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Automated Doubt Identification From Informal Reflections Through Hybrid Sentic Patterns And Machine Learning Approach, Siaw Ling Lo, Kar Way Tan, Eng Lieh Ouh
Automated Doubt Identification From Informal Reflections Through Hybrid Sentic Patterns And Machine Learning Approach, Siaw Ling Lo, Kar Way Tan, Eng Lieh Ouh
Research Collection School Of Computing and Information Systems
Do my students understand? The question that lingers in every instructor’s mind after each lesson. With the focus on learner-centered pedagogy, is it feasible to provide timely and relevant guidance to individual learners according to their levels of understanding? One of the options available is to collect reflections from learners after each lesson to extract relevant feedback so that doubts or questions can be addressed in a timely manner. In this paper, we derived a hybrid approach that leverages a novel Doubt Sentic Pattern Detection (SPD) algorithm and a machine learning model to automate the identification of doubts from students’ …
Text Analytics Approach To Extract Course Improvement Suggestions From Students’ Feedback, Swapna Gottipati, Venky Shankararaman, Jeff Rongsheng Lin
Text Analytics Approach To Extract Course Improvement Suggestions From Students’ Feedback, Swapna Gottipati, Venky Shankararaman, Jeff Rongsheng Lin
Research Collection School Of Computing and Information Systems
In academic institutions, it is normal practice that at the end of each term, students are required to complete a questionnaire that is designed to gather students’ perceptions of the instructor and their learning experience in the course. Students’ feedback includes numerical answers to Likert scale questions and textual comments to open-ended questions. Within the textual comments given by the students are embedded suggestions. A suggestion can be explicit or implicit. Any suggestion provides useful pointers on how the instructor can further enhance the student learning experience. However, it is tedious to manually go through all the qualitative comments and …
Sufat: An Analytics Tool For Gaining Insights From Student Feedback Comments, Siddhant Pyasi, Swapna Gottipati, Venky Shankararaman
Sufat: An Analytics Tool For Gaining Insights From Student Feedback Comments, Siddhant Pyasi, Swapna Gottipati, Venky Shankararaman
Research Collection School Of Computing and Information Systems
Teacher evaluation is a vital element inimproving student learning outcomes. Course and instructor feedback given bystudents, provides insights that can help improve student learning outcomes andteaching quality. Teaching and course evaluation systems help to collectquantitative and qualitative feedback from students. Since manually analysingthe qualitative feedback is painstaking and a tedious process, usually, onlythe quantitative feedback is often used for evaluating the course and theinstructor. However, useful knowledge is hidden in the qualitative comments, inthe form of sentiments and suggestions that can provide valuable insights tohelp plan improvements in the course content and delivery. In order toefficiently gather, analyse and provide …