درخت حوزه‌های تخصصی

Purpose: In 2007, a responsible management education program began working on a global scale at the United Nations. This program is a framework for changing curriculum, research and orientation, and experimenting with new educational methods. The program seeks to create social responsibility among graduates of the educational system. The conditions for regulating affairs through social commitment, which is one of the important pillars of your social system, can create a discipline in society and provide predictive power. Social commitment is a factor for the satisfaction of the mutual needs of the community as well as social solidarity. The purpose of this paper is to identify the components of responsible management education and to examine educational practices and provide responsive instructional solutions to improve the status quo. Methodology: In this paper, the Atrid-Sterling (2001) method used to analyzing the subject in deductive approach. Findings: The research environment included 46 papers from 2007 to 2017, a book, and a thesis addressing directly the subject of management education. Findings of this study based on the six principles of responsible management education (purpose, values, method, research, participation, dialogue). Discussion: These findings include 16 themes organizer. they named (student initiatives, promotion of curriculum, the use of value concepts in the training course, institutional solutions, evaluation, infrastructure, training procedures, internal support, research results, participation with industries, participation with industrial universities, participation with the private sector, participation with learners, participation with other organizations, Communication tools and selection methods) as well as 48 basic themes.

Investigating the processes underlying test performance is a major source of data for supporting the explanation inference in the validity argument (Chappelle, 2021). One way of modeling the cognitive processes underlying test performance is through the construction of a Q-matrix, which is essentially about summarizing the attributes explaining test takers’ response behavior. The current study documents the construction and validation of a Q-matrix for a high stakes test of reading within a generalized-deterministic inputs, noisy “and” gate (G-DINA) model framework. To this end, the attributes underlying the 20 items of the reading comprehension test were specified through retrospective verbal reports and domain experts’ Delphi techniques. In the ensuing stage, the Q-matrix thus developed along with item response data of 2625 test-takers were subjected to empirical analysis using the procedure suggested by de la Torre and Chiu (2016). Item-level results showed that, except for one item, the processes underlying the other items were captured by compensatory and additive models. This finding has significant implications for model selection for DCM practitioners.