Faculty of Computing

Permanent URI for this communityhttps://rda.sliit.lk/handle/123456789/4202

Browse

Filters

2020 - 20222

Advanced Search

Filter by

Settings

Has files: YesSubject: search.filters.subject.Evaluating

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    PublicationEmbargo
    Evaluating the Success of Digital Learning in Sri Lankan Tertiary Education
    (IEEE, 2022-12-09) Weerapperuma, J; Nawinna, D; Gamage, N
    This paper takes a social capital perspective to explain the underlying mechanisms that drive the success of digital learning in tertiary education in an emerging economy. It is crucial to explore ways in which the success of tertiary education can be maximized since these students will immediately contribute to the economy. Although digital-learning initiatives have advanced in developed countries, it is still in its early phases in many developing countries, including Sri Lanka. This study focuses on structural, relational, and cognitive dimensions of social capital and provides a new theoretical framework to examine its relationship to digital educational success. The study uses a quantitative approach where the data is collected from University students in Sri Lanka using a survey deployed online. The model is validated using the structural equation modeling technique. The findings of this study indicated that the three dimensions of social capital positively influence the success of digital education at the tertiary level. Further, this paper contributes to the existing literature on Social Capital Theory and provides valuable insights and recommendations for policymakers in the educational sector on improving digital learning achievements.
  • Thumbnail Image
    PublicationEmbargo
    Evaluating Teaching Content and Assessments based on Learning Outcomes
    (IEEE, 2020-12-10) Pallegama, P. M. O. N; Kumari, K. A. M. R; Dissanayaka, D. M. D. P. M; Ravihansi, A. V. Y; Karunasenna, A; Samarakoon, U
    A modularized syllabus content assigned to different units of a subject proves very useful to both teachings as well as the student community. In each module, learning outcomes are defined. In each learning outcome, lesson learning outcomes are defined. When the Teaching Content (Lecture content), Learning activities (Labs sheets and Tutorials), Final Question Papers are being made the subject learning outcome should be considered and it should be made within the subject learning outcomes. Then the teaching and learning process will be done properly. Nowadays Revised Bloom's Taxonomy standard is used to structure the Teaching Content, Learning Activities, and Final Question paper of a course in the best way. Currently, there is no proper solution to corporate above areas according to the Revised Bloom's Taxonomy. This paper discusses an automated system that provides the features to verify the module and lesson learning outcomes and their levels according to Revised Bloom's taxonomy and to verify that the teaching content and learning activities are within the learning outcomes. Beyond that, this system uses various technologies and algorithms to improve the accuracy and efficiency of this research. This automated system is able to achieve to the final outcome with the best accuracy and efficiency than the manual process.