Model Based on Learning Needs of Children with Auditory Impairment

This paper presents a model based on the needs of children with an auditory impairment, in which the dual research lines of Human Computer Interaction and Artificial Intelligence are employed in the design of intelligent interactive systems able to meet the requirements of the user. In following a philosophy of user-centered design, different characteristics of children with hearing disabilities are identified, along with AI techniques that could be applied in the model. The main issues involved in designing a user profile and the techniques used in order to create the process of adapting the system to the user are also discussed.

[1]  Gary B. Wills,et al.  Profiling the Educational Value of Computer Games , 2013, IxD&A.

[2]  Marc Marschark,et al.  Problem-solving by deaf and hearing students: twenty questions , 1999 .

[3]  Qiyang Chen,et al.  A neural network approach for user modeling , 1991, Conference Proceedings 1991 IEEE International Conference on Systems, Man, and Cybernetics.

[4]  Rosella Gennari,et al.  The Design of an Intelligent Adaptive Learning System for Poor Comprehenders , 2010, AAAI Fall Symposium: Cognitive and Metacognitive Educational Systems.

[5]  Reyes Juárez-Ramírez,et al.  Implementing adaptive interfaces: a user model for the development of usability in interactive systems , 2012, Comput. Syst. Sci. Eng..

[6]  Jianping Zhang,et al.  The Adaptive Learning System Based on Learning Style and Cognitive State , 2008, 2008 International Symposium on Knowledge Acquisition and Modeling.

[7]  Adel Mahfoudhi,et al.  Bayesian networks for user modeling: Predicting the user's preferences , 2013, 13th International Conference on Hybrid Intelligent Systems (HIS 2013).

[8]  Rabail Tahir.  Analyzing the intelligence in user interfaces , 2015, 2015 SAI Intelligent Systems Conference (IntelliSys).

[9]  Widodo Budiharto,et al.  The psychological aspects and implementation of adaptive games for mobile application , 2013, 2013 International Joint Conference on Awareness Science and Technology & Ubi-Media Computing (iCAST 2013 & UMEDIA 2013).

[10]  Neil D. Fleming,et al.  Not Another Inventory, Rather a Catalyst for Reflection , 1992 .

[11]  Eva Millán Valldeperas,et al.  Modelo Bayesiano del Alumno basado en el Estilo de Aprendizaje y las Preferencias , 2009, Rev. Iberoam. de Tecnol. del Aprendiz..

[12]  Gabriela Arias Enciso,et al.  Los estilos de aprendizaje , 2013 .

[13]  Christoph Froschl,et al.  User Modeling and User Profiling in Adaptive E-learning Systems , 2005 .

[14]  Peter Brusilovsky.  Methods and Techniques of Adaptive Hypermedia , 1996 .

[15]  Demetrio Arturo Ovalle Carranza,et al.  Modelo del estudiante para Sistemas Adaptativos de Educación Virtual , 2008, Rev. Avances en Sistemas Informática.

[16]  Krzysztof Z. Gajos,et al.  Predictability and accuracy in adaptive user interfaces , 2008, CHI.

[17]  Hongjing Wu,et al.  AHAM: a Dexter-based reference model for adaptive hypermedia , 1999, Hypertext.

[18]  César A. Collazos,et al.  Model for Analysis of Serious Games for Literacy in Deaf Children from a User Experience Approach , 2015, Interacción.

[19]  Richard M. Felder,et al.  MATTERS OF STYLE , 2004 .