Multicultural Teacher Preparation in Practice: A Hermeneutical Disposition

It is a fact that learning to teach is basically a social and practical activity that is supported and informed by theoretical reflections. Field experience and realities should be the core component of any teacher preparation program. That is why, most of the teacher education programs based on theory into practice model. The main aim of this research is not to reject this model, but to sketch out an alternative way of teacher preparation that is based upon teacher’s own context and socio cultural settings or in other words teacher preparation must be organized Hermeneutically. The hermeneutical approach of Hans-Georg Gadamer, is not only of philosophical importance but contains practical implications also. The concepts of understanding, interpretation and application are the core concepts of teacher preparation. In contrast to adopting an entire theory as the guiding principle to the whole content and practice of teacher preparation courses, this research argue for the focus to be on inculcating a hermeneutic disposition in all teachers preparation programs and courses. Hermeneutics is basic to human interaction, especially in dealing with student-teachers belongs to diverse socio-cultural settings or multicultural environment. The main argument or focus of this research is that it is necessary that the teacher preparation programs must be consider the problem of multiculturalism (inter and intra cultural). Multicultural Teacher Preparation (MTP) or hermeneutical mode of teacher preparation plays an important role in the preparation of teachers. It will be helpful for teachers to develop a deep level understanding of students needs belongs to various backgrounds and perspectives, not through applying a predetermined model of classroom activities, but through helping future teachers to recognize their own prejudices and how these help to determine their understandings of diversity in their future classrooms. Developing a hermeneutic disposition in teachers training facilitates and enrich experience of future teachers. A mixed method design was used to conduct the study

NEGATIVE AFFECTIVITY, CONSCIENTIOUSNESS AND JOB SCOPE (A CASE OF IT AND TELECOM INDUSTRY)

Based on a sample of 350 employees in the telecommunication and telecommunication, we obtained empirical evidence suggesting that while individuals high on conscientiousness tended to react more positively to job scope, individuals high on negative affinity tended to react less positively. Job scope was defined as the extent to which a job required the jobholder to be mentally and physically involved to get it done effectively. Typically, a job characterized by a high job scope would be non-repetitive, would need a great deal of independent thought/action and training, would entail the job holder to keep track of his/her progress, and others. The affirmative results obtained in regard of the moderating roles of personality factors in the present study suggested that job design researchers should further explore individuals’ personality differences in response to job scope

Evaluating the Nature of Distractive Driving Factors towards Road Traffic Accident

For past two decades many researchers have been working on quantitative as well as qualitative study of distractive driving using different approaches. Road traffic accidents have been identified as the main source of human casualties and cause of damages to the economy and society, as millions of humans is killed every year in these accidents around the world. National-level studies in Pakistan reveal that a higher percentage of males in the age group from twenty to forty years lose their lives in road traffic accidents when compared with that of females. Due to these factors, it is alarming for a society, which is highly dependent on males such as Pakistan, as these losses put numerous families into the financial crisis that lead to poverty. This study envisaged identifying whether moods and emotions play any role in road traffic accidents of young drivers. The study reviews have shown various gaps in our understanding. For this purpose, qualitative interviews of young drivers who are university going and have met some road accidents in recent years in Pakistan had been conducted. Data from the interviews had been transcribed for analysis while maintaining the anonymity of the participants for confidentiality. Analysis of the transcribed data reveals various factors that contribute to road traffic accidents where major causes are distractions, different weather conditions, sleep deprivation, unsafe lane changes, night-time driving, and these factors are triggered by the behavior when youthful drivers engage in driving for sensation seeking and self-esteem. We conclude that it is just through the appropriation of a systems approach that coordinated countermeasures can be proposed and actualized to relieve driver mistakes caused by distraction

The dynamics of leader technical competence, subordinate learning, and innovative work behaviors in high-tech, knowledge-based industry

This study tests a conceptual model for understanding the relationship between subordinates’ ‘learning work behaviour’ and ‘innovative work behaviour’, with the moderating role of their leaders’ self-reported as well as subordinates’ rated ‘leader technical competence’. The study was conducted in the context of a high-tech, knowledge-based telecommunications industry. Based on the evaluation of job description, leaders/managers with responsibilities of not only managing internal and external stakeholders but also capable to lead engineers to resolve any technical issue multiple-source data were collected from the identified leaders and their respective subordinates working with telecommunication operator (n¼179). This study proposed a three-way interaction moderation model between the independent variable (subordinate learning work behaviour) and the moderator variables (that is, the self-assessed leaders’ ‘technical competence’ and subordinates’ rated ‘leader’ technical competence’) to predict the subordinates’ ‘innovative work behaviour’. Our results demonstrate that that subordinate learning work behaviour had the strongest positive relationship with subordinate innovative work behaviour when both the leader self-assessment of technical competence and the subordinates rated leader’s technical competence were high. This study fills an important gap in leadership literature by focussing on the technical competence of leaders which has received little attention from leadership research in knowledge-based industries

A New Form of Interlocking Developing Technology for Level Crossings and Depots with International Applications

There are multiple large rail infrastructure projects planned or currently being undertaken within the United Kingdom. Many of these projects aim to reduce the continual issue of limited or overcapacity service. These projects involve an expansion of Rail lines, introducing faster lines, improved stations in towns and cities and better communication networks. Some major projects like Control Period 6 (CP6) are being managed by Network Rail; where projects are initiated throughout Great Britain. Many projects are managed outside Great Britain e.g., Trans-European Transport Network Program, which is planning for expansion of Rail lines (almost double) for High-Speed Rails (category I and II). These projects will increase the number of junctions and Level Crossings. A Level Crossing is where a Rail Line is crossed by a road or a walkway without the use of a tunnel or bridge. The misuse from the road users account for nearly 90% of the fatalities and near misses at Level Crossings. During 2016/2017, the Rail Network recorded 6 fatalities, about 400 near-misses and more than 77 incidents of shock and trauma. Accidents at Level Crossings represent 8% of the total accidents from the whole Rail Network. Office of Rail and Road (ORR) suggested that among these accidents at Level Crossings 90% of them are pedestrians. Such high numbers of accidents, fatalities and high risk have alarmed authorities. These authorities found it necessary to invest time and utilise given resources to improve the safety system at a Level Crossing using the safer and reliable interlocking system. The interlocking system is a feature of a control system that makes the state of two functions mutually independent. The primary function of Interlocking is to ensure that trains are safe from collision and derailment. Considering the risk associated with the Level Crossing system, the new proposed interlocking system should utilise the sensing system available at a Level Crossing to significantly reduce implementation cost and comply with the given standards and Risk Assessments. The new proposed interlocking system is designed to meet the “Safety Integrity Level- SIL” and possibly use the “2oo2” approach for its application at a Level Crossing, where the operational cycle is automated or train driver is alarmed for risk situations. Importantly, the new proposed system should detect and classify small objects and provide a reasonable solution to the current risk associated with Level Crossing, which was impossible with the traditional sensing systems. The present work discusses the sensors and algorithms used and has the potential to detect and classify objects within a Level Crossing area. The review of existing solutions e.g Inductive Loops and other major sensors allows the reader to understand why RADAR and Video Cameras are preferable choices of a sensing system for a Level Crossing. Video data provides sufficient information for the proposed algorithm to detect and classify objects at Level Crossings without the need of a manual “operator”. The RADAR sensing system can provide information using micro-Doppler signatures, which are generated from small regular movements of an obstacle. The two sensors will make the system a two-layer resilient system. The processed information from these two sensing systems is used as the “2oo2” logic system for Interlocking for automating the operational cycle or alarm the train drive using effective communication e.g., GSM-R. These two sensors provide sufficient information for the proposed algorithm, which will allow the system to automatically make an “intelligent decision” and proceed with a safe Level Crossing operational cycle. Many existing traditional algorithms depend on pixels values, which are compared with background pixels. This approach cannot detect complex textures, adapt to a dynamic background or avoid detection of unnecessary harmless objects. To avoid these problems, the proposed work utilises “Deep Learning” technology integrated with the proposed Vision and RADAR system. The Deep Learning technology can learn representations from labelled pixels; hence it does not depend on background pixels. The Deep 3 | P a g e Learning technology can classify, detect and localise objects at a Level Crossing area. It can classify and differentiate between a child and a small inanimate object, which was impossible with traditional algorithms. The system can detect an object regardless of its position, orientation and scale without any additional training because it learns representation from the data and does not rely on background pixels. The proposed system e.g., Deep Learning technology is integrated with the existing Vision System and RADAR installed at a Level Crossing, hence implementation cost is significantly reduced as well. The proposed work address two main aspects of training a model using Deep Learning technology; training from scratch and training using Transfer Learning techniques. Results are demonstrated for Image Classification, Object Detection and micro-Doppler signals from RADAR. An architecture of Convolutional Neural Network from scratch is trained consisting of Input Layer, Convolution, Pooling and Dropout Layer. The model achieves an accuracy of about 66.78%. Different notable models are trained using Transfer Learning techniques and their results are mentioned along with the MobileNet model, which achieves the highest accuracy of 91.9%. The difference between Image Classification and Object Detection is discussed and results for Object Detection are mentioned as well, where the Loss metrics are used to evaluate the performance of the Object Detector. MobileNet achieves the smallest loss metric of about 0.092. These results clearly show the effectiveness and preferability of these models for their applicability at Level Crossings. Another Convolutional Neural Network is trained using micro-Doppler signatures from the Radar system. The model trained using the micro-Doppler signature achieved an accuracy of 92%. The present work also addresses the Risk Assessment associated with the installation and maintenance of the system using Deep Learning technology. RAMS (Reliability, Availability, Maintainability and Safety) management system is used to address the General and Specific Risks associated with the sensing system integrated with the Deep Learning technology. Finally, the work is concluded with the preferred choice, its application, results and associated Risk Assessment. Deep Learning is an evolving field with new improvements being introduced constantly. Any new challenges and problems should be monitored regularly. Some future work is discussed as well. To further improve the model's accuracy, the dataset from the same distribution should be gathered with the cooperation of relevant Railway authorities. Also, the RADAR dataset could be generated rather than simulated to further include diversity and avoid any biases in the dataset during the training process. Also, the proposed system can be implemented and used in different applications within the Rail Industry e.g., passenger census and classification of passengers at the platform as discussed in the work

A journey from Cure to Care- Wellness management for healthy lifestyle: Diabetes management a case study

Smart ubiquitous computing has a vital role to avoid and indicate the preventable lifestyle-based chronic diseases. It is focusing to adopt a healthy lifestyle by converging science and technology in this digital world for improving health and quality of life. From the last decade, the development of wellness applications has supported personalization and self-quantification. These applications facilitate the users through activity tracking and monitoring, based on the raw sensory data to adopt healthy behavior. The challenge of behavior change is not only to indicate the issues but also provides step-by-step coaching and guidance at real time. The realization of behavior change theories through digital technology has revolutionized the lifestyle change in a systematic and measurable manner. We have proposed a methodology to understand the behavior for generating just-in-time intervention for adopting a healthy lifestyle. Wellness platform based behavior analysis is performed using unbiased life-log and questionnaire for qualitative assessment of behavior. Behavior stage wise intervention is provided to adapt behavior for enhancing the quality of life and boost the socio-economic conditions. Personalized education is provided to understand the importance of healthy behavior and motivate the users, whereas just-in-time context-based recommendations have supported the stage-wise adaptation of unhealthy behavior. These capabilities require status evaluation of the activities and an efficient way to portray the comprehensive index of lifestyle habits. The real focus is to correlate the primarily linked habits in appropriate proportion through healthy behavior index (HBI) for personalized wellness support services. The healthy behavior index and behavior change theories through smart technologies

How moral efficacy and moral attentiveness moderate the effect of abusive supervision on moral courage?

Moral courage is a competency exercised in the workplace as employees face ethical challenges with a moral response. Managers exert considerable effort to foster subordinates’ moral courage given its positive organisational consequences. However abusive supervision, not uncommon in the organisational context, negatively affects moral courage. The purpose of this article is to examine the relationship between abusive supervision and moral courage as well as to test the moderating roles of moral efficacy and moral attentiveness on that very relationship. Data were collected from six public hospitals in Pakistan. The sample included 359 nurses and 121 nurse heads. The moderating roles were tested using the moderated hierarchical regression analysis. Results revealed that there was a significant negative relationship between abusive supervision and moral courage. In addition, this very relation was weaker when both moral efficacy and moral attentiveness were higher than when they were lower. The study provided new insights into the influence that abusive supervision might have on nurses’ moral courage and it also offered a practical assistance to employees in the health care industry and their leaders that moral efficacy and moral attentiveness would act as neutralisers in mitigating the pernicious effect of abusive supervision on nurses’ moral courage

Functions of Code-switching in Bilingual Classrooms

The significance of role of code switching and code mixing in classrooms where medium of instruction is second/foreign language is approved reality. Observations of bilingual/multilingual classrooms show that teachers use code switching and code mixing in different situations for different purposes. This study aims at knowing the functions of CS (code switching) and CM (code mixing), use teachers in classrooms and the significance of the functions. The data for this study would be collected from teachers, teaching at intermediate level, of government and private colleges, using survey technique. The data would be analyzed statistically using SPSS software. The finding of this study would develop awareness about the use of CS and CM in bilingual classrooms. This study is significant as it would create flexibility in teaching methodologies of teachers. Keywords: Code, Code switching, code mixing, SL, F

Methods of condition monitoring and fault detection for electrical machines

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