Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551039
Pertenecen a esta colección Tesis y Trabajos de grado de las Maestrías correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
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- Evaluating teaching performance of teaching-only and teaching-and-research professors in higher education through data analysis(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2020-06) Chávez López, Mario Daniel; Cantú Ortiz, Francisco Javier; emipsanchez/tolmquevedo; Torres Delgado, Gabriela; Hernández Gress, Neil; Barrón Cano, Olivia Maricela; Escuela de Ingeniería y Ciencias; Campus Monterrey; Ceballos Cancino, Héctor GibránWe present a study that compares the teaching performance of Teaching-only versus Teaching-and-research professors at higher education institutions. It is a common belief that, generally, Teaching-only professors outperform Teaching-and-Research professors in teaching and research universities according to student perception reflected in student surveys. We present a case study which demonstrates that, in the vast majority of the cases, it is not necessarily true. Our work analyzes these two type of professors at their ability to function as an intellectual challenger, learning guide and their tendency to be recommended to other students. The case study takes place at Tecnológico de Monterrey (Tec), a teaching and research private university in Mexico that has developed a research profile during the last two decades with a mix of teaching-only and teaching and research faculty members and shows a growing accomplishment on world university rankings. We use five datasets from a student survey called ECOA which accounts observations from 2016 to 2019. We present the results of statistical and machine learning methods applied when the taught courses of more than nine thousand professors are taken into account. Methods include Analysis of Variance, Logistic Regression, Recursive Feature Elimination, Coarsened Exact Matching and Panel Data. Contrary to common belief we show that, for the case presented, teaching and research professors perform better or at least the same as teaching-only professors. We also document the differences found on teaching with respect to attributes related to courses and professors.
- A data analytics approach for university competitiveness: the QS rankings(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2020-06) Estrada Real, Ana Carmen; ESTRADA REAL, ANA CARMEN; 791773; Cantú Ortiz, Francisco Javier; emipsanchez/puemcuervo; Sucar Succar, Luis Enrique; Galeano Sánchez, Natalíe María; Hernández Gress, Neil; Monroy Borja, Raúl; School of Engineering and Sciences; Campus Estado de México; Ceballos Cancino, Héctor GibránIn recent years, higher education has been facing the entrance to the internationalmarket due to globalization, this has developed a highly competitive environment, in whichmany institutions have used university rankings as a tool to attract the best academic andstudent talent from all over the world. In this work we take as a base the ranking of QSWord University Rankings and QS Best Student Cities, to apply data science techniques.Extract information on the performance of the most attractive institutions and cities forstudents worldwide, and develop a methodology that allows the stakeholders of the insti-tutions and cities to improve their services for the benefit of students interested in receivingan education of global quality. We accumulated ten years of university rankings (2011-2020) and six years of city rankings (2014-2019), we carried out an exploratory analysisof the indicators and their influence with the final score, later we trained a multiple regres-sion model and panel data to make predictions in the score. Finally, in order to predictthe position, we carry out groupings and train various machine learning algorithms. Withthis work we show a methodology that allows administrators to plan long-term institutionalimprovements to offer a better education and improve their performance in world rankings.
- A Scientometric Study of the Impact of Mexican Institutions in the Period 2007-2016(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2020-05) Méndez López, Diana Carolina; Ceballos Cancino, Héctor Gibrán; 223871; Ceballos Cancino, Héctor Gibrán; emipsanchez; Garza Villarreal, Sara Elena; Juárez Ibarra, Erika Alejandra; Hernández Gress, Neil; Galeano Sánchez, Nathalíe María; Escuela de Ingeniería y Ciencias; Campus Monterrey; Cantú Ortiz, Francisco JavierIn management contexts of science, the study of the impact that different research outputs have often involves a combination of bibliometric and scientometric indicators, as well as peer review and expert opinion. Scientometric indicators are effective for a quantitative analysis as they provide a quick insight of the current and past situation at any organizational level. However, there is no indicator that fits every decision as there are many factors that can have an effect on the impact of an entity (e.g., different publication and citation patterns among disciplines or types of publications), and not all indicators are normalized to account for them. The present study, focuses on the analysis of a set of indicators and their relation with a proposed field-normalized indicator, known as the Field-Weighted Citation Impact for Mexican Institutions (FWCIMX), using a panel data model. The proposed indicator is based on the formula for the FWCI developed by Scopus; the main differences involve ignoring the document type and using data that only contemplates the citations done to Mexican documents, so it only compares Mexican institutions against other Mexican institutions. Two models are proposed: the first model analyzes the relation between the citations per region and the FWCIMX, while the second one analyzes the collaborations per region. Both models include other indicators, and have presented different results when tested in three-year time windows. This research has been performed with the intention of helping researchers and research institutions understand the relation, either positive or negative, that certain indicators have on the behavior of the FWCIMX, which has been designed to compare the impact that the most relevant Mexican institutions have, regardless of the disciplines in which each one of them is more prominent. To achieve these results, it is worth mentioning that the data used was collected from Scopus and comprises a ten-year period that goes from 2007 to 2016. Two batches of experiments were run. The first batch revealed that publishing in journals and trade journals had positive effects on the FWCIMX, so did receiving citations from Oceania, and collaborating with South America and Oceania. In contrast, indicators with negative effects on the FWCIMX include publishing in Open Access periodicals, receiving citations from Europe, and collaborating with Europe. The second batch of experiments revealed that Mexico is the main source of citations for the publications published by the institutions analyzed in this study. The results also suggested that international collaborations and publishing in journals have negative effects. This batch also revealed that publishing in periodicals that are open access have negative effects on the proposed metric. Not so surprisingly, publishing in periodicals in quartiles Q1 and Q2 have positive effects. During the computation of the metrics and the FWCIMX itself, other interesting discoveries where obtained, such as the identification of the averaged expected citations per area and year with respect to the production in Mexico, and the ranking of Mexican institutions with regard to their averaged FWCIMXs.