https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4753 2026-03-29T07:51:33Z 2026-03-29T07:51:33Z Harischandra, B.A.I.V Devinda, K.K Abeyvickrama, A.W.A.V.H https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4807 2024-10-21T04:53:38Z 2024-09-01T00:00:00Z

Title: The Nebula Framework: A Deep Gamification Framework for High-Quality Online Learning Experience Authors: Harischandra, B.A.I.V; Devinda, K.K; Abeyvickrama, A.W.A.V.H Abstract: Abstract The trend towards online learning has become a pivotal part of modern education, but it comes with notable challenges, particularly in maintaining student motivation, engagement, retention, and performance over time. Traditional approaches, including attempts at integrating gamification, have been unable to fully unlock its potential to address these issues. In response to these challenges, this research introduces ”Nebula,” a deep gamification framework designed specifically to enhance the student experience on online learning platforms. Nebula shifts the focus from surface-level (shallow) gamification elements, like badges and leaderboards, to a more immersive and meaningful application of deep gamification principles. It aims to improve key educational outcomes such as engagement, consistency, retention, and performance. The project’s scope includes the development and iterative testing of the Nebula framework on a custom-built online learning platform, utilizing the design science research method. Each iteration incorporates feedback and insights, refining the framework to ensure its effectiveness in different learning contexts. The findings from our study indicate that the integration of Nebula into online learning platforms results in significant improvements in student engagement, consistent participation, retention rates, and overall performance. Furthermore, it highlights how deep gamification can lead to a more enriching and sustainable learning experience, thereby enhancing the overall quality of higher education. This research provides valuable implications for educators and platform developers, offering a new perspective on how online learning environments can be optimized through advanced gamification strategies. Keywords: Gamification, eSports, Personalization, Technology Enhanced Learning, The Nebula Framework.

2024-09-01T00:00:00Z Samaradivakara, Y.N Nimalsiri, K.T.U Pathirage, A.D https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4806 2024-10-21T04:50:27Z 2024-04-01T00:00:00Z

Title: SeEar: Enhancing Learning Experience for the Deaf and Hard-of-Hearing (DHH) Students with Real-time AR Captioning Interfaces Authors: Samaradivakara, Y.N; Nimalsiri, K.T.U; Pathirage, A.D Abstract: Abstract Deaf and hard-of-hearing (DHH) students encounter significant challenges within educational settings, primarily stemming from limited exposure to written and spoken language, a lack of tailored educational tools and methodologies, and restricted access to educational resources. We, therefore, adopted a User-Centered Design (UCD) process, collaborating with 8 DHH students and 2 Teachers of the Deaf (ToDs) from a School of Deaf from Sri Lanka to effectively co-design, develop and utilize a real-time captioning augmented reality (AR) system to their school settings, aiming to enhance their learning experience. We address four main research questions: how do we present and place real-time captions, how do we visualize wearer transcriptions and how do we visually represent inaccurate transcriptions from Automatic Speech Recognition (ASR) systems. User study with 24 DHH participants revealed a strong preference (87.5%) for our system, underscoring its potential to enhance learning experience. We share a comprehensive needs analysis, the UCD process, and insights from user feedback and evaluations, highlighting the effectiveness of tailored AR caption interfaces in improving education for DHH students. We discuss the implications of our findings for future development of educational technologies for DHH students. Our findings contribute to further exploration of the potential of tailored AR caption interfaces in addressing the educational challenges faced by DHH students and enhancing their learning experience in specialized educational settings.

2024-04-01T00:00:00Z Maithripala, S.A.A.D Menike, W.R.G Weerasinghe, W.M.H.P.B https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4805 2024-10-21T04:46:02Z 2024-04-01T00:00:00Z

Title: UTILIZING MULTI-SENSORY CUES TO ENHANCE ART GALLERY EXPERIENCE Authors: Maithripala, S.A.A.D; Menike, W.R.G; Weerasinghe, W.M.H.P.B Abstract: Abstract Assistive technologies play a major role in bridging the accessibility gap in the arts. Despite constant advancements, people with visual impairments (VI) still face challenges in independently experiencing and interpreting paintings. This study aimed to evaluate the effectiveness of conveying the contents of a painting to people with VI using selected multi-sensory stimuli (tactile, auditory, and somatosensory) to compensate for the loss of sight. A prototype, named SEMA (Specially Enhanced Multi-sensory Art), was designed around a simple painting, incorporating actuators for the aforementioned stimuli. SEMA was developed and refined iteratively with visually impaired students at the University of Colombo, Sri Lanka. We analyzed and evaluated all the sensations individually and as a whole system, utilizing several quantitative and qualitative measures. The final user study, conducted with 22 visually impaired participants, showed a strong preference (92.6%) for the prototype over traditional painting experiences, highlighting its potential to enhance how VI individuals experience art. The findings of this study contribute to further exploration of multi-sensory integration in entertainment and its impact on the visually impaired community.

2024-04-01T00:00:00Z Wickramasinghe, M.A.V.V Abeywardana, T.H.H Nandadewa, P.A.N.P https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4804 2024-10-21T04:42:59Z 2024-09-01T00:00:00Z

Title: Enhancing Automated Student Answer Marking: Authors: Wickramasinghe, M.A.V.V; Abeywardana, T.H.H; Nandadewa, P.A.N.P Abstract: Abstract In this research, we explored the potential of Large Language Models (LLM) to enhance the automated marking process in education by utilizing LLMs’ improved understanding of language and instructions following nature. We provided subject content as knowledge to increase accuracy in the marking of answers written for structured questions that are made up of theoretical subjects. Additionally, we examined the use of grading rubrics to maintain consistency and fairness in the marking process and, the use of prompt optimization techniques to enhance the accuracy by refining the prompts. Importantly, we examined the reliability and generalizability of prompts across various subjects and di↵erent questions, making the optimized prompt applicable to automated student answer marking of various theoretical subjects. Finally, detailed feedback generated utilizing the rubric grading scale that provide students with valuable insights to aid their learning journey. The results of the study highlighted the importance of providing external knowledge within the prompt to improve the performance of Large Language Models (LLMs) like Generative Pre-Trained Transformers (GPT) in the automated grading of students’ answers. The inclusion of grading rubrics, model answers, and course content significantly enhanced the accuracy of scores assigned by the LLM, reducing deviations from human evaluator scores. Particularly in theoretical subjects within the IT domain, where LLMs tend to apply vast knowledge beyond the scope of student expectations, providing course content or model answers helped define the expected answer scope and guide the LLM in determining other possible correct answers. This approach not only streamlines the marking process for academic sta↵ but also promotes transparency and reduces human errors in marking. Additionally, prompt engineering techniques were used to further engineer the basic prompt. A detailed feedback was also provided to students at the end of the marking process. However, combining multiple prompt engineering techniques with a basic prompt did not outperform the basic prompt, suggesting the need for further exploration and refinement in prompt design strategies.

2024-09-01T00:00:00Z