Performance and planning model for HEIS: A developmental engine for intellectual capital

BACKGROUND: HEIs implement different techniques for the problem of assessing the progress towards the notified goals or the achievements, which is the only way to ensure that the HEIs are functioning properly along the right way or not. OBJECTIVE: The aim of this paper is to propose a model for assessing the performance, which may be of interest to institutions, partners, society and students. METHODS: In this paper, the technique of performance-related goals of HEIs, and a statistical approach are proposed. The methodology of this paper will manage briefly the issues of the applicability of the technique, how to derive the “goals” for HEI’s, taking into consideration the indicators of the Intellectual Capital (Human, Organizational, and Relational), and how to collect the data from HEIs successfully. The processes of assuring the technique of performance-related goals, deriving and implementing the goals, and the acquisition and testing of data are developed. RESULTS: The findings of this paper are in two directions, i.e. in the proposing of a performance model for HEIs which is based on the goals of HEIs; and in the application side, i.e. in the practical results of the evaluation of HEIs and how to clarify the performance of institutions and how to compare between them. The findings show that the practical results are significant, and reliable. CONCLUSIONS: This paper develops a significance model for performance appraisal of HEIs, how we can compare between the performance of HEIs, and to rank their performance. The practical results of the model are both accurate and significant.

An Intelligent Mission Planning Model for the Air Strike Operations against Islands Based on Neural Network and Simulation

Mission planning of air strike operations is hard because it has to give instructions to a large number of units during a relatively long period of time in an uncertain environment. If some instruction parameters can be calculated by an intelligent agent, better strategies can be found more quickly. In a specific combat scenario of air strike operations against islands, an intelligent model is proposed to improve the performance and flexibility of mission planning. The proposed intelligent mission planning model is based on rule-based decision and uses a fully connected recurrent neural network to calculate some of the decision parameters. The proposed intelligent mission planning model shows better results as compared to rule-based decision making with randomized parameters, and it performs as good as experts in the test set of the specific combat scenario.

Computational Thinking and Social Studies Teacher Education

Computational thinking is highly applicable to social studies education, particularly decision-focused social studies. To better fit the disciplinary needs of social studies and align with social studies standards, we adapt and group computational thinking skills into a heuristic of data, patterns, rules, and questions (DPR-Q). We then propose a four-step model for social studies teachers to follow when planning lessons that integrate computational thinking within their curricular instruction. Both the DPR-Q heuristic and the instructional planning model are explained with worked examples from social studies classrooms. Successful integration of computational thinking into decision-focused social studies can both enrich the social studies curriculum and provide a curricular home for teaching computational thinking, bearing out Wing's claim that computational thinking is ‘everywhere' and ‘for everyone.'