Browsing by Author "Najhan Muhamad Ibrahim"

E-learning enables an environment in which educational activities are delivered through online platforms using computing devices to empower learning facilities anywhere and anytime without geographical boundaries. During the COVID-19 crisis where social distancing was mandatory, many e-learning platforms were adopted by institutions around the globe. Experiences show that for the adaptation of E-learning, several challenges were faced by educational institutions, among them some of the core challenges are Cost, System Quality, System Complexity, Infrastructure, Social influence, COVID-19 effect, and Student learning motivation. Therefore, this research aims to find the factors affecting the adoption of E-Learning during COVID-19 in Pakistan. To achieve this, a proposed hypothetical model has been formed based on well-known IT/IS acceptance models such as extended TAM, UTAUT, M&D, TRA, and IDT. Keeping problems in mind, an extensive literature search has been completed. In this study, constructs like Perceived Cost, System Quality, Complexity, Social Influence, Facilitating Condition, COVID-19 (Lockdown and COVID fear); Student learning motivation; Perceived Ease of User (PEOU), and Perceived Usefulness (PU) are the most significant variables to impact Behavior Intention (BI) to use e-learning in Pakistan, are measured. The hypothesized correlations were investigated using Smart-PLS software and Structural Equation Modeling (SEM). The correlational paths between constructs are studied using a quantitative methodology (survey questionnaire). A cluster sampling methodology was employed to gather a comprehensive dataset of 461 responses from students who utilized e-learning throughout the COVID-19 epidemic. The research findings indicate a significant statistical relationship in 13 out of the 15 hypotheses tested, while the other 2 did not yield statistically significant results. The research findings suggest that a significant portion, specifically 61.1%, of the change in Behavioral Intention may be reported by factors such as PU, PEOU, SI, SQ, CS, and COVID-19. Likewise, PEOU factors explained 39% of the variance, and Perceived Usefulness explained 54.7% in descending order of importance. Furthermore, the Cost and COVID-19 factors involved in adopting e-learning during COVID-19 negatively correlate with behavioral intention. Thus, Cost and COVID-19 were considered obstacles to adopting e-learning in the COVID-19 pandemic. This study contributes to identifying the significant factors influencing the behavioral intentions of Pakistani students for e-learning adoption during the COVID-19 pandemic, it also proposes an integrated research model to investigate the adoption of e-learning. Moreover, it offers practical and theoretical implications of its findings for stakeholders, including policymakers, educators, researchers, and industry practitioners involved in developing and implementing e-learning initiatives in Pakistan.

Security requirements are fundamental to the grid design and architecture. The basic security components within the Grid environment provide the mechanisms for authentication, authorization, and confidentiality of communication between grid computers. Some of the security models generate simple security codes where they would be easy to be cracked and some have applied bio-metric generations. Biometric model will lead to future privacy issue where most nations have approved to use data protection act, where some action or misuse of this Bio-metric data will be construed as conducting a crime with or without intention. This research explores biobased recursive programming theory to serve the best security mechanism for future Grid Computing where currently the security issues of Computer Grid environment are still at its infancy stage, an area with very high potential to conduct research. The main motivation for this project is to explore whether bio-based recursive programming model will be able to generate a promising Authentication and Authorization code patterns. The Tower of Hanoi is the meta-magical model where it is able to be modified to adapt to generate bio-like genetic codes and such few research study of similar nature has successfully been conducted. In this research study we generated and evaluated unique codes or patterns which would be with particles of large and randomized codes that are non-repetitive and non-predictive strings of genetic codes. In this modified model by using combinations of recursive models with step-wise randomization, each generated pattern will deliver different authentication or authorization certificates. We are also able to compare which other recursive models that would generate the most effective code or pattern to be used as authentication or authorization certificates. Programming recursive code generator using multiple Towers of Hanoi was implemented on the Grid computing environment that itself had generated the unique code or the unique pattern to obtain the required authentication and authorization certificates.