An Effective BiLSTM-CRF Based Approach to Predict Student Achievement: An Experimental Evaluation
- Title
- An Effective BiLSTM-CRF Based Approach to Predict Student Achievement: An Experimental Evaluation
- Creator
- Manigandan E.; Anispremkoilraj P.; Suresh Kumar B.; Satre S.M.; Chauhan A.; Jeyaganthan C.
- Description
- Currently, massive volumes of data are accumulated in databases when people configure new requirements and services. Data mining techniques and intelligent systems are emerging for managing large amounts of data and extracting actionable insights for policy development. As digital technology has grown, it has naturally become intertwined with e-learning practices. In order to facilitate communication between instructors and a diverse student body located all over the world, distance learning programs rely on Learning Management Systems (LMSs). Colleges can better accommodate their students' individual needs by using and analyzing interaction data that reveals variances in their learning progress. Predicting pupils' success or failure is a breeze with the help of learning analytics tools. Better learning outcomes might be achieved through early prediction leading to swift focused action. Preprocessing, feature selection, and model training are the three components of the proposed method. Data cleansing, data transformation, and data reduction are the preprocessing steps used here. It used a CFS to enable feature selection. This study has used a BiLSTM-CRF hybrid approach to train the model. When compared to tried-and-true techniques like CNN and CRF, the proposed method performs effectively. 2024 IEEE.
- Source
- 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2024, pp. 779-784.
- Date
- 2024-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Bidirectional Long Short-Term Memory (Bi-LSTM); Gated Convolution (GC); Self - Attention (SA)
- Coverage
- Manigandan E., Saveetha College of Liberal Arts and Sciences, SIMATS, Department of Computer Applications, Tamilnadu, Chennai, India; Anispremkoilraj P., KSR Institute for Engineering and Technology, Tiruchengode, India; Suresh Kumar B., Chaitanya Bharathi Institute of Technology, Dept of EEE, Telangana, Hyderabad, India; Satre S.M., Bharati Vidyapeeth College of Engineering, Department of Information Technology, Navi Mumbai, India; Chauhan A., School of Sciences, CHRIST (Deemed to Be University), Department of Life Sciences, Bengaluru, Karnataka, India; Jeyaganthan C., AMET Business School, AMET University, Chennai, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835032753-3
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Manigandan E.; Anispremkoilraj P.; Suresh Kumar B.; Satre S.M.; Chauhan A.; Jeyaganthan C., “An Effective BiLSTM-CRF Based Approach to Predict Student Achievement: An Experimental Evaluation,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/19506.