AN INVESTIGATION OF SAUDI TEACHERS’ PERCEPTIONS TOWARDS TRAINING IN COOPERATIVE LEARNING

Cooperative Learning (CL) approaches have been widely researched in a number of educational contexts and a various studies indicate the effectiveness of using them to improve learners’ social and academic performance when working in small cooperative groups. However, there is still relatively little research on teacher training on CL and teachers perceptions of such training programmes. Investigations on challenges teachers face when start using CL in class or on factors that help overcome such challenges are also relatively few. This paper presents some of the results of a case study conducted in an all-male high school in Saudi Arabia. This article discusses participant-teachers’ perceptions towards the training in cooperative learning they received as well as their perceptions of the initial challenges the implementation of CL posed when working in a country where education still relies heavily on lecture style transmission and memorisation. Qualitative data was collected from eight participant-teachers by using semistructured individual interviews. The data was then submitted to thematic analysis using inductive and deductive analytical approaches. The findings suggest that preservice and in-service training, also referred to as Continuing Professional Development (CPD), in cooperative learning are important to help teachers change their perceptions towards training as well as their views on classroom roles,responsibility and authority. However, data also shows that are considerable initial challenges that teachers face during the period in which a change from lecture style to CL is taking place. Besides the training programme, it is important to consider the factors that can help to overcome these challenges and difficulties.&nbsp

Cyber-attack detection in network traffic using machine learning

Rapid shifting by government sectors and companies to provide their services and products over the internet, has immensely increased internet usage by individuals. Through extranets to network services or corporate networks used for personal purposes, computer hackers can lead to financial losses and manpower/time consumption. Therefore, it is vital to take all necessary measures to minimize losses by detecting attacks preemptively. Due to learning algorithms in cyberspace security challenges, deep learning-based cyber defense has lately become a hot topic. Penetration testing, malware categorization and identification, spam filtering, and spoofing detection are just a few of the key concerns in cyber defense that were tackled using Machine Learning (ML) approaches (Somme, 2020). Result, effective adaptive approaches, such as machine learning approaches could result in increased response times, reduced probability of false alerts, as well as cheaper computing and communication expenses. Our primary point is to demonstrate that the problem of detecting malware is distinct from other technologies, making it far more difficult for the access control group to properly use machine learning

His scent of sandalwood.

This creative thesis is a collection of fictional stories, connected by a common geographical and cultural thread: Kuwait. The stories unravel across a span of four thousand years. The poetic-prose style of the opening vignette is a nod to the earliest form of writing that makes up the bulk of Kuwait’s literature: poetry. The abstractedness of the two opening pieces reflects the lack of a deep-rooted national identity, and a brevity in Kuwait’s historical record. The remainder of the thesis explores the evolution of this national identity, as well as the infiltration of Western culture into modern Kuwait, and its effect on the lifestyles of its youth. The stories also study familial relations and taboo in Kuwaiti society, both past and present. Each piece stands as an individual tale, but there is also an interconnectedness between them that functions as a metaphor for the lives of Kuwaitis. JPG images have been used in “Almighty” to enhance the story

The Impact of Culture in Performance Evaluation Procedure in the UAE Public Sector

There is currently little research or literature on performance evaluation in the Arabic and United Arab Emirates (UAE) cultural context. The rapid changes and development of the UAE economy has lead to a growing interest in performance management in the public sector in the UAE. This current research explores performance evaluation in the UAE public sector, its practices, processes and the linkage between performance evaluation, and the impact of the UAE national culture on those processes. This work examines and compares private and public sector practices of performance evaluation. This comparison enables a broader assessment of approaches to performance evaluation, and therefore, the understanding of the impact of national culture on such processes. The research aimed to understand the social context of phenomena through participants’ thoughts, opinions and beliefs. The research combined a mixed research method of qualitative and quantitative approaches. For the mixed methods, pragmatism opens the door to multiple methods, different worldviews, and different assumptions, as well as to different forms of data collection and analysis. Data was collected through surveys to provide a larger amount of data from a wider population, therefore the questionnaire survey was sent to mid-level employees who have experienced performance evaluation from both private and public sectors. Interviews gathered more in depth insights on participants’ attitudes, thoughts and actions. The original contribution of the research was to provide a deep understanding of the performance evaluation process in UAE’s public sector. This study is one of a few to be carried out in the UAE, so it provides new findings for cultural influences on the performance evaluation procedure research and literature in the Arabic and Islamic contexts. Cultural values and practices affect the performance evaluation procedure, cultural values such as gender, Wasta, power distance, cultural diversity, and Arabic and Islamic values. The findings indicated that since the announcement of the UAE government strategy of 2008, some public organisations have developed and improved their performance evaluation practices considering factors, such as the employees’ involvement in the process. On the other hand, other public organisations conduct the evaluation as a routine job and do not evaluate the actual employee’s contribution. Furthermore, the evaluation does not affect the employees’ careers. The investigated private organisations have an evaluation system that is improved constantly and is linked to the employee’s careers and frequent and constructive feedback is obtained that enables the employees to make improvements to their performance on a regular basis. UAE culture is shaped and influenced by Arabic culture and Islamic values as well as national policy such as Emiritisation. UAE national culture has an impact the process of performance evaluation in the public and private sectors. For instance Wasta, part of the Arabic and UAE culture, influences the process. Wasta starts with recruiting candidates regardless of their qualification and is based on relationships; therefore, these employees are evaluated and treated differently, affecting both the organisation’s and employee’s performances. In addition, Wasta led to a UAE process for performance evaluation that built discrimination among employees. Addressing and managing the inappropriate elements of Wasta increases the effectiveness of the performance evaluation processes. The view of the role of women in society and the segregation between genders impacts the performance evaluation process; it affects communication in terms of providing feedback and guidance to enhance performance. However, there have been slight changes in the view of women’s roles in the UAE and the communication between genders is improving. As a result of these findings this study contributes a UAE culturally focused conceptual framework for performance evaluation

The question of the translatability of the Qurʼān, with particular reference to some English versions

No abstract available

Learning How to Search: Generating Exception-Triggering Tests Through Adaptive Fitness Function Selection

Search-based test generation is guided by feedback from one or more fitness functions—scoring functions that judge solution optimality. Choosing informative fitness functions is crucial to meeting the goals of a tester. Unfortunately, many goals—such as forcing the class-under-test to throw exceptions— do not have a known fitness function formulation. We propose that meeting such goals requires treating fitness function identification as a secondary optimization step. An adaptive algorithm that can vary the selection of fitness functions could adjust its selection throughout the generation process to maximize goal attainment, based on the current population of test suites. To test this hypothesis, we have implemented two reinforcement learning algorithms in the EvoSuite framework, and used these algorithms to dynamically set the fitness functions used during generation.We have evaluated our framework, EvoSuiteFIT, on a set of 386 real faults. EvoSuiteFIT discovers and retains more exception-triggering input and produces suites that detect a variety of faults missed by the other techniques. The ability to adjust fitness functions allows EvoSuiteFIT to make strategic choices that efficiently produce more effective test suites

Generating Diverse Test Suites for Gson Through Adaptive Fitness Function Selection

Many fitness functions - such as those targeting test suite diversity—do not yield sufficient feedback to drive test generation. We propose that diversity can instead be improved through\ua0adaptive fitness function selection\ua0(AFFS), an approach that varies the fitness functions used throughout the generation process in order to strategically increase diversity. We have evaluated our AFFS framework, EvoSuiteFIT, on a set of 18 real faults from Gson, a JSON (de)serialization library. Ultimately, we find that AFFS creates test suites that are more diverse than those created using static fitness functions. We also observe that increased diversity may lead to small improvements in the likelihood of fault detection