Human Resource Management
Permanent URI for this collectionhttp://repository.kln.ac.lk/handle/123456789/217
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Item An investigation of visually impaired learners marginalized in an online classroom environment(IEEE, 2021) De Silva, G. H. B. A.; Sandanayaka, T. C.; Firdhous, M. F. M.Despite their abilities or skills, all students had to attend online classes in universities last two years. Visually Impaired Learners (VIL) had unexplored problems associated with existing learning technologies, pedagogy, students per se, and facilitators in online classrooms. The objective of this study is to identify these problems and causes and to propose a theoretical model as a solution. The study identified 10 main problems causing dissatisfaction with VIL in online classrooms: the accessible devices and connectivity problems, the teaching-learning platform problems, lack of adequate training for teaching staff, pedagogical approach problems, lack of individual attention, inadequate time (extra) for learning and assessment, limitations of individual (reserved) space, limitations of assessment methods and platform, unavailability of the peer support, and unavailability of bilingual communication. The proposed theoretical model suggests consolidating learning technology with pedagogy, students, facilitators, and an extended learning environment to enhance the online class experience for VIL.Item Exploring Unorthodox Predictors of Smartphone Addiction during the COVID-19 Outbreak(IEEE, 2021) De Silva, G. H. B. A.; Sandanayaka, T. C.; Firdhous, M. F. M.Smartphones became an integral part of household & corporate management across all industries which resulted in high screen time, & smartphone addiction during the pandemic. This study attempts to examine the association between sociodemographic factors, & perceived smartphone addiction towards real smartphone addiction. Kwon's (2013) validated Smartphone Addiction Survey was used to collect data from the identified subjects (n = 192), and descriptive analyzes and statistical crosstabs were used to infer the associations. The results portray that Sex and Age are strong predictors of smartphone addiction: females over males tend to get addicted to smartphones, while age below 25 is highly addicted to smartphones, and age over 41 is less smartphone addict. The level of education is a moderately fair predictor of smartphone addiction. The higher the level of education, the higher the tendency to become addicted to smartphones. Marital status is not a good predictor of smartphone addiction in context, and there is no difference between being married or not of smartphone addiction. Perceived smartphone addiction is a good predictor of smartphone addiction, who believe they are addicted are more likely to become addicted to smartphones, and vice versa.