Browsing by Author "Pathirana, S"

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MOOCs Recommender Based on User Preference, Learning Styles and Forum Activity
(IEEE, 2019-12-05) Hilmy, S; De Silva, T; Pathirana, S; Kodagoda, N; Suriyawansa, K
With the development of MOOCs (Massive Open Online Courses) as a major source of e-learning materials, the number of MOOCs available today has become dauntingly high. Furthermore, MOOCs are produced in many different video production styles and these styles play an important role in helping the consumer stay engaged and interested in the course throughout. However, due to the sheer number of MOOCs available today, it is becoming increasing difficult to find the MOOCs that suits your personal preferences and the learning style. This paper describes how thousands of MOOCs that belong to different styles are identified efficiently while each consumer's preferences are identified to provide personalized MOOC recommendations. Furthermore, the paper describes how forums can be analyzed to identify how consumers feel about MOOCs that they followed, which is a crucial metric in recommending MOOCs to consumers.
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Sustainability Insights: Unveiling the Impact of Business Analytics in Shaping Sustainability Practices in the Apparel Industry
(2025) Gajanayake, L; Rajapaksha, D; Rukshan, T; Pathirana, S; Thelijjagoda, S; Pathirana, G
The Sri Lankan apparels industry has a strategic importance for the national economy as the country has been one of the main exports and employers. But it has sustainability issues such as high resource consumption, increased pollution, and poor labor standards. As the consumption of sustainable and environmentally responsible clothes continues to rise around the world, such concepts as business analytics (BA) present an opportunity to tackle these issues. This study investigates the effects of BA tools and techniques in enhancing sustainability in Sri Lanka apparel industry with regards to waste reduction, efficient resource management and compliance to ethical standards for sustainable driven global business. A qualitative research design was followed and conventional interviews conducted on key informants from GOTS certified apparel factories. Data were coded and analyzed thematically using MAXQDA software, with reference to the subthemes that emerged in the study, such as waste reduction and increasing efficiency and effective decision-making. It was revealed that BA solutions such as RFID, predictive modelling and dynamic dashboards offered promising improvements to sustainability performance. Techniques like 3D sampling reduced fabric consumption during the generation of prototypes, and dashboard analytics allowed constant tracking of other forms of sustainability KPIs like power use and carbon footprint. They also increased efficiency of cross-functional coordination, integrating sustainability into functions and departments. This study demonstrates how BA enables the sustenance of development within the apparel industry, based on a strategic management of economical, ecological, and social goals. The outcomes would help industry leaders and policymakers in developing improved strategies for sustainability practice to overcome existing gaps between theory and practice and for sustainable and competitive business growth in the context of a world economy moving toward sustainability.