With the advancement of information technology, we have got an opportunity to change the learning experience of students. E-learning systems such as Learning Management Systems (LMS), Course Management Systems and Students Management Systems have been emerged as a result of this, aiding a vast variety of education institutes around the globe. Yet, the quality assurance processes are still dependent on conventional student feedback mechanisms that have their inherent drawbacks. This has become a major barrier for quality improvement of the learning experience of students. We have introduced a solution for this through a crowdsourcing based perception capturing and analysis platform that can be adapted in many scenarios seamlessly. The design and implementation of backend analysis algorithms have been discussed along with the results gained from this project.
Keywords: Education | Sentiment Analysis | Crowdsourcing |
@inproceedings{ponnamperuma2014novel,
title={{Novel Approach for Perception Analysis In a Learning Environment}},
author={Ponnamperuma, Sachintha Rajith and Gunawardana, Andun S. L. and Shanika, Thilini and Pathirana, Prabahth Suminda and Markus, Shahani and de Silva, N. H. Nisansa Dilushan},
booktitle={Teaching, Assessment and Learning (TALE), 2014 International Conference on},
pages={148--154},
month={12},
year={2014},
organization={IEEE},
abstract={With the advancement of information technology, we have got an opportunity to change the learning experience of students. E-learning systems such as Learning Management Systems (LMS), Course Management Systems and Students Management Systems have been emerged as a result of this, aiding a vast variety of education institutes around the globe. Yet, the quality assurance processes are still dependent on conventional student feedback mechanisms that have their inherent drawbacks. This has become a major barrier for quality improvement of the learning experience of students. We have introduced a solution for this through a crowdsourcing based perception capturing and analysis platform that can be adapted in many scenarios seamlessly. The design and implementation of backend analysis algorithms have been discussed along with the results gained from this project.},
misc={https://goo.gl/qp3a9X,EDU,https://i1.rgstatic.net/publication/269465999_Novel_Approach_for_Perception_Analysis_in_a_Learning_Environment/links/59aef81aa6fdcca654242a10/largepreview.png},
doi={10.1109/TALE.2014.7062607}
}
ActivePI: Nisansa de Silva
We propose to advance aspect-based sentiment analysis (ABSA) by developing enhanced models, datasets, and evaluation methods that improve the accuracy and applicability of sentiment classification across multiple domains.