Categorizing the Students' Activities for Automated Exam Proctoring Using Proposed Deep L2-GraftNet CNN Network and ASO Based Feature Selection Approach.
Tanzila SabaAmjad RehmanNor Shahida Mohd JamailSouad Larabi Marie-SainteMudassar RazaMuhammad SharifPublished in: IEEE Access (2021)
Keyphrases
- feature selection
- text categorization
- student learning
- multi task
- learning environment
- mid term
- lifelong learning
- multiple choice questions
- collaborative learning
- young students
- learning activities
- undergraduate students
- tutoring system
- learning outcomes
- mutual information
- network structure
- machine learning
- multiple choice
- learning scenarios
- distance learning
- higher education
- learning experience
- learning styles
- virtual laboratories
- e learning
- meta cognitive
- online environment
- cellular neural networks
- high school students
- open ended
- multi class
- information gain
- secondary school
- collaborative activities
- wireless sensor networks
- text classification
- online course
- learning process
- intelligent tutoring systems