Component Analysis

Jihad as one of the central words of the Qur'an, meaning praiseworthy and condemned war and enduring hardship in the field of semantics has a close semantic relationship with the words "Qatl (murder), Harb (war), Jadal (dispute), Qalz (severity), Nafar (go forth), Sabr (patience)" in the form of synonyms. This semantic model, which considers the conceptual range of the word "Jihad" to consist of smaller components called syntagmatic semantic components, by analyzing the semantic components, expresses similarities and differences of the word Jihad with its synonymous terms. And it also plays a crucial role in explaining synonymy. Based on this vital point, the author in the present article tries to use this semantic hypothesis to examine the semantic coordinates of "Jihad" with words that have a possible synonymy; represents the semantic similarities and differences of each of them and explains the role of these elements in determining the specific situation and differentiating the context (Siyaq) and linguistic context of the mentioned words. Therefore, each context requires a combination of specific syntagmatic components that is the unit of word differentiation in different contexts. Hence, it is not possible to replace the word "Jihad" with words that have a relative synonymy; because this leads to a deviation from the intended meaning in "Jihad" and the terms that have a synonymy with Jihad.

This study investigates the crucial components propelling the integration of green technology and blockchain technology within electronic education (e-learning). Employing a mixed-methods research design, the inquiry blends quantitative and qualitative methodologies for comprehensive analysis. The qualitative phase draws upon the expertise of 125 purposefully sampled academic experts, subject-area specialists, and e-learning professionals through semi-structured interviews. Content analysis dissects these qualitative data, while structural equation modeling and factor analysis illuminate the quantitative dimension. The findings unveil five key components orchestrating green technology development in e-learning with blockchain integration: causal conditions, central phenomena, strategies, background conditions, and intervening conditions. Further analysis within each component identifies critical sub-components, informed by expert insights. Collectively, the study's predictor variables, encompassing both green technology development components and blockchain technology utilization, demonstrate a significant predictive influence (0.36, p < 0.01) on the mediator variable, green technology development. Additionally, they exhibit a nuanced yet statistically significant predictive effect (0.16, p > 0.05) on the criterion variable, e-learning and educational software performance enhancement. These positive and direct associations suggest a robust model for integrating blockchain technology to propel green technology advancements within e-learning. The proposed five-component model sheds light on the interplay between key factors, emphasizing the substantial impact of its application in guiding effective integration strategies.