Browsing by Author "Manathunga, K"

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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.
Open Access
Authoring and enactment of mobile pyramid‐based collaborative learning activities
(Wiley Online Library, 2018-03) Manathunga, K; Hernández‐Leo, D
Collaborative learning flow patterns (CLFPs) formulate best practices for the orchestration of activity sequences and collaboration mechanisms that can elicit fruitful social interactions. Mobile technology features offer opportunities to support interaction mediation and content accessibility. However, existing mobile collaborative learning research has mostly focussed on simple activity orchestrations from the perspective of collaborative flow orchestration and flexibility requirements, predominantly in face-toface pre-university educational contexts. This paper proposes a particularisation of the Pyramid CLFP to support flexible face-to-face and distance mobile learning scenarios in which learners interact in increasingly larger groups along a sequence of activities (Pyramid levels). PyramidApp implements this Pyramid particularisation that provides both a web-based authoring tool and an enactment tool accessible through web or mobile devices. The authoring tool was evaluated in workshops where teachers appreciated its design and applicability to their educational contexts. PyramidApp flows were enacted in three higher education settings. Learners enjoyed the activities but usage and satisfaction varied depending on several design and contextual factors like the epistemic tasks given, the education level and application mode (face-to-face or distance).
Open Access
Collaborative learning orchestration using smart displays and personal devices
(Springer, Cham, 2015-09-15) Manathunga, K; Hernández-Leo, D; Caicedo, J; Ibarra, J. J; Martinez-Pabon, F; Ramirez-Gonzalez, G
Pervasive classroom environments with interconnected smart devices permit enacting diverse pedagogical models in education. This paper proposes an extensible architecture integrating smart display, smart phones and wearable devices to support flexible orchestration of dynamic collaborative learning activities in face-to-face educational scenarios. The paper motivates an architectural design and describes its main components based on existing systems like Signal Orchestration System (SOS) and a multi-screen cooperation middleware. An applicable scenario illustrates the usage of proposed architecture in which wearable devices are used to indicate orchestration mechanisms (group formation, change of activity), a shared display visualizes tasks with summary of the orchestration and activity progress for collective awareness and smart phones are used to interact with the shared display and complete the activities.
Open Access
Connecting pattern-based learning designs with analytics: The case of the PyramidApp
(2016) Manathunga, K; Michos, K; Hernández Leo, D
This paper presents preliminary work aiming to identify learning analytics that can be presented to teachers or learning designers to support (re)use or (re)design of learning scenarios based on the pyramid (a.k.a. snowball) pattern by using the PyramidApp. A pattern-based analytics approach considers teacher´s metacognition in three levels, the pedagogical intent, pedagogical method/structure of a CLFP pattern and the practicalities to implement a learning scenario. Learning analytics are proposed to inform these three dimensions. A case scenario where N = 38 secondary school students in a face to face classroom used the PyramidApp was analyzed from the log files of the App. The recommended analytics for teachers are visualized in such a way that are hypothesized to foster decision making for customization of specific design elements of the pyramid pattern.
Embargo
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.
Open Access
Flexible CSCL orchestration technology: mechanisms for elasticity and dynamism in pyramid script flows
(International Society of the Learning Sciences (ISLS), 2019) Manathunga, K; Hernández-Leo, D
Flow patterns (e.g., Pyramid or Snowball) formulate good practices to script collaborative learning scenarios, which have been experimented in small-scale settings widely. Applying flow patterns on large-scale contexts present challenges to educators in terms of orchestration load. Orchestration technology can support educators to manage collaborative activities; yet existing technology do not address flexibility challenges like accommodating growing numbers of students or tolerating dynamic conditions in learning settings. We define elasticity and dynamism as two key elements in the flexibility of a script. Elasticity is related to the capacity of an orchestration technology to incorporate varying participant counts. Dynamism is the capacity to maintain a pedagogically meaningful script progression in presence of different individual behaviors. In this paper we propose flow creation and flow control mechanisms to address elasticity and dynamism in orchestration technology for Pyramid flows. These mechanisms, implemented in the PyramidApp tool, have been evaluated across four scenarios varying from small to large settings. The results show that rules enabling pyramid creation on-demand and the use of timers are useful to achieve elasticity and dynamism in the pyramid formation and progression in an automatic manner.
Embargo
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.
Embargo
Improvements for agile manifesto and make agile applicable for undergraduate research projects
(IEEE, 2013-04-26) Manamendra, M. A. S. C; Manathunga, K; Perera, K. H. D; Kodagoda, N
The paper describes the use of Agile software development methodology for undergraduate research projects. The students are required to do a project which spans for two academic semesters. The main objective is to see the appropriateness of Scrum for the undergraduate projects which is a widely used agile method at present in the software industry. The paper discusses main agile principles in the student's viewpoint to check how those are affected to meet the learning outcomes of the module by means of meeting the deadlines and getting constructive feedback from supervisors. The circulated survey results are analyzed thoroughly and discussed to prove the arguments made during the research time and the recommendations are provided to improve appropriateness hence required changes for the agile principles. Finally it is positive feedback from the students about using Agile for undergraduate projects to achieve the targets given to them.
Open Access
A multiple constraints framework for collaborative learning flow orchestration
(Springer, Cham, 2016-10-26) Manathunga, K; Hernández-Leo, D
Collaborative Learning Flow Patterns (e.g., Jigsaw) offer sound pedagogical strategies to foster fruitful social interactions among learners. The pedagogy behind the patterns involves a set of intrinsic constraints that need to be considered when orchestrating the learning flow. These constraints relate to the organization of the flow (e.g., Jigsaw pattern - a global problem is divided into sub-problems and a constraint is that there need to be at least one expert group working on each sub-problem) and group formation policies (e.g., groups solving the global problem need to have at least one member coming from a different previous expert group). Besides, characteristics of specific learning situations such as learners’ profile and technological tools used provide additional parameters that can be considered as context-related extrinsic constraints relevant to the orchestration (e.g., heterogeneous groups depending on experience or interests). This paper proposes a constraint framework that considers different constraints for orchestration services enabling adaptive computation of orchestration aspects. Substantiation of the framework with a case study demonstrated the feasibility, usefulness and the expressiveness of the framework.
Open Access
PyramidApp: Scalable Method Enabling Collaboration in the Classroom
(Springer, Cham, 2016-09-13) Manathunga, K; Hernández-Leo, D
Computer Supported Collaborative Learning methods support fruitful social interactions using technological mediation and orchestration. However, studies indicate that most existing CSCL methods have not been applied to large classes, means that they may not scale well or that it’s unclear to what extent or with which technological mechanisms scalability could be feasible. This paper introduces and evaluates PyramidApp, implementing a scalable pedagogical method refining Pyramid (aka Snowball) collaborative learning flow pattern. Refinements include rating and discussing to reach upon global consensus. Three different face-to-face classroom situations were used to evaluate different tasks of pyramid interactions. Experiments led to conclude that pyramids can be meaningful with around 20 participants per pyramid of 3–4 levels, with several pyramids running in parallel depending on the classroom size. An underpinning algorithm enabling elastic creation of multiple pyramids, using control timers and triggering flow awareness facilitated scalability, dynamism and overall user satisfaction in the experience.
Embargo
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.
Embargo
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.
Embargo
Revisit of Automated Marking Techniques for Programming Assignments
(IEEE, 2021-04-21) Tharmaseelan, J; Manathunga, K; Reyal, S; Kasthurirathna, D; Thurairasa, T
Due to the popularity of the Computer science field many students study programming. With large numbers of student enrollments in undergraduate courses, assessing programming submissions is becoming an increasingly tedious task that requires high cognitive load, and considerable amount of time and effort. Programming assignments usually contain algorithmic implementations written in specific programming languages to assess students' logical thinking and problem-solving skills. Evaluators use either a test case-driven or source code analysis approach when evaluating programming assignments. Given that many marking rubrics and evaluation criteria provide partial marks for programs that are not syntactically correct, evaluators are required to analyze the source code during evaluations. This extra step adds additional burden on evaluators that consumes more time and effort. Hence, this research work attempts to study existing automatic source code analysis mechanisms, specifically, use of deep learning approaches in the domain of automatic assessments. Such knowledge may lead to creating novel automated marking models using past student data and apply deep learning techniques to implement automatic assessments of programming assignments irrespective of the computer language or the algorithm implemented.
Open Access
Say No to Free Riding: Student Perspective on Mechanisms to Reduce Social Loafing in Group Projects.
(Science and Technology Publications, 2021) Samarakoon, U; Imbulpitiya, A; Manathunga, K
Project based learning is a popular teaching method in Information Technology undergraduate programs where students gain necessary skills and knowledge via a hands-on capstone project. Key learning gains from such projects are problem-solving skills by applying theoretical knowledge while improving soft skills like collaboration and communication. Students can improve critical thinking, learn to face challenging situations, and build creative solutions for a desired problem as a group. Irrespective of all these benefits, social loafing or simply free riding can be recognized as the key challenge in these group-based projects. Some students in group projects put less effort on group work than when they work alone while surviving in the group and taking credits for someone else’s work. This scenario leads to demotivation of hard-working members and lot of group conflicts. Ultimately, social loafing affects the group performance while resulting with unsuccessful projects and dissatisfied students. Seeking mechanisms for reducing social loafing in group projects is becoming a vital and this research proposes set of mechanisms to reduce social loafing in IT group projects and presents the students’ perspective on usefulness of each mechanism.
Open Access
A Social Learning Space Grid for MOOCs: Exploring a FutureLearn Case
(Springer, Cham, 2017) Manathunga, K; Hernández Leo, D; Sharples, M
Collaborative and social engagement promote active learning through knowledge intensive interactions. Massive Open Online Courses (MOOCs) are dynamic and diversified learning spaces with varying factors like flexible time frames, student count, demographics requiring higher engagement and motivation to continue learning and for designers to implement novel pedagogies including collaborative learning activities. This paper looks into available and potential collaborative and social learning spaces within MOOCs and proposes a social learning space grid that can aid MOOC designers to implement such spaces, considering the related requirements. Furthermore, it describes a MOOC case study incorporating three collaborative and social learning spaces and discusses challenges faced. Interesting lessons learned from the case give an insight on which spaces to be implemented and the scenarios and factors to be considered.
Open 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.
Open 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
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.
Embargo
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.
Open Access
Sustaining continuous collaborative learning flows in MOOCs: orchestration agent approach
(Graz University of Technology. Institut für Informationssysteme und Computer Medien (IICM), 2018) Amarasinghe, I; Hernández Leo, D; Manathunga, K; Jonsson, A
Collaborative learning spaces deployed in Massive Open Online Courses (MOOCs) provide productive social learning opportunities. However, sustaining collaboration in these spaces is challenging. This paper provides a classification of MOOCs participants based on their behavior in a structured collaborative learning space. This analysis leads to requirements for new technological interventions to orchestrate collaborative learning flows in MOOCs. The paper proposes the design of an intelligent agent to address these requirements and reports a study which shows that the intervention of the proposed orchestration agent in a MOOC facilitates to maintain continuous yet meaningful collaboration learning flows.
Embargo
"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.