Evaluation for Teacher’s Ability and Forecasting Student’s Career Based on Big Data
| Autor: | Hlaing May Tin, Zun Hlaing Moe, Mie Mie Tin, Nan Yu Hlaing, Thida San |
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| Rok vydání: | 2018 |
| Předmět: |
Class (computer programming)
Process (engineering) business.industry Computer science 05 social sciences Sentiment analysis Big data 050301 education Variety (cybernetics) Active participation 0502 economics and business ComputingMilieux_COMPUTERSANDEDUCATION Mathematics education 050211 marketing business 0503 education Competence (human resources) |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9789811308680 |
| DOI: | 10.1007/978-981-13-0869-7_3 |
| Popis: | This paper attempts to offer the evaluation of teacher’s ability and the forecasting of students’ career opportunities. Teacher’s ability is decided based on the student’s feedback, active participation in the class, students’ result in the tests and the teacher’s competency. Feedback is an essential element in the learning process. Students’ feedback is an effective tool for teacher evaluation resulting in teacher development. The career opportunity available for a student is a significant area that determines the ranking of a university. This research will also forecast the student’s career based on their individual subject grade. The system analyzes the teacher’s ability by using Sentiment Analysis which is known as Opinion Mining technique. Student career forecast is based on predictive analytic. It comprises of a variety of techniques that predict future outcomes based on historical and current data. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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