Article Gold Open Access 2020

Impact of students evaluation of teaching: a text analysis of the teachers qualities by gender

International Journal of Educational Technology in Higher Education
Journal · Vol. 17 · Issue 1 · Art. 49
Abstract

Today, modern educational models are concerned with the development of the teacher-student experience and the potential opportunities it presents. User-centric analyses are useful both in terms of the socio-technical perspective on data usage within the educational domain and the positive impact that data-driven methods have. Moreover, the use of information and communication technologies (ICT) in education and process innovation has emerged due to the strategic perspectives and the process monitoring that have shown to be missing within the traditional education curricula. This study shows that there is an unprecedented increase in the amount of text-based data in different activities within the educational processes, which can be leveraged to provide useful strategic intelligence and improvement insights. Educators can apply the resultant methods and technologies, process innovations, and contextual-based information for ample support and monitoring of the teaching-learning processes and decision making. To this effect, this paper proposes an Educational Process and Data Mining (EPDM) model that leverages the perspectives or opinions of the students to provide useful information that can be used to enhance the end-to-end processes within the educational domain. Theoretically, this study applies the model to determine how the students evaluate their teachers by considering the gender of the teachers. We analyzed the underlying patterns and determined the emotional valence of the students based on their comments in the Students Evaluation of Teaching (SET). Thus, this work implements the proposed EPDM model using SET comments captured in a setting of higher education. © 2020, The Author(s).

Keywords

Author Keywords

Higher education educational innovation learning process sentiment analysis technology adoption Gender perspective Teacher-student evaluation Teachers' competence

Index Keywords

Author Affiliations
Writing Lab, Tecnológico de Monterrey, Monterrey, NLE, Mexico
School of Engineering Sciences, Tecnológico de Monterrey, Monterrey, NLE, Mexico
Writing Lab, Tecnológico de Monterrey, Monterrey, NLE, Mexico, School of Engineering Sciences, Tecnológico de Monterrey, Monterrey, NLE, Mexico
EMINES School of Industrial Management, Mohammed VI Polytechnic University, Ben Guerir, Marrakesh-Safi, Morocco
Institutional Effectiveness Department, Tecnológico de Monterrey, Monterrey, NLE, Mexico
Funding & Acknowledgements
Instituto Tecnológico y de Estudios Superiores de Monterrey, ITESM
Funding text 1: The authors would like to acknowledge the technical and financial support of Writing Lab, TecLabs, Tecnologico de Monterrey, in the publication of this work. We will also like to acknowledge the Institutional Effectiveness Department, North Region ECOA, Tecnologico de Monterrey, Mexico for provision of the datasets used for the analysis in this study.; Funding text 2: The authors would like to acknowledge the technical and financial support of Writing Lab, TecLabs, Tecnologico de Monterrey, in the publication of this work. We will also like to acknowledge the Institutional Effectiveness Department, North Region ECOA, Tecnologico de Monterrey, Mexico for provision of the datasets used for the analysis in this study.; Funding text 3: This research was funded by Writing Lab, TecLabs unit of Tecnologico de Monterrey, Mexico. Acknowledgements
References 10 References
1 Abu Zohair, Lubna Mahmoud, Prediction of Student’s performance by modelling small dataset size, International Journal of Educational Technology in Higher Education, 16, 1, (2019)
2 Alizadeh, Mehrasa, Evaluating a blended course for Japanese learners of English: why Quality Matters, International Journal of Educational Technology in Higher Education, 16, 1, (2019)
3 Sentiment Analysis on Students Real Time Feedback, (2016)
4 Badri, Masood Abdulla, Identifying potential biasing variables in student evaluation of teaching in a newly accredited business program in the UAE, International Journal of Educational Management, 20, 1, pp. 43-59, (2006)
5 Bianchini, Stefano, Instructor characteristics and students' evaluation of teaching effectiveness: Evidence from an Italian engineering school, European Journal of Engineering Education, 38, 1, pp. 38-57, (2013)
6 Binali, Haji H., A new significant area: Emotion detection in E-learning using opinion mining techniques, 2009 3rd IEEE International Conference on Digital Ecosystems and Technologies, DEST '09, pp. 259-264, (2009)
7 Boex, L. F.Jameson, Attributes of effective economics instructors: An analysis of student evaluations, Journal of Economic Education, 31, 3, pp. 211-227, (2000)
8 Bollen, Johan, Twitter mood predicts the stock market, Journal of Computational Science, 2, 1, pp. 1-8, (2011)
9 Boring, Anne, Gender biases in student evaluations of teaching, Journal of Public Economics, 145, pp. 27-41, (2017)
10 Scienceopen Research, (2016)
Quick Actions
Full Text via DOI
Citation Metrics
58
Times Cited (Scopus)

References 10
Document Identifiers