Browsing by Author "Sandanayake, TC"

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item: Article-Abstract
Affective E learning model for recognising learner emotions
Sandanayake, TC; Madurapperuma, AP; Dias, D
Online learning is commonly accepted as a support tool for educators as well as a medium of delivery of any-time, any-where content of a wide range of study programs to a widely dispersed learner community. Web-based learning environments are a relatively new medium of learning to Sri Lankan universities. Characteristics of learners of such environments vary widely, from technology geniuses to technological novices, from high bandwidth access to slow Internet connections etc. There are predictions of a near future boom of digital learning in Asian educational context, challenging the conventional face to face learning environments. Like any learning process, digital learning depends on effective communication of human knowledge, whether this occurs in a face-to-face classroom or across the Internet. The effectiveness of digital learning also depends on establishing two-way communication between facilitators and learners, and among learners themselves. Within the state university settings, learners experience varied emotions and interest towards learning. Although both emotions and interest can increase learners’ likelihood to engage in traditional learning, little is known about the influence of emotions and interest in learning activities in a digital environment. Previous research have identified that emotions occur while individuals assess events in their environment that are related to the needs, goals and well-being. Moreover, recent research on the emotional response to online learning has focused on the importance of learners’ feelings in relation to the community of learning. Major objective of this research study is to introduce a new model of online learning with relevance to the emotional response of the learning community. The study is based on Barry Kort’s Learning Spiral Model which is a four quadrant learning model in which emotions change while the learner moves through quadrants and up the spiral.
item: Conference-Abstract
Affective e-learning model for recognising learner emotions in online learning environment
(2014-06-26) Sandanayake, TC; Madurapperuma, AP
Today online learning provides wider coverage many different approaches such as distance learning, classroom-based electronic learning and self-access learning. Online learning has been recognized as a support tool for educators and researchers simply it gives is luxury of using at anytime, anywhere. Like any learning process, online learning depends on effective communication of human knowledge, whether this occurs in a face-to-face classroom or across the Internet. Emotions can have enormous affects on learning and play a vital role in decision making, managing learning activities, timing, and reflecting on the studies. Emotions are also important in teaching and learning and often find expression in particular ways, such as interactions with others and motivation in learning. The aim of the research is to develop a computational model for recognizing leaner emotions in online learning environment. The research study was focused on developing a tool to recognise the online learner's emotions. Therefore, the study has developed Online Achievement Emotion Questionnaire (AEQ) based on the AEQ which is suited for the online learning environment. Also the study has identified a methodology for recognising learner performances during learning. That has being measured through six parameters which represent the learner's level of learning during the learning experience. These parameters are analysed using multiple regression analysis and a model equation was developed to compute the online learner's level of learning. Finally the study has analysed and evaluated the correlation between the learner emotions and the observed behaviour. This research study therefore developed a novel model of affective online learning which can be use as a tool to recognise online learner's emotions with regard to the performance in learning
item:
Affective e-learning model for recognising learner emotions in online learning environment
(2015-07-10) Sandanayake, TC; Madurapperuma, AP
Today online learning provides wider coverage many different approaches such as distance learning, classroom-based electronic learning and self-access learning. Online learning has been recognized as a support tool for educators and researchers simply it gives is luxury of using at anytime, anywhere. Like any learning process, online learning depends on effective communication of human knowledge, whether this occurs in a face-to-face classroom or across the Internet. Emotions can have enormous affects on learning and play a vital role in decision making, managing learning activities, timing, and reflecting on the studies. Emotions are also important in teaching and learning and often find expression in particular ways, such as interactions with others and motivation in learning. The aim of the research is to develop a computational model for recognizing leaner emotions in online learning environment. The research study was focused on developing a tool to recognise the online learner's emotions. Therefore, the study has developed Online Achievement Emotion Questionnaire (AEQ) based on the AEQ which is suited for the online learning environment. Also the study has identified a methodology for recognising learner performances during learning. That has being measured through six parameters which represent the learner's level of learning during the learning experience. These parameters are analysed using multiple regression analysis and a model equation was developed to compute the online learner's level of learning. Finally the study has analysed and evaluated the correlation between the learner emotions and the observed behaviour. This research study therefore developed a novel model of affective online learning which can be use as a tool to recognise online learner's emotions with regard to the performance in learning.
item: Conference-Full-text
Agent Based Employee Performance Management and Decision Support System
Ekanayake, DC; Gunasekara, RGAD; Weerasinghe, KHWMMM; Deemanthi, SHS; Sandanayake, TC; Fernando, S
Performance appraisal is a process used by companies, in order to evaluate the employees efficiency and productivity. This process can be carried out in different ways, by employees supervisors or by different collectives related to the evaluated employee. When 360-degree performance appraisal approach is used to evaluate employees, different appraisers have different degree of knowledge about the employee. Such knowledge is usually vague, subjective and very limited. To overcome these limitations, this paper presents an agent based employee performance management and decision support system which enables an employee to represent himself in a virtual environment through an autonomous agent. This representation provides an opportunity for a person to justify the marks he/she has allocated for a given attribute to a virtual panel consists of his/her peers and managers. Furthermore, agents in this virtual environment are capable of acquiring the knowledge from other agents and update the beliefs according to feedbacks they receive and recalculate the evaluation marks.
item: Conference-Abstract
Automobile product ranking based on the singlish comments in social media platforms
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa., 2022-12) Warnakulasooriya, A; Sandanayake, TC; Wickramasinghe, GAMPS; Ranasinghe, RADW; Sumathipala, KASN; Sumathippala, KASN; Ganegoda, GU; Piyathilake, ITS; Manawadu, IN
In today's world, many customers buy or choose products based on online reviews. The internet contains a vast collection of natural language. People share their subjective thoughts and experiences with one another in various social media platforms. Product reviews can be analyzed to determine how people feel about a particular product .In Sri Lanka, people widely use Singlish (Sinhala-English) to comment and give reviews on products, rather than a single pure language .Therefore in this research it has extracted data from social media platforms on various brands in the automobile industry and propose a system to rank the automobile brands in Sri Lanka based on the social media comments which are written on Singlish. When ranking products, it is not practical to rank products based only on the frequency of the products. Because a brand having the highest number of comments does not necessarily indicate that it has good market perception compared to other brands. In order to get an accurate overview, the study have considered both the people's sentiment towards the particular brand and the frequency of comments. When ranking the products research has done several rankings based on different aspects namely market value, country of origin and second hand market, vehicle performance, product features which people pay their most attention in the automobile industry and also an overall ranking considering all these aspects together. With that it is possible to identify which vehicle type or brand has the highest and lowest demand in the market, and the automobile manufacturer can get a good understanding where a particular product stands out comparative to other brands and apply their strategies accordingly. When implementing the ranking system 100000 social media comments were extracted and annotated. Convolutionary neural network was used to develop the main model, and out of the different methods tried to predict the sentiment as the part of the main model, random forest method gave a higher accuracy of 96.7 making it a more sophisticated combination.
item: Conference-Full-text
Computational model for affective e-Learning : developing a model for recognising E-Learner's emotions
(2015-07-15) Sandanayake, TC; Madurapperuma, AP
e-Learning is the use of information and communication technology to enable people to learn anytime and anywhere. E-learning is a support tool for educators as well as a medium of delivery of any-time, any-where delivery of content to a dispersed learner community. Emotions are also important in teaching and learning and often find expression in particular ways, such as interactions with others and motivation in learning. Although both emotions and interest can increase learners' likelihood to engage in traditional learning, little is known about the influence of emotions and interest in learning activities in a digital environment. The aim of the research is to develop a computational model for recognizing learner emotions in online learning. Therefore, the study has developed Online Achievement Emotion Questionnaire (AEQ) tool which is suited for the online learning environment. Also the study has identified six parameters which represent the learner's level of learning during the learning experience. Finally the study has analysed and evaluated the correlation between the learner emotions and the observed behaviour. This research study therefore developed a novel model of affective online learning which can be use as a tool to recognise online learner's emotions with regard to the performance in learning.
item: Thesis-Abstract
A Computational model for recognising students emotions in E-learning systems
(2014-08-06) Sandanayake, TC; Madurapperuma, AP
Online learning is a support tool for educators as well as a medium of delivery of any-time, any-where delivery of a content to a dispersed learner community. Web-based learning environments are a relatively new medium of learning to Sri Lankan universities. Like any learning process, online learning depends on effective communication of human knowledge, whether this occurs in a face-to-face classroom or across the Internet. The effectiveness of online learning also depends on establishing two-way communication between facilitators and learners, and among learners themselves. Although both emotions and interest can increase learners’ likelihood to engage in traditional learning, little is known about the influence of emotions and interest in learning activities in a digital environment. Emotions play an essential role in decision making, managing, perceiving and learning and influence the rational thinking process of humans. Emotions are also important in teaching and learning and often find expression in particular ways, such as interactions with others and motivation in learning. The influence of emotions on e-learning is still not emphasized. Continuous and increasing exploration of the complex set of parameters surrounding online learning reveals the importance of the emotional states of learners and especially the relationship between learning and affective behaviour. Previous research have identified that emotions occur while individuals assess events in their environment that are related to the needs, goals and well-being. Moreover, recent research on the emotional response to online learning has focused on the importance of learners’ feelings in relation to the community of learning. The aim of the research is to develop a model to recognize leaner emotions in online learning environment. Through a critical literature review on affective computing, the study has identified several models and selected Barry Kort’s Learning Spiral Model as the prototype model of the research study. The learning spiral model is a four quadrant learning model in which emotions change while the learner moves through quadrants and up the spiral. This study will be presenting a model which describes the relationship between the online learners learning performances and emotions that occur during online learning process. The research study has built a high-level architecture which consists of three sub modules representing the current context on online learning and two sub modules representing the novel approach of affective learning. Experiments were conducted based on the sub modules developed. The research was focused on identifying a suitable tool to recognise the online learner’s emotions. During the comprehensive literature survey, different tools enabling recognising learner emotions were identified and the study has selected Achievement of Emotions Questionnaire (AEQ) by Pekrun et al. to be applied in recognising learner emotions. Therefore, the study has developed Online AEQ based on the AEQ which is suited for the online learning environment. The study has identified six parameters which represent the learner’s level of learning during the learning experience. These parameters are analysed using multiple regression analysis and a model equation was developed to compute the online learner’s level of learning. Finally the study has analysed and evaluated the correlation between the learner emotions and the observed behaviour. This research study therefore developed a novel model of affective online learning which can be use as a tool to recognise online learner’s emotions with regard to the performance in learning.
item: Article-Abstract
Decision support system for diagnosing asthma disease
Shahany, MNA; Sivalingam, M; Sandanayake, TC
Field of medicine is more about decision making. The role of a physician is more pivotal in the diagnosis of a disease from all other possible illnesses. This is called as “Differential Diagnosis” in the field of medicine where the key aspect is the analysis of symptoms. But, due to both physicians’ factors and patient’s factors there occurs considerable amount of diagnostic errors which lead to dangerous consequences. So, there’s a rising concern in reducing these errors in medical diagnosis worldwide. When it comes to respiratory diseases differential diagnosis is more challenging due to the commonness of symptoms of various diseases and also the connection of cardiac diseases. Proper diagnosis needs both theoretical knowledge and the knowledge comes from experience. If we can blend both types into one place it will definitely support to come to more appealing conclusions when diagnosing diseases. Due to the nature of vagueness in expressions in the medical field, a technology which can cope with this gray area is more suitable. Fuzzy logic is a type of logic that identifies more than simple true and false values and can be represented with degrees of truthfulness and falsehood. Fuzzy logic is being integrated in many experts systems to solve many real world problems. Through our project we have developed a decision support system for diagnosing Asthma (a respiratory disease) and its stages in adults using fuzzy logic. The system is built based on 21 inputs which were considered by the expert as the most important symptoms and laboratory tests in diagnosing Asthma and its severity stages. The system proves its ability of addressing the problems stated above thus can be relied upon and further improved for coverage of more diseases.
item: Conference-Full-text
Detecting and capturing the intensity of a brain tumor using mri images
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lanka, 2019-12) Gayanga, TDL; Pathirana, GPSN; Sandanayake, TC; Sudantha, BH
Mutated cells in the brain are known as tumors. There are two types of tumors present in the brain, and they are malignant and benign tumors. Benign tumors are non-cancerous tumors which reside inside a person's brain having a primitive shape and size. Malignant tumors are cancerous brain tumors which spread by transforming the cells into the cell type next to the malignant tumor and have no clearly defined edge or shape(cloudy). Treatment planning and detection is the most efficient way of treating a patient and improving the condition. Magnetic Resonance Imaging (MRI) is the established method to detect the tumors. After the detection classification of the tumor manually takes reasonable time and sometimes it is impossible to detect the type with the naked eye. This results in having to conduct a biopsy which is a risk as well as sometimes impossible. One of the main factors to be considered in segmenting the tumor is the edge intensity of the tumor. For detecting the intensity of the tumor edge a novel completely automatic and reliable detection based on CNN is proposed. Pre-processing and running the improved images through CNN to get the best possible features to be extracted from the MRI images. Canny edge detection and Wavelet transform are applied to detect the edge and finally, Hough transform is used to detect the intensity of the edge. Edge detection method that proposed in this paper will have a wide verity of surgical applications.
item: Conference-Full-text
Development of digital storytelling platform for children based on emotions
(Faculty of Information Technology, University of Moratuwa., 2021-12) Vijayakumaran, T; Thavachelvam, T; Gnaeswaran, A; Sandanayake, TC; Sumathipala, K; Bandara, S; Ganegoda, GU; Mahadewa, KT
Storytelling is one of the means to make Gen Alpha children attractive to books. This is becoming a challenging task for parents, as they have to spend time telling stories to children. This research proposed a system that can emotionally tell stories as a human storyteller tells stories with twists and suspense. This research involves the implementation of technologies related to Natural Language Processing and Deep Learning, especially the inclusion of Convolutional Neural Networks, Transformers. Camera images of the storybook are the input for optical character recognition (OCR) of the Storybook. Here, various complex algorithms are used throughout the processes of optical character recognition (OCR), sentence-level contextual emotion recognition(CER), and emotional text to speech(TTS) synthesis to implement the Emotional digital storyteller. In addition, immense testing is carried out to explore the effectiveness and characteristics of the implemented model. We achieve 75% and 72.09% accuracy in OCR and CER respectively and MOS values of 3.85 and 1.65 in neutral and emotional TTS respectively. The experiment results show that each model performs well in the children's domain, specifically storytelling books.
item: Article-Abstract
An Effective system to acoustically convey sign language
Sandanayake, TC; Lenagala, GJY; Liyanaarachchi, WLADVA; Atukorala, ADKR; Weerarathna, RS
Having 5% of the world’s population suffering from speaking disability, building up an effective communication between them and the ordinary community is essential. The people of the community of deaf use sign language as their communication method. In other words sign language is employed by the hearing-impaired to communicate with each other. There arc different sign languages used by different cultures and the communities across the globe. It is very important to have a mechanism for this special group to communicate and blend with the ordinary people specially in working day to day. These special groups of people are contributing much in the development of the economy and other social activities. Therefore, there is a need for a mechanism to bridge the communication gap between this special group and the ordinary community. This research study aims to develop an effective mechanism to acoustically convey sign language to the ordinary community using current technological advancements. The research study has identified the communication issues prevailing betw een the two parties and has developed an effective methodology to convey sign language used by Sri Lankan deaf community. The system has been designed in such a way that the sign or body gesture of the people with speaking disabilities arc captured and converted into voice in English which can be easily understood by ordinary people. This research work also can be extended to many sign languages used by different deaf communities around the world which will contribute to the enhancement of communication in the business
item: Conference-Full-text
Evaluation of employee engagement towards work performance in a hybrid working model in the Sri Lankan construction industry
(Business Research Unit (BRU), 2023-12-04) Devinda, WASSS; Sandanayake, TC; Mufitha, MB
There are various alternative hybrid working models in practice for middle-layer employees in the construction industry due to post-pandemic work arrangements. This calls for an evaluation of the suitability of alternative working models since hybrid working models encompass a wide range of activities. However, a paucity of literature is observed when it comes to recommending the most effective model to achieve higher work performance and employee engagement. Additionally, there is a scarcity of literature when investigating the factors influencing effective employee engagement towards work performance when hybrid working models are employed. The current study evaluates the moderating effect of gender on the main relationship between employee engagement and work performance. The population is defined as the middle-layer employees of the construction industry in Sri Lanka. Due to the prevailing economic challenges in the Sri Lankan construction industry, a convenient sampling technique was used. The study employed a survey methodology and collected responses from 142 self-administered questionnaires. The one-way ANOVA test results show that out of the four alternative hybrid working models—'at will model,' 'split week model,' 'shift work model,' and 'week by week model'—the shift work model is the best-fit hybrid working model for middle-layer construction employees. From the linear regression analysis, it was found that employee engagement has a positive relationship with work performance. Concerning the challenges faced by middle-layer construction employees, the results reveal that female employees face the challenges more than their male counterparts. However, the results of the interaction effect in the regression analysis show that gender has no effect on the relationship between employee engagement and work performance. The findings of the study help top-level managers in the construction industry make decisions related to enhancing work performance. They can also choose the most appropriate hybrid working model for their projects based on specific considerations and the expected employee engagement in such scenarios.
item: Conference-Full-text
Game-based analytical skills testing for graduate software engineering recruitment
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa., 2023-12-07) Dasanayake, DWMNC; Sandanayake, TC; Premasiri, SMU; Piyatilake, ITS; Thalagala, PD; Ganegoda, GU; Thanuja, ALARR; Dharmarathna, P
Game-based recruitment is an emerging trend adopted by organizations globally, given its proven results in boosting candidate perceptions of the company and providing an improved recruitment experience. This paper explores the use of game-based analytical skill testing in the recruitment process of entry-level graduate software engineers in Sri Lanka. The Test of Logical Thinking by Tobin and Capie has been used as a reference, and a game-based version has been developed using the MDA framework, relying on mechanics, dynamics, and aesthetics. The testing phase has been carried out using a focus group of eight fresh graduate software engineering recruits, and the results have depicted a significantly high level of accuracy between the results produced through the paper-based and gamebased versions. Candidate perceptions of the recruitment process and the employer have been recorded to be positively influenced by the introduction of game-based testing in the recruitment process
item: Conference-Full-text
Identification of brain tumor and extracting its’ features through processing of mri
(Faculty of Information Technology, University of Moratuwa., 2020-12) Lakmi, KWDT; Pathirana, GPSN; Sandanayake, TC; Karunananda, AS; Talagala, PD
The abnormal growth of tissues inside the brain is known as brain tumors and they are considered as a life threatening disease. According to the cell types containing in a tumor they can be classified into two groups as Benign and malignant. Benign tumors are considered to be non-cancerous and they have a primitive shape and size. At the same time malignant tumors are considered to be cancerous and do not have clearly defined edges. Modern technology has introduced several types of imaging techniques for internal body evaluation and analysis. Among them Magnetic Resource Imaging techniques are used to analyze many diseases as they have high resolution and better quality compared to others. Using conventional methods to identify brain tumors using MRI and extracting their features are difficult as the brain is complex. Therefor image processing techniques can be used to detect brain tumors and extract features automatically and effectively. This study presents a method to detect and extract features of the brain tumors which consist of five steps: preprocessing, skull stripping, detecting tumors in axial, coronal and sagittal planes, identifying tumor location and extracting features. The outcomes of the research study will help the doctors or the medical technicians to identify the brain tumor and its features in an effective manner.
item: Conference-Abstract
Impact of innovation and r & d on financial performance of telecommunication sector in Sri Lanka
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa., 2022-12) Prabath, JA; Sandanayake, TC; Sumathipala, KASN; Ganegoda, GU; Piyathilake, ITS; Manawadu, IN
The intention of this research is to investigate and analyze how innovation affects organizational performance in the Sri Lankan telecommunication sector. Three variables were used to measure the innovation construct: product innovation, process innovation, and disruptive innovation. The moderating variable organizational culture is used to measure the moderating effect between the independent and dependent variables (organization performance). The findings of this study will enable enhancing the performance of the telecommunication sector. By examining the impact of innovation and R&D on the telecommunication sector in Sri Lanka, as well as organizational performance, this analysis will address the research gap in the field of telecommunication sector in Sri Lanka. There are six hypotheses available in research methodology that was tested. Three main telecommunication sector firms out of five telecommunication sector firms in Sri Lanka was selected to collect data. The selected three companies are Sri Lankan Telecom, Mobitel and Dialog Axiata PLC. The result of the analysis shows that organizational innovation has a positive relationship towards organizational performance. The moderating variable “organizational culture” does not show any moderating effect between independent and dependent variables. The telecommunication firms that are more into organizational innovation have scored high in organizational performance criteria. Organizational culture does not highlight a moderating impact on the independent and dependent variables.
item: Article-Abstract
Navigator application for blind navigation
Samarasinghe, WKSM; Wanigasinghe, CH; Sandanayake, TC; obstacle detector
A person, who has partially or completely lost their capacity to see, has to face some big challenges during his life. Blind navigation is one of the major challenges for their day to day life activities. The sighted population can use vision to get safely across streets, through a grocery store, to and from school. Blind travelers are very effective using canes and using native sensory abilities, like auditory and kinesthetic skills for their navigations. Throughout the human life span, blindness, and particularly the inability to freely navigate, disrupts independence. This leads to decreased competence, economic dependence, depression, even failure of cognitive abilities to develop. Nowadays many people use hand held device with Android operating system. This research solution is an android navigator application to help blind people navigation. It will use GPS (Global Positioning System) and Google Maps technologies to identify locations around the user. User can specify the destination by address, and then our app will help him to reach his destination. Walking directions that are spoken by Google Maps help him to navigate in the physical world. User can listen to the audio instructions given by the application during the navigation and move to the destination and the application informs about any obstacle on the path of the user. Application is using the camera of the device and external sensors for obstacle detection.
item: Conference-Full-text
Open innovation practices in Sri Lankan tech-startups: a pilot study
(Faculty of Information Technology, University of Moratuwa., 2021-12) Samarasinghe, NP; Sandanayake, TC; Samarasinghe, GD; Ganegoda, GU; Mahadewa, KT
Tech-startups are vital entities in a business context, which are contributing to the economic and social development of a country. Tech-startups are identified as a booming industry segment in Sri Lanka that involves innovative solution development. Innovativeness is an unavoidable concept in today's business world because innovativeness has become a competitive advantage in each industry. In terms of innovations, there are open and closed innovations. Open innovation is the most attentive topic in the innovation field and in the global context also this field is still emerging. The open innovation perspective in the Sri Lankan context is having much more avenues to explore within many industries. This pilot study is completely focused on identifying the open innovation practices in the Sri Lankan tech-startups; to get an understanding of the current situation of Sri Lankan tech-startups in open innovation perspective. The study was conducted to do a situational analysis of open innovation practices while interviewing the key personalities of Sri Lankan tech-startups including CEOs, founders and co-founders of the tech-startups. The interviews were conducted in distance mode and each interview has taken 20 to 25 minutes. As a pilot study, the findings were really interesting and the findings of the study will be used in future studies for the uplifting the open innovation practices in Sri Lankan tech-startup culture.
item: Conference-Full-text
Personal loan default prediction and impact analysis of debt-to-income ratio
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa., 2023-12-07) Rodrigo, KLS; Sandanayake, TC; Silva, ATP; Piyatilake, ITS; Thalagala, PD; Ganegoda, GU; Thanuja, ALARR; Dharmarathna, P
Loan defaults affect the financial sector, particularly impacting banks and lending institutions, resulting in a rise of non-performing assets and financial strain. To counteract this trend, traditional credit assessments use methods like credit scores and exploitation of socio-demographic composition of the customers. However, customers may possess numerous debt obligations that credit bureaus uncover, which can help to measure their repayment ability. This study proposed a comparative methodology that leverages five machine learning algorithms to predict personal loan defaults using debt-to-income ratio apart from the credit scoring models that prevail at banks. It analyzed the impact of debt payments on loan defaults and applied ensemble clustering to categorize customers’ risk levels based on their debt-to-income ratio. Experimental results indicated that ensemble clustering has enhanced the prediction power compared to conventional classification models to predict loan defaults.
item: Article-Abstract
Preliminary study on leaner perceptions and learner performance of OER integrated online courseware
Sandanayake, TC; Karunanayake, SP; Madurapperuma, AP
Technology-infused distance education is the fastest growing sector in modern education. Online learning has become an ubiquitous concept in modern education, while online learning systems provide a rich and flexible learning environment to facilitate the acquisition of knowledge. Open Educational Resources (ORE) which gives and new face for the open and online learning in modern education system. The learner perceptions on course development is one of most essential factor that every course designer must consider. This research study is aiming on conducting a preliminary investigation on learner perceptions of OER integrated online course ware. The study has been carried out in the Faculty of Information Technology of University of Moratuwa. Target group of learners were participated in the research study in the course module E-Education in the Level 4 Semester I. The outcome of this research study will be an input for the OER courseware development with the support of proper pedagogical features.
item: Article-Full-text
Promoting open educational resources-based blended learning
(Springer Netherlands, 2019) Sandanayake, TC
The OER movement has empowered researchers and educators to become more innovative in their teaching and learning, through the openness and flexibility. The use and adaptation of OER have been recommended as a very cost-effective investment in quality teaching-learning. In conventional teaching practices, teachers mostly spend time developing learning materials, reviewing lecture notes, anticipating questions and formulating answers, preparing for examinations. This method is no longer appropriate with the learner’s current association with the technology. This research aims on promoting OER-based blended learning for the undergraduate learners. Action research has been conducted in order to identify the learner adaptation to the new culture of OERbased blended learning. This research has evaluated the learner perceptions on OER-based blended learning. The learner performance records were also evaluated as a measure of quality of learning. The study has focused on how the OER materials to be incorporated in the online course development in undergraduate learning. At the same time, research provides feedback on the use of OER- based blended learning methods. The study further elaborates on effective assessment activities which need to be used in OER-based blended learning. Learners were quite positive on these effective assessment activities. Moreover, the study specifies the importance of incorporating OER in undergraduate online learning.