PREDOMINANT TRAIT OF PAKISTAN AND WESTERN POLITICS: A SERIES OF LANGUAGE POLITICS

This research deals with the power of language in politics, specifically in the dimension of Metaphors and the Rhetorical Philosophy of Aristotle's Ethos, which famous politicians significantly used. It determines the art of speech of three politicians, Former Prime Minister Imran Khan and former Presidents of the United States, Donald Trump and Barack Obama, who are consistently in the public eye for a great command of rhetorical language. Furthermore, the data combines and fusion of their pre-election and post-election speeches. The structure and layout of the research are first to emphasize and identify their art of speaking and delivery by comparing and contrasting these speakers and, secondly, analyzing their characteristics of how each one of them has chosen the tool of rhetorical and persuasive strategies in a unique style to make a striking impression upon the audience. These public speakers are specifically chosen for this research as they are renowned for their great competence and excellence in stump oratory, which built massive trust and created a socio-cognitive influence upon the audience’s mind. His research paradigm is based on a qualitative approach, and the design used in this study focuses on content analysis.

Design of Cognitive Driven Adaptive E-Learning Environment Using Individual Differences

The educational system of Pakistan surrounds with several problems. Among them, the most alarming issue is the poor learning outcomes of students. The predominant cause of such worst condition is weak traditional learning environment. To cater chronic educational issues the world around us strongly rely on technology because E-learning is being considered as widely recognized alternative to handle the shortcomings of traditional learning environment. Adaptive Educational Systems (AESs) are specialized class of e-learning which aimed to deliver individualized learning experience. The AESs integrate learner‟s individual characteristics with the help of user modeling techniques to impart instruction to each individual in accordance to his/her learning needs. Numerous AESs have already been developed in the pursuit of quality learning experience. These systems consider single aspect of learner such as learning styles. The success rate of such systems is reasonably low as their impact in terms of improving learning outcomes is still unclear. The researchers affirmed that considering a single aspect of learner is not enough to positively impact the learning process. It is therefore suggested to conduct further research considering other effective parameters along with learning styles. In this thesis, an adaptive learning system is being proposed considering combination of multiple sources of personalization including prior knowledge, Working Memory Capacity (WMC) and learning styles. An experiment has been conducted using sample size of (184) students to evaluate the impact of proposed approach in comparison to traditional learning environment. The student sample was equally divided into control and experimental groups. The control and experimental groups further consisted of subgroups formed on the basis of learners cognitive and non-cognitive characteristics identified using standard instruments. The experimental subgroups learned the subject contents with proposed adaptive learning system whereas control subgroups learned in traditional classroom environment. The results revealed that participants of experimental subgroups outperformed in terms of learning outcomes and learning efficiency than their counterparts of control subgroups.