Research Publications

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Author: search.filters.author.Manathunga, K

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Now showing 1 - 10 of 23
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    A BI Approach for Student Engagement and Retention along with Cognitive Load Analysis for Educator
    (979-833153098-3, 2025) Algewatta, M. N; Manathunga, K
    This research presents a systematic approach to monitoring student engagement, retention, and cognitive load within higher education by integrating Business Intelligence (BI) tools with cognitive load analysis. The proposed framework utilizes a diverse range of data sources -including attendance, academic performance, mental health indicators, demographic variables, and student feedback to generate real-time insights into student behavior patterns. The BI system identified critical trends, such as irregular attendance, declining academic performance, and the influence of demographic factors, enabling educators to identify at-risk students and intervene proactively. Additionally, cognitive load analysis was employed to evaluate the mental demands of course content, categorizing learning objectives in alignment with Bloom's Taxonomy. This allowed for the identification of content that could potentially overwhelm students, facilitating adjustments in instructional complexity. The integration of BI insights with cognitive load data provided a holistic approach that not only enhanced the monitoring of student engagement but also supported the tailoring of instructional content to optimize learning without inducing cognitive overload. The findings suggest that combining BI tools with cognitive load metrics offers a robust framework for both improving student retention and assisting educators in creating a balanced, engaging, and supportive learning environment. This study contributes a practical model for institutions seeking to leverage data-driven insights to promote student success and address the dynamic challenges of modern higher education.
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    "Talking Books" : A Sinhala Abstractive Text Summarization Approach for Sinhala Textbooks
    (IEEE, 2023-05-23) Rathnayake, B.R.M.S.R.B.; Manathunga, K; Kasthurirathna, D
    The ability for books to talk would be an exciting concept, and this research discussion paves the path for an identical approach. The research objectives discussed in this paper address several burning problems, solve them and adapt them to future technological enhancements from a Sri Lankan context. Burning problems include reducing printing costs for textbooks, addressing students’ health, promoting green technology, and identifying a suitable summarising approach to the native language, Sinhala resulting in students’ learning ease. Other symptoms for the betterment indicate paths taken to reduce the weight of school bags carried by students, reduce paper usage by the government on printing textbooks, and spread technological awareness to teenagers regarding e-Learning. Textbooks issued by the government will be digitized and centralized into a single system that the government officials themselves can administer. The paper discusses limited hindsight literature and proposes 2 new algorithms for abstractive and extractive summarization for Sinhala text. The 2 algorithms are compared against one another in terms of performance, efficiency, precision and accuracy. Experts in the education domain have verified the derived summary of both algorithms. The deliverable artefacts are the mobile application, a RESTful auto-summarization plugin service, and new data sets extracted to train the GPT-3 models.
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    Success Factors of Requirement Elicitation in the Field of Software Engineering
    (IEEE, 2022-12-09) Attanayaka, B; Nawinna, D; Manathunga, K; Abeygunawardhana, P. K. W
    Requirement elicitation (RE) is a cognitively challenging and time-consuming task in software development due to the numerous challenges associated with it including conflicting requirements, unspoken, or assumed requirements, difficulty meeting with relevant stakeholders, stakeholder resistance to change, and not enough time set aside for meetings with all stakeholders. The prime causes of software implementation failure have been identified as inadequacies in the treatment of requirements. Without collecting the quality requirement, cannot achieve the goal of a quality software product. Through identifying the success factors affecting requirement elicitation, the paths to the quality requirements can be identified. The success factors identify through this research are experience, business analyst skills, stakeholder relationship, organizational elicitation process. This study aims to identify the factors affecting requirement elicitation based on the data collected from business analysts and similar positions in the software industry through a survey, interviews, and analyzed data to provide the initial validation for the identified factors. Through the analysis, we identified the main factors affecting successful requirement elicitation with a perfect significance value of less than 0.05 for all factors.
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    Adaptivo: A Personalized Adaptive E-Learning System based on Learning Styles and Prior Knowledge
    (IEEE, 2022-12-09) Rishard, M.A.M; Jayasekara, S.L; Ekanayake, E.M.P.U; Wickramathilake, K.M.J.S; Reyal, S; Manathunga, K; Wickramarathne, J
    The rapid advancement of technology and the internet has resulted in an increase in the number of learners seeking e-learning. Though E-Learning is widely used most e-learning systems provide the same set of learning resources and learning paths to each student, regardless of their personal preferences. In recent years there has been increasing attention towards the characteristics of learners such as the learning styles and the knowledge level of the learner. This research paper proposes a personalized adaptive E-learning system called “Adaptivo” that provides a personalized learning experience to the learners based on their learning style and knowledge level. To make the learning process more efficient and engaging, Adaptivo takes into account the specific differences between learners in terms of time, online interactions and learning duration. It then builds a personalized learning path depending on each learner's learning style and knowledge level. The main aim of this study is to investigate the impact of the proposed adaptive learning approach on learners. The results show that the students appreciate the approach, are highly satisfied, and performed better when content is personalized according to their learning style and prior knowledge.
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    PublicationOpen Access
    Teacher-Led Debriefing in Computer-Supported Collaborative Learning Pyramid Scripts
    (International Society of the Learning Sciences (ISLS), 2022-06-06) Amarasinghe, I; Hernández-Leo, D; Manathunga, K; Pérez, J. C; Dimitriadis, Y
    Debriefing is an integral part of orchestration and provides a space for teachers to review the learning experience. Although this concept is not new, little is known about how debriefing is conducted in scripted computer-supported collaborative learning situations, and its effects on students’ learning gains. Moreover, there is a lack of studies providing evidence of how learning analytics can be effectively utilised to support teacher-led debriefing. The objective of this study is twofold: Firstly, it studies how debriefing impacts students’ learning gains in Pyramid pattern-based learning situations. Secondly, it explores the types of learning analytics indicators that can support debriefing. Results indicated that debriefing can contribute to improve students’ learning gains, however, it does not always lead to the optimal outcomes and the type of task can have a major influence. Mechanisms such as semantic similarity score, knowledge graph visualisations and flag features are scrutinized as options to support debriefing
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    Real-Time Exam Anomaly Detection in Moodle-based Exam Systems with an AI Agent
    (IEEE, 2022-10-04) Manathunga, K; Akalanka, P. D. A. U.
    Online education takes a high priority in the modern world because technology is evolving so rapidly that education needs to adapt to this changing and evolving technology. However, after the COVID-19 pandemic, e-learning is the only available solution to continue teaching during the lockdown periods. The evolution of these studies also needs to adapt to the situation. One of the significant issues with this online evaluation method is the anomalies during the evaluation process. This proposed implementation mainly focuses on anomaly detection of the Moodle environment exam systems. The proposed system produces a Moodle plugin to detect the time taken for each question in the Moodle environment examination system and detect the exam anomalies using the time variations. Then analyze and calculate the time that each candidate has taken for each question and the average time. The invigilator can see the candidates who took more than average time and less than average time and get the suspicious candidate list. The plugin also contains a separate algorithm that monitors the candidate while facing the exam. This face detection algorithm will notice the unusual behaviours of the candidate and upload the created report to the database, and the invigilator can access these reports on their loggings. To guide the candidate system, they also have an AI agent who will help to understand the exam process, give pre-defined answers for the questions, and provide contact details of the relevant authorities for exceptional cases. Also, the developed plugin detects the system information and background apps that run during the exam process and automatically creates relevant reports, and uploads them into the database. After the system implementation, the system was tested using a selected audience. The developed application is an innovative initiative to support the Moodle-based examination process.
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    COVID-Tracker: Surveillance of Potential Clusters Using a Wristband and Location-based Data
    (IEEE, 2022-07-18) Mandara, A.P. M; Randula, H.K. K; Priyadarshana, H. L.Y; Uyanahewa, J. J.; Manathunga, K; Reyal, S
    COVID-19 is a global pandemic that has threatened the survival of humans and other living beings. COVID-19 causes illnesses varying from the very mild cold to serious health complications resulting in death. Most Information Technology based solutions have been implemented to prevent the COVID-19 pandemic while raising awareness in the public. However, there is a limited number of reliable and real-time applications of self-awareness on COVID-19. Currently, the globe is dealing with the COVID-19 epidemic, particularly in pursuit of economic growth in each country. Therefore, an accurate, efficient automatic method to raise self-awareness by avoiding risky contacts is useful for human survival. This paper describes the automatic detection of temperature using a wearable device and an automatic alerting mechanism to inform the users of potentially risky contacts with higher temperatures nearby within a considerable time frame. COVID-Tracker produces results with high accuracy and efficiency, this is beneficial to improve self-awareness among users, to visualize potential covid clusters, and also to improve the mental health of self-isolated people. The developed application consists of four main components namely: temperature measuring band, mobile application, prediction model-based visualization dashboard and an AI bot. Based on the results reported here, developed methods can help people to achieve self-awareness of COVID-19 by avoiding risk factors early and accurately.
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    Remotify: The Emergency Remote Learning Solution using Learning Analytics
    (IEEE, 2022-07-18) Amarasinghe, S. N.; Thalakumbura, T. M. D. D; Wijewardena, M. D. N. K.; Perera, D. H.; Manathunga, K; Senaweera, O
    Current pandemic situation has manipulated people to adapt to a new normal forcefully and due to the same reason education system is also evolving but the actual question is how productive the new methodologies utilized are. E-learning is not a novel concept but is becoming a necessity and the proposed platform could be identified as a direct response to the current emergency. This can also be known as an "ERT" situation; a shift of instructional delivery to an alternate delivery method in response to a crisis situation. The main intention in these situations is not to recreate a robust educational system but to provide access to institutions in a manner that is easy to set up and is dependable during an emergency while outperforming both E-learning & traditional classroom methods. To provide a solution to overcome barriers faced in a pandemic situation in a virtual classroom, the implemented system is encapsulated with a dashboard centralizing facts gathered from audio & video analyzing components which are analyzed against student performance utilizing personalized assessing techniques to deliver learning analytics.
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    PublicationOpen Access
    Source Code based Approaches to Automate Marking in Programming Assignments
    (Science and Technology Publications, 2021) Kuruppu, T; Tharmaseelan, J; Silva, C; Samaratunge Arachchillage, U. S. S; Manathunga, K; Reyal, S; Kodagoda, N; Jayalath, T
    With the embarkment of this technological era, a significant demand over programming modules can be observed among university students in larger volume. When figures grow exponentially, manual assessments and evaluations would be a tedious and error-prone activity, thus marking automation has become fast growing necessity. To fulfil this objective, in this review paper, authors present literature on automated assessment of coding exercises, analyse the literature from four dimensions as Machine Learning approaches, Source Graph Generation, Domain Specific Languages, and Static Code Analysis. These approaches are reviewed on three main aspects: accuracy, efficiency, and user-experience. The paper finally describes a series of recommendations for standardizing the evaluation and benchmarking of marking automation tools for future researchers to obtain a strong empirical footing on the domain, thereby leading to further advancements in the field.
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    Impact of E-Learning System User Interface Design on User Satisfaction
    (IEEE, 2021-09-30) Senevirathne, G; Manathunga, K
    Interface design is a mandatory aspect influencing the success of an e-Learning system implementation. User interface (UI) design of e-learning is a point of interaction between user and computer software. Users prefer more attractive and simpler interface designs rather than dull or complex designs. This study aims to outline the impact of UI design on the satisfaction of learners. Specifically, this study will be evaluating different user interaction design strategies such as ease of navigation, ease of resource discoverability, ease of configuring integrated tools etc. in e-learning platforms such as learning management systems, and massive open online courses (MOOCs). Further, this research aims to find answers for the challenges and issues faced by students and teachers when using e-learning platforms. A comprehensive questionnaire was distributed among teachers and students. Collected data was analyzed to get an idea about main interface design problems that frustrate the learners and teachers and distract them from educational tasks. Using this statistical analysis results, a model is proposed indicating success factors and failure factors that may affect to e-learning system interface designing. Moreover, this research also results in a set of guidelines or suggestions that can be followed to improve UI designing in e-learning platforms. Finally, an initial prototype implementation capable of recommending suggestions intelligently for e-learning platform designers and users is proposed after modelling the user satisfaction factors.