DETECTING AND IMPROVING STUDENT EMOTIONS USING ACTIONABLE PATTERN DISCOVERY IN STUDENT SURVEY DATA

 

DETECTING AND IMPROVING STUDENT EMOTIONS USING ACTIONABLE PATTERN DISCOVERY IN STUDENT SURVEY DATA

 

Angelina Tzacheva1 , Akshaya Easwaran2 and Priyanka Jadhav31Department of Computer Science, University of North Carolina at Charlotte, Charlotte, North Carolina – 28223, USA2Department of Information Technology, University of North Carolina at Charlotte, Charlotte, North Carolina - 28223, USA3Department of Computer Science, University of North Carolina at Charlotte, Charlotte, North Carolina – 28223, USA

 

ABSTRACT

 

Each year number of students enrolling in higher education is increasing significantly. Students from diverse backgrounds can be found in a class. These changing circumstances are making it necessary to develop Innovative teaching and Learning methodologies. Active Learning methodology is an innovative strategy and Lightweight Team comes under this Active Learning methodology. Lightweight Team approach is one such low-stake activity and it has very little or no direct impact on a student's grade whereas it makes the learning process fun and interesting. A student’s Emotion towards a class plays a major role in their class performance. In this work we use the feedback from the Student Survey Data which aims to evaluate student emotions and overall satisfaction with Course Teaching methods and Group Work experience. We use Actionable Pattern Discovery methodology to provide suggestions in the form of Action Rules to enhance student Emotions thereby achieving a Positive Learning and Teaching experience.

 

KEYWORDS

 

Actionable pattern discovery, education, emotion detection, data mining, active learning.

 

Full Text: https://airccse.com/adeij/papers/3221adeij04.pdf

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