysia ABSTRACT Heuristic Evaluation (HE) is used as a basis in developing a new technique to evaluate usability or educational computer games known as Playability Heuristic Evaluation for Educational Computer Game (PHEG). PHEG was developed to identify usability problems that accommodate five heuristics, namely, interface, educational elements, content, playability and multimedia. In HE process, usability problems are rated based on severity score and this is followed by presentation of a mean value. The mean value is used to determine the level of usability problems; however, in some cases, this value may not accurate because it will ignore the most critical problems found in a specific part. In developing PHEG, a new quantitative approach was proposed in analyzing usability problems data. Numbers of sub-heuristics for each heuristic involved were taken into account in calculating percentage for each heuristic. Functions to calculate critical problems were also introduced. Evaluation for one educational game that was still in development process was conducted and the results showed that most of the critical problems were found in educational elements and content heuristics (57.14%), while the least usability problems were found in playability heuristic. In particular, the mean value in this analysis can be used as an indicator in identifying critical problems for educational computer games. Keywords: Usability of educational computer game, tool, interface, playability, multimedia Article history: Received: 31 March 2012 Accepted: 31 August 2012 E-mail addresses: hasia980@tganu.uitm.edu.my (Hasiah Mohamed@Omar), aj@ftsm.ukm.my (Azizah Jaafar), rohanayu@tganu.uitm.edu.my (Rohana Yusoff) *Corresponding Author INTRODUCTION In application development process, evaluation plays an important and integral part. This evaluation can be carried out either during the development (formative) or once the development is completed (summative). Expert evaluators may involve in any stage either formative or summative and real (potential) users are normally involved during summative evaluation. Meanwhile, selection
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Surface Roughness Y. Yusuf, J. M. J
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DISCUSSION Y. Yusuf, J. M. Juoi, Z.
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Modelling of Motion Resistance Rati
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Norhashila Hashim et al. effectiven
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Statistical Analysis Norhashila Has
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