An Empirical Study on Students’ Frustration Level Detection
Abstract & Details
Research Area
Computer Engineering
Keywords
Preprocessing
Clustering
Entropy
Fuzzy Classification
Decision Tree
Frustration Level.
Abstract
Now-a-days growing interest in the development of computer systems which respond to users’ affect. We report three small studies, which uses strategies derived from human–human interaction, can reduce user frustration within human–computer interaction. In this paper, we present a strategy to respond to students' different causes of frustration through by providing some questionaries. After analysing these questionaries, this study address the reason for frustration and reduce the frustration instances of student per session.
License
This work is licensed under a Creative
Commons
Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | Poorva Kurhade | KJCOEMR, Pune. |
| 2 | Komal Kalbhor | KJCOEMR, Pune. |
| 3 | Rupali Mohite | KJCOEMR, Pune. |
| 4 | Pooja Talathi | KJCOEMR, Pune. |
| 5 | Prof. Reshma Patil | KJCOEMR, Pune. |
How to Cite
Use the following formats to cite this article in your research.
APA Style
Kurhade, Poorva, Kalbhor, Komal, Mohite, Rupali, Talathi, Pooja, & Patil, Prof. Reshma (2019). An Empirical Study on Students’ Frustration Level Detection. International Journal of Advance Research and Innovative Ideas In Education, 5(3), 546-549.
MLA Style
Kurhade, Poorva, et al. "An Empirical Study on Students’ Frustration Level Detection." International Journal of Advance Research and Innovative Ideas In Education, vol. 5, no. 3, 2019, pp. 546-549.
IEEE Style
Poorva Kurhade, Komal Kalbhor, Rupali Mohite, Pooja Talathi, and Prof. Reshma Patil, "An Empirical Study on Students’ Frustration Level Detection," International Journal of Advance Research and Innovative Ideas In Education, vol. 5, no. 3, pp. 546-549, 2019.
Vancouver Style
Kurhade Poorva, Kalbhor Komal, Mohite Rupali, Talathi Pooja, Patil Prof. Reshma. An Empirical Study on Students’ Frustration Level Detection. International Journal of Advance Research and Innovative Ideas In Education. 2019;5(3):546-549.
Harvard Style
Kurhade, Poorva, Kalbhor, Komal, Mohite, Rupali, Talathi, Pooja, & Patil, Prof. Reshma (2019) 'An Empirical Study on Students’ Frustration Level Detection', International Journal of Advance Research and Innovative Ideas In Education, 5(3), pp. 546-549.
Chicago Style
Kurhade, Poorva, et al. "An Empirical Study on Students’ Frustration Level Detection." International Journal of Advance Research and Innovative Ideas In Education 5, no. 3 (2019): 546-549.
Turabian Style
Kurhade, Poorva, et al. "An Empirical Study on Students’ Frustration Level Detection." International Journal of Advance Research and Innovative Ideas In Education 5, no. 3 (2019): 546-549.
Related Research
Comprehensive Review of Existing Chatbot Systems for Career Assistance, Resume Support, and ATS-Aware Guidance
PDF Unavailable
Development of an AI-Powered Multimodal Web Assistant with Intelligent Resume Building and ATS Enhancement
PDF Unavailable
A Deep Learning-Based Framework for Mood-Oriented Music Recommendation Using Facial Expression Analysis
PDF Unavailable
Survey On : Intelligent Payroll and Human Resource Management Systems: A Systematic Review of Automation, Security, and Analytics
PDF Unavailable
Civic Engagement & Empowerment Platform
PDF Unavailable
Recent Developments in Microneedle Technology and Its Diverse Biomedical Applications
PDF Unavailable
RAG System Development with Pydantic AI ChromaDB & Groq
PDF Unavailable
Machine Learning Based Early Stage Diabetes Detection System
PDF Unavailable
A Survey on Skillsense:AI Career Analyzer App
PDF Unavailable
Employee Performance Portal
PDF Unavailable