An Ontological Model to Blend Didactic Instruction and Collaborative Learning

Author(s):  
Yusuke Hayashi ◽  
Seiji Isotani ◽  
Jacqueline Bourdeau ◽  
Riichiro Mizoguchi
2008 ◽  
Vol 11 (1) ◽  
pp. 9-11 ◽  
Author(s):  
Carolyn S. Potts ◽  
Sarah M. Ginsberg

Abstract In recent years, colleges and universities across the country have been called upon to increase the quality of education provided and to improve student retention rates. In response to this challenge, many faculty are exploring alternatives to the traditional “lecture-centered” approach of higher education in an attempt to increase student learning and satisfaction. Collaborative learning is one method of teaching, which has been demonstrated to improve student learning outcomes.


2005 ◽  
Author(s):  
Vanessa Kowollik ◽  
Eric A. Day ◽  
Jazmine Espejo ◽  
Lauren E. McEntire ◽  
Paul R. Boatman

2010 ◽  
Vol 37 (4) ◽  
pp. 23-25
Author(s):  
Colette Copeland

2015 ◽  
Vol 5 (1) ◽  
pp. 31-54
Author(s):  
Khaled Barkaoui ◽  
Margaret So ◽  
Wataru Suzuki

Author(s):  
Isabel Álvarez

El propósito de este artículo es fortalecer la colaboración entre dos instituciones que buscan integrar e-learning en sus prácticas más cotidianas y en contextos donde antes no habían tenido experiencia previa. El objetivo principal es acercar a los estudiantes universitarios, en este caso a los usuarios del Banco del Tiempo (BdT) del Ayuntamiento de Terrassa, Barcelona, a las prácticas reales para que obtengan un aprendizaje más significativo,. La experiencia relata el proceso de coordinación, diseño, gestión y valoración desde el punto de vista del aprendizaje en la formación inicial de los estudiantes de grado.


Author(s):  
Alessandro Umbrico ◽  
Gabriella Cortellessa ◽  
Andrea Orlandini ◽  
Amedeo Cesta

A key aspect of robotic assistants is their ability to contextualize their behavior according to different needs of assistive scenarios. This work presents an ontology-based knowledge representation and reasoning approach supporting the synthesis of personalized behavior of robotic assistants. It introduces an ontological model of health state and functioning of persons based on the International Classification of Functioning, Disability and Health. Moreover, it borrows the concepts of affordance and function from the literature of robotics and manufacturing and adapts them to robotic (physical and cognitive) assistance domain. Knowledge reasoning mechanisms are developed on top of the resulting ontological model to reason about stimulation capabilities of a robot and health state of a person in order to identify action opportunities and achieve personalized assistance. Experimental tests assess the performance of the proposed approach and its capability of dealing with different profiles and stimuli.


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