Atefeh Sedaghati, Mohammad Taghi Pirbabaei, Farshad Nourian, Hamed Beyti,
Volume 32, Issue 4 (Special Issue: Green Housing, Guest Editor: Dr. Abbs. Yazdanfar 2022)
Abstract
The hedonic valuation method has been considered in various fields by researchers in order to estimate the value of a commodity or the demand for exploitation of a commodity for many years. Besides, the hedonic method has been widely used to identify ‘value’ indicators in the housing market. The need for indicators as the key tool for housing planning is related to the need to prioritize planning. Indicators are also critical to understanding housing characteristics. This article tries to develop a "conceptual model" of value by meta-analyzing the existing theoretical literature regarding the valuing indicators in the hedonic model, which has been done by the
meta-analysis method, uses MAXQDA software and open and axial coding to analyze the texts in order to compile and classify the features that explain the value of housing. The research findings, which are taken from 335 highly cited articles between 2009 and 2019, show that despite the long period of application and theoretical development of the model, there is no theoretical consensus on the explanatory indicators of housing value. So, 7 main categories can be identified in the form of 350 concepts and 5883 codes (including frequency), which can show the range of housing value dimensions, in addition to summarizing the issue. Also, the share of basic structural-physical and peripheral categories, with 53.5 and 25.5 percent, respectively, has the most application in the hedonic housing valuation model. In the two-mentioned categories, the share of variables affecting the residential unit, the building of the property, and access to services and land uses with relative shares of 23.6, 19.2, and 16.5%, is more than other variables. The results show that while the concepts of many explanatory indicators of value are the same, a suitable range of explanatory indicators of housing value can be used in the hedonic model according to the goals and the target community, and this can lead to the formation of indigenous and specific values of a society.
Abbas Sedaghati,
Volume 36, Issue 3 (7-2026)
Abstract
Academic motivation is a critical determinant of students’ engagement, learning effectiveness, and academic achievement. In architectural education, technically oriented courses such as Building Structures are often perceived as more challenging and less engaging than design studio courses, which may negatively affect students’ motivation and learning experiences. Consequently, identifying innovative instructional approaches that enhance students’ academic motivation has become an important objective in higher education. This study investigates the effectiveness of interactive computer simulation-based instruction in enhancing the academic motivation of undergraduate architecture students enrolled in a Building Structures course. A quasi-experimental pre-test–post-test design with a control group was employed. The study involved 50 undergraduate architecture students at Urmia Islamic Azad University, who were assigned to either an experimental group (n = 25) or a control group (n = 25). The experimental group received instruction through an interactive computer simulation environment, whereas the control group was taught using conventional lecture-based methods. Academic motivation was assessed using the Hermans Achievement Motivation Questionnaire (AMT). Data were analyzed using descriptive statistics and analysis of covariance (ANCOVA). The findings revealed a statistically significant increase in academic motivation among students who participated in simulation-based instruction compared with those who received traditional instruction. In addition, students in the experimental group achieved significantly higher scores on the final examination than their counterparts in the control group. These findings indicate that interactive computer simulation can serve as an effective pedagogical strategy for enhancing both academic motivation and learning outcomes in Building Structures education. The study contributes to the growing body of research on technology-enhanced learning in architectural education by providing empirical evidence from a technical course context that has received comparatively limited attention in previous studies.
