UPSI Digital Repository (UDRep)
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UPSI Digital Repository (UDRep)
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| Abstract : Universiti Pendidikan Sultan Idris |
| Personalization is a good supplement for learning process. It has been claimed that personalization has a huge potential of providing solution to facilitate the learning path based on children ability and preferences. Diverse research on personalized learning for children have been conducted which, are commonly concerns on the development and implementation of personalized learning products and services. However these researches have little emphasized in exploring slow learner personalized learning process particularly on their reading ability. With that, this paper aims to highlight two key important processes of personalization for slow learner children which are construction of user profile and scenario. The scope of this study is on personalization of reading for slow learner children. There were 13 slow learner children with reading difficulties from primary school participated in this study. The key findings from this study are the construction of user profile and scenario that represent the personalization for reading. These user profile and scenario construction then provide guidelines for the development of personalized interface design for slow learner reading application. |
| References |
[1] S. Cakula and M. Sedleniece, “Development of a personalized e-learning model using methods of ontology,” Procedia Comput. Sci., vol. 26, no. December, pp. 113–120, 2013. https://doi.org/10.1016/j.procs.2013.12.011 [2] T. Yang, G. Hwang, and S. J. Yang, “Development of an Adaptive Learning System with Multiple Perspectives based on Students’ Learning Styles and Cognitive Styles,” J. Educ. Technol. Soc., vol. 16, no. 4, 2016. [3] M. Gil, P. Giner, and V. Pelechano, “Personalization for unobtrusive service interaction,” Pers. Ubiquitous Comput., vol. 16, no. 5, pp. 543–561, 2012. https://doi.org/10.1007/ s00779-011-0414-0 [4] Y. A. Rezaei, G. Heisenberg, and W. Heiden, “User Interface Design for Disabled People Under the Influence of Time, Efficiency and Costs,” in Communications in Computer and Information Science, 2014, vol. 435 PART I, pp. 197–202. https://doi.org/10.1007/978-3- 319-07854-0_35 [5] T. H. Wang, “Developing an assessment-centered e-Learning system for improving student learning effectiveness,” Comput. Educ., vol. 73, pp. 189–203, 2014. https://doi.org/ 10.1016/j.compedu.2013.12.002 [6] A. G. Hwang, H. Sung, C. Hung, and I. Huang, “A Learning Style Perspective to Investigate the Necessity of Developing Adaptive Learning Systems,” J. Technol. Soc., vol. 16, no. 2, 2016. [7] C. Chen, “Personalized Intelligent Mobile Learning System for Supporting Effective English Learning Published by : International Forum of Educational Technology & Society Personalized Intelligent Mobile Learni,” Int. Forum Educ. Technol. Soc., vol. 11, no. 3, 2017. [8] J. M. Carroll, Making use: scenario-based design of human-computer interactions, vol. 48. 2000. [9] K. Wu, Y. Tang, and C. Tsai, “Graphical interface design for children seeking information in a digital library,” Vis. Eng., vol. 2, no. 1, p. 5, 2014. [10] K. Moffatt, J. David, and R. M. Baecker, “Reading, Laughing and Connecting with Young Children,” Springer-Verlag London, pp. 173–193, 2013. [11] C. Walkington and M. Sherman, “Using adaptive learning technologies to personalize instruction: The impact of interest-based scenarios on performance in algebra,” J. Educ. Psychol., vol. v105, no. 4, pp. 932–945, 2013. [12] A. Gauch, Susan; Speretta, Mirco; Chandramouli,Aravind; Micarelli, “User Profiles for Personalized Information Access,” Adapt. Web, vol. 4321, pp. 54–89, 2007. https://doi.org/10.1007/978-3-540-72079-9_2 [13] S. Kanoje, S. Girase, and D. Mukhopadhyay, “User Profiling Trends, Techniques and Applications,” Int. J. Adv. Found. Res. Comput., vol. 1, no. 11, pp. 2348–4853, 2014. [14] G. Jawaheer, M. Szomszor, and P. Kostkova, “Comparison of implicit and explicit feedback from an online music recommendation service,” Proc. 1st Int. Work. Inf. Heterog. Fusion Recomm. Syst. - HetRec ’10, pp. 47–51, 2010. https://doi.org/10.1145/ 1869446.1869453 [15] D. Godoy and A. Amandi, “User profiling in personal information agents: A survey,” Knowl. Eng. Rev., vol. 20, no. 4, pp. 329–362, 2005. [16] Ahmed Altaboli, “Investigating the Effects of Font Styles on Perceived Visual Aesthtics of Website Interface Design,” LNCS 8004 - Human-Computer Interact. Hum. centered Des. approaches, methods, tools Environ., vol. 1, no. July, 2013. https://doi.org/10.1007/978-3-642-39232-0_59 [17] K. L. Mcclarty and M. N. Gaertner, “Measuring Mastery: Best Practices for Assessment in Competency-Based Education,” no. April, p. 16 p., 2015. [18] L. Wawryk-Epp, G. Harrison, and B. Prentice, Teaching Students with Reading Difficulties and Disabilities: A Guide to Educators. Saskatchewan Learning, 2004. [19] A. G. K. Hugh W. Catts, The Connections Between Language and Reading Disabilities. London: Lawrence Erlbaum Associates, 2005. [20] A. Druin, Mobile Technology for Children:Designing for Interaction and Learning. Amsterdam: Morgan Kaufman Publishers, 2009. [21] Y. S. Al-hashmi, “Slow Learners: How are they Identified and Supported?,” English, 2008. [22] B. Wawryk-Epp, Lynne; Harrison, Gina; Prentice, Teaching Students with Reading Difficulties and Disabilities: A Guide for Educator. 2004. [23] B. Saleena and S. K. Srivatsa, “Using concept similarity in cross ontology for adaptive eLearning systems,” J. King Saud Univ. - Comput. Inf. Sci., vol. 27, no. 1, pp. 1–12, 2015. https://doi.org/10.1016/j.jksuci.2014.03.007
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