Weighting and Prioritizing of Valuation Factors and Indicators for Applied Science in Primary School

Hierarchical analysis is one of the prioritization methods of phenomena. This method provides comparison and use of expert people. In this research, the men-tioned method was applied in order to weight and prioritize valuation factors and indicators for applied science in primary school. The methodology of this research is descriptive survey. The statistical population is all experts (education heads) of Hamadan Province Education Office in primary level which all of them responded to the questionnaires due to lack of sampling. Data analysis was done through hierarchical analysis using Excel software. Findings showed that on viewpoint of experts and with regards to importance level, significant factors in valuation of applied science course in primary school were generals, content, goals, logic of plan, role of teacher, learning activities, measurement, learning materials and resources, location, time and grouping. Regarding the valuation indicators in generals of curriculum, indicators of the program accordance to primary education principles, capability of the program in growing the basic scientific competencies, and realization rate of the program had more weight. Also, in program’s logic and goals, indicators of the program’s accordance to students’ needs, it’s accordance to primary education goals, and compatibility of curriculum with scientific principles, structures and bases had more weight. On content and learning activities, indicators of content accordance to learning needs, content accordance to general goals of the program, and focus of learning strategies on learner had more weight and importance. Considering the role of teacher and measurement, rate of program’s accordance to role of teacher, rate of consideration to role of teacher, and prediction of flexible role for teacher had most weight. About learning resources and grouping, indicators of foresee of laboratory equipments in program, prediction of required software and hardware, and prediction of group learning activities had highest weight. Finally, in factors of time and space, prediction of laboratory in program, explanation of program’s location to school, and time allocated to learning owned most weights.