The notion of integration in educational games, namely the way in which the learning content is inserted into a game for efficient learning and increased motivation, remains relatively undefined in the literature (Szilas & Acosta, 2011), and no operational guide to analyse existing educational games has been provided to date. The goal of this master thesis is to design a tool to objectively classify and quantify educational games based on the type and degree of integration between the game and its learning content. For this purpose, two questionnaires have been created, the first assessing the primary learning outcome (cognitive, motor, affective, communicative) targeted by the game being analyzed, and the other providing a guide to classify the game’s type of integration based on the framework. The framework’s implications for the notion of integration in educational games will be discussed, and propositions for future research on the topic will be provided.
This study shows how the non-parametic optimisation model of Data Envelopment Analysis can be applied to Corporate Social Responsibility in a company-wide analysis of the capacity of people, processes, and other resources to meet the expected social obligations to all stakeholders under the organisation’s promulgated corporate citizenship. Data used in the analysis are the scores of empirical results from an Australian bank study. The DEA model identified 11 decision making units, from a cohort of 231, that were leading exponents of the behavioural characteristics required to be rated as the most efficient in meeting the corporate social responsibility criteria set by the firm. These findings can be used to investigate why some units succeeded so well while others wallowed. The analysis can provide valuable information for developing an efficient organizational structure for the company for achieving good corporate governance.
This paper presents measures for the performances of 12 selected Asia Pacific countries in developing knowledge-based economies (KE). The performances of the selected countries are evaluated using Data Envelopment Analysis (DEA). The DEA scores indicate that four of the emerging countries (India, Indonesia, Thailand and mainland China) are relatively inefficient in K-E development compared to the other eight which are equally efficient. The main reason for their backwardness is due to the outflow of their human capital resource to the developed countries. This seriously undermines the level of their K-E development compared to their counterparts. The results also indicate that knowledge dissemination is generally not a serious problem, except for India. However, in terms of knowledge output, knowledge dissemination becomes the weakest point for all low-scoring countries except China. Both India and China however, encounter serious obstacles in knowledge innovation and external connection.
This paper presents measures for the performances of 12 selected Asia Pacific countries in developing knowledge-based economies (KE). The performances of the selected countries are evaluated using Data Envelopment Analysis (DEA). The DEA scores indicate that four of the emerging countries (India, Indonesia, Thailand and mainland China) are relatively inefficient in K-E development compared to the other eight which are equally efficient. The main reason for their backwardness is due to the outflow of their human capital resource to the developed countries. This seriously undermines the level of their K-E development compared to their counterparts. The results also indicate that knowledge dissemination is generally not a serious problem, except for India. However, in terms of knowledge output, knowledge dissemination becomes the weakest point for all low-scoring countries except China. Both India and China however, encounter serious obstacles in knowledge innovation and external connection.
This paper presents measures for the performances of 12 selected Asia Pacific countries in developing knowledge-based economies (KE). The performances of the selected countries are evaluated using Data Envelopment Analysis (DEA). The DEA scores indicate that four of the emerging countries (India, Indonesia, Thailand and mainland China) are relatively inefficient in K-E development compared to the other eight which are equally efficient. The main reason for their backwardness is due to the outflow of their human capital resource to the developed countries. This seriously undermines the level of their K-E development compared to their counterparts. The results also indicate that knowledge dissemination is generally not a serious problem, except for India. However, in terms of knowledge output, knowledge dissemination becomes the weakest point for all low-scoring countries except China. Both India and China however, encounter serious obstacles in knowledge innovation and external connection.