Video games in the classrooms: implications of a disruptive innovation to develop the Multiple Intelligences

The present study aims to identify the framework of personal, organizational and technical variables that contribute to the viability and successful of innovative educational practices with video games within the school context to enhance the multiple intelligences. For this purpose, advantage was taken on the information previously collected through a questionnaire about the views, thoughts and experiences of a group of teachers of childhood and primary education (N=25) who voluntarily participated in a blended training activity from Center of Teachers (CEFIRE) of Valencia, around a community of practice aimed at promoting and advising projects for implementing educational video games in the classroom. The mixed methodology adopted has allowed the following: a) describe the relationship between their degree of development and daily use made of ICT in the classroom, their level of familiarity with video games,  their previous experience to integrate them for educational purposes..., and their participation in projects that focus on game-based learning; b) conduct content analysis of the opinions and thoughts expressed in a forum for teachers on innovation on and methodological strategies adopted reflected in a virtual board; and c) develop a SWOT analysis: Strengths, Weaknesses, Opportunities and Threats inherent in the implementation of experience with video games in the classroom. Among the conclusions, it is highlighted that, even though most did not have specific training or enough technological resources and the planning and implementation of innovation required them a great investment of time, their personal interest, the support given by members of the online community of practice, helped to encourage their activity, along with receptivity, positive attitude and high motivation of students with the experience. These aspects have been crucial to promote successful innovative practices with video games.

Familiarity and Preference for Pitch Probability Profiles

We investigated familiarity and preference judgments of participants toward a novel musical system. We exposed participants to tone sequences generated from a novel pitch probability profile. Afterward, we either asked participants to identify more familiar or we asked participants to identify preferred tone sequences in a two-alternative forced-choice task. The task paired a tone sequence generated from the pitch probability profile they had been exposed to and a tone sequence generated from another pitch probability profile at three levels of distinctiveness. We found that participants identified tone sequences as more familiar if they were generated from the same pitch probability profile which they had been exposed to. However, participants did not prefer these tone sequences. We interpret this relationship between familiarity and preference to be consistent with an inverted U-shaped relationship between knowledge and affect. The fact that participants identified tone sequences as even more familiar if they were generated from the more distinctive (caricatured) version of the pitch probability profile which they had been exposed to suggests that the statistical learning of the pitch probability profile is involved in gaining of musical knowledge.

Approach to automatic video motion segmentation

A novel, fast automatic motion segmentation approach is presented. It differs from conventional pixel or edge based motion segmentation approaches in that the proposed method uses labelled regions (facets) to segment various video objects from the background. Facets are clustered into objects based on their motion and proximity details using Bayesian logic. Because the number of facets is usually much lower than the number of edges and points, using facets can greatly reduce the computational complexity of motion segmentation. The proposed method can tackle efficiently the complexity of video object motion tracking, and offers potential for real-time content-based video annotation.

Low-power systolic array processor architecture for FSBM video motion estimation

A novel power-efficient systolic array architecture is proposed for full search block matching (FSBM) motion estimation, where the partial distortion elimination algorithm is used to dynamically switch off the computation of eliminated partial candidate blocks. The RTL-level simulation shows that the proposed architecture can reduce the power consumption of the computation part of the algorithm to about 60% of that of the conventional 2D systolic arrays.

Reconfigurable video Motion Estimation processor

In this paper, a new reconfigurable multi-standard Motion Estimation (ME) architecture is proposed and a standard-cell based design study is presented. The architecture exhibits simpler control, high throughput and relative low hardware cost and is highly competitive when compared with existing designs for specific video standards. ©2007 IEEE.