Building a Community of Shalom: What the Bible Says about Multicultural Education

Multicultural education is a highly controversial topic in which it has been the center of contentions and conflicts as it has evolved for the last couple of decades. Several concerns and problems existed in the field of multicultural education will be addressed in this article. In addition, a new framework of multicultural education, called the shalom model, which is drawn from the Bible is presented, along with the characteristics of the model. The goal of multicultural education, according to this model, is to build a community of shalom, an image that is clearly described in Isaiah 11:6. In order to accomplish this goal, the model suggests that all people need to be equipped with the truth that all people are the image bearers of God. This concept is expanded into four implementation interventions when relating to others: biblical perspective; cultural competence; contextualized pedagogy; and intentional praxis. Finally, regarding the application issue of this model, some points of the implementation strategies are addressed in this article

Exploiting the user interaction context for automatic task detection

Detecting the task a user is performing on her computer desktop is important for providing her with contextualized and personalized support. Some recent approaches propose to perform automatic user task detection by means of classifiers using captured user context data. In this paper we improve on that by using an ontology-based user interaction context model that can be automatically populated by (i) capturing simple user interaction events on the computer desktop and (ii) applying rule-based and information extraction mechanisms. We present evaluation results from a large user study we have carried out in a knowledge-intensive business environment, showing that our ontology-based approach provides new contextual features yielding good task detection performance. We also argue that good results can be achieved by training task classifiers `online' on user context data gathered in laboratory settings. Finally, we isolate a combination of contextual features that present a significantly better discriminative power than classical ones

Transforming a competency model to assessment items

The problem of comparing and matching different learners’ knowledge arises when assessment systems use a one-dimensional numerical value to represent “knowledge level”. Such assessment systems may measure inconsistently because they estimate this level differently and inadequately. The multi-dimensional competency model called COMpetence-Based learner knowledge for personalized Assessment (COMBA) is being developed to represent a learner’s knowledge in a multi-dimensional vector space. The heart of this model is to treat knowledge, not as possession, but as a contextualized space of capability either actual or potential. The paper discusses the automatic generation of an assessment from the COMBA competency model as a “guideon- the–side”

The Effects of Storytelling on EFL Young Learners' Reading Comprehension and Word Recall

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