Scopus Index Publications

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This collection consists of all Scopus-indexed publications produced by SLIIT researchers. Scopus is recognized worldwide as a leading and reputable academic indexing database.

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Subject: search.filters.subject.gamification

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    Gamifying Coding Education for Beginners: Empowering Learners with HTML, CSS and JavaScript
    (Institute of Electrical and Electronics Engineers Inc., 2025) Chandrasekara, S; Hewavitharana, D; Weerasinghe, M; Gayasri, B; Wijendra, D; De Silva, D
    Traditional coding education often fails to engage and motivate beginners due to its lack of interactivity and personalized learning experiences. This paper presents a gamified learning platform designed to teach Hypertext Markup Language (HTML), Cascading Style Sheets (CSS), and JavaScript (JS) to beginners. The platform incorporates interactive lessons, AI (Artificial Intelligence)-powered coding assistance, and advanced gamification mechanics to enhance learner motivation, engagement, and success. Furthermore, key features include performance-based recommendation engines, virtual coding environments with real-time feedback, and a collaborative platform for peer interactions. The integration of AI provides personalized feedback and adaptive learning paths, while gamified elements such as badges, points, and leaderboards foster competitive and enjoyable experiences. Preliminary findings demonstrate a 40% increase in student engagement metrics and a 35% improvement in coding competency compared to traditional methods. This research lays the groundwork for future expansion to additional programming languages and broader educational applications, with potential implications for transforming computer science education on a scale.
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    Smart Monitor for Tracking Child's Brain Development
    (researchgate.net, 2019-03) Anparasanesan, T; Mathangi, K; Seyon, S; Kobikanth, S; Gamage, A
    This paper provides a way to track the brain development of children and improving it via gamification. Machine Learning and Gamification are the key technologies used here. As the population rises, the demand for cost-effective methods to reduce the rate of cognitive decline becomes higher. A mobile application is developed to track and develop the brain development of children. In the mobile application, the child initially undergoes an evaluation phase to determine the current level of the cognitive skills of the child. Milestones particular to that age category are also tracked in this evaluation phase. The results of this evaluation phase are analyzed by the machine learning model and suitable brain games are suggested. K-means algorithm is used to develop the model which is an unsupervised learning algorithm. The dataset is prepared by storing the results of each game category in the evaluation phase. Data preprocessing is done to clean up the dataset. During this period, data undergoes a series of steps. The dataset is divided into 80% and 20%. 80% of the dataset is used as the training dataset and the remaining 20% as the test dataset. The accuracy of the model is checked several times against the test data. Model accuracy is improved through model training and finally, the model got an accuracy of 88.49%. For the child, proper training is given to improve his cognitive skills and thus the brain development using Gamification. Games are developed using the UNITY game engine. The system generates a report and notifies parents about their child's statistics periodically. This paper elaborates the procedure of model development, model training, model testing and development of suitable brain games in details. The results of the research work and future works are also discussed in the following sections.