A data analytics approach to contrast the performance of teaching (only) vs. research professors
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TECHNICAL PAPER
A data analytics approach to contrast the performance of teaching (only) vs. research professors Mario D. Chavez1 · Héctor G. Ceballos1 · Francisco J. Cantu-Ortiz1 Received: 13 November 2019 / Accepted: 12 September 2020 © Springer-Verlag France SAS, part of Springer Nature 2020
Abstract This research article presents a study to compare the teaching performance of teaching-only versus teaching-and-research professors at higher education institutions. It is a common belief that, generally, teaching professors outperform research professors in teaching-and-research universities according to student perceptions reflected in student surveys. This case study presents experimental evidence that shows this is not always the case and that, under certain circumstances, it can be the contrary. The case study is from Tecnologico de Monterrey (Tec), a teaching-and-research, private university in Mexico that has developed a research profile during the last two decades using a mix of teaching-only and teaching-and-research faculty members; during this time period, the university has had a growing ascendancy in world university rankings. Data from an institutional student survey called the ECOA was used. The data set contains more than 118,000 graduate and undergraduate courses for 5 semesters (January 2017 to May 2019). The results presented were derived from statistical to data mining methods, including Analysis of Variance and Logistic Regression, that were applied to this data set of more than nine thousand professors who taught those courses. The results show that teaching-and-research professors perform better or at least the same as teaching-only professors. The differences found in teaching with respect to attributes like professors’ gender, age, and research level are also presented. Keywords Student Evaluation of Teaching (SET) · Teaching Professor · Research Professor · Data Science · ANOVA and Logistic Regression · Innovation in Higher Education
1 Introduction Assessment of teaching and methods of evaluation are active fields of research and present opportunities for innovation, spanning from elementary grades to higher education levels [1]. The phenomenon of digital transformation has brought new technologies that are revolutionizing modern organizations, including higher education institutions, where teaching and learning are experiencing novel pedagogical methods that require new ways to assess the quality of education
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Francisco J. Cantu-Ortiz [email protected] Mario D. Chavez [email protected] Héctor G. Ceballos [email protected]
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School of Engineering and Science, Tecnologico de Monterrey, Ave. Eugenio Garza Sada 2501, 64989 Monterrey, N.L., Mexico
from the viewpoints of administrators, teachers, and students [2]. Digital technologies and Artificial Intelligence have made it possible to combine traditional physical presence with online, virtual tools to deliver teaching as a worldwide phenomenon. Emerging technologies such as the Internet of Things (IoT), Cloud Computing, Big Data, Machine L
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