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Call for Proposals: Fostering the Analysis of Competency-based Higher Education

Competences

 

Competency-based education (CBE) as a higher education model is one of the topics that has shown an increased interest in the study, both by university academics and the labor sector, in the last decade. The scientific and academic production in this area has been rising steadily in the last 12 years [1]. One characteristic of CBE is the diversity of suggestions to define and classify competencies. This phenomenon can be explained by the diversity of theoretical perspectives that make it possible to conform to the CBE model [2]. For the effect of this Call of Proposals, there is one definition on which the TEC21 Educational Model is supported, as well as two types of competencies. Then, competency is defined as a combination of knowledge, skills, and attitudes appropriate to the context. Competence indicates the ability to adequately apply learning outcomes in a defined context (education, work, personal or professional development). Competence is not limited to cognitive elements; it also encompasses functional aspects, as well as interpersonal attributes, and ethical values [3].

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On the one hand, disciplinary competencies are built from diverse knowledge (knowing, knowing how to do, knowing how to be, knowing how to live together) that integrate, configure, and represent the area of specialized knowledge in which the students are being trained. On the other hand, transversal competencies are built from the knowledge that allows the development of capabilities that complement the disciplinary performance, without necessarily being linked to a thematic specialization. These competencies are especially useful to face tasks of different types and in diverse contexts, in which it is required to integrate thinking processes, decision-making, communication, interaction, and collaboration, to mention a few [4]. The information that emerges from the educational activities that conform to the learning outcomes from CBE is frequently recorded in Learning Management Systems (LMS). Nevertheless, these databases are left aside most of the time as the criteria that configure and give sense to CBE evidence data storage are vast and complex.

Currently, competency-based training goes beyond theoretical knowledge, on the contrary, it requires the putting into practice of knowledge, skills, and motivations to achieve the expected capacities at a professional level. In this sense, educational institutions carry out training programs where it is not only important to monitor the development of skills at all levels, but also the continuous review and updating of skills to meet the requirements of the ever-changing labor market. It is here where the statistical and learning models contribute to the understanding of the elements involved in the development, monitoring, and evaluation of competencies; in addition to the prediction and modeling of skill profiles, which are the basis for generating new training offers. Some of the research efforts carried out are focused on the evaluation of digital competence profiles [5-6], the alignment of online profiles and job advertisements [7], the updating of the professional and academic competencies from profiles obtained from the Web [8], and the use of competencies to guide the adaptation process of a learning environment [9], among others.

To face these challenges, Tecnologico de Monterrey evolved towards a challenge-based and competency-based educational model, on which this data-driven call is supported, called the TEC21 Educational Model. This model is focused on preparing future professionals as leaders and entrepreneurs by strengthening the skills of the next generations to develop the competencies required to face the challenges and opportunities of the 21st century. These competencies must be developed through four pillars that promote student transformation in both disciplinary and personal aspects: 1) Challenge-based Learning, 2) Flexibility in how and where to learn, 3) A memorable university experience, and 4) Inspiring Professors [10]. For this purpose, the TEC21 Model offers different learning modules called Week i and Semester i to expose students to experiences close to the challenges with the intention of developing successful competencies in them [10]. In addition, the student has the opportunity to participate in the LiFE (Leadership and Student Education) program (that is, in sports, cultural, and student leadership activities), in a voluntary or structured manner, which contributes to the development of transversal competencies and, in some cases, professional competencies [11].

Therefore, the challenge of this call is to propose new approaches based on Statistical models, Artificial Intelligence algorithms, and/or Visualization techniques that allow for the analysis of the development of competencies in undergraduate students in the TEC21 Educational Model of the Tecnologico de Monterrey in Mexico. The purpose of this challenge is to identify the activities and types of evidence that impact student learning in order to provide university teachers and heads with the tools that support them in the design of optimal didactic strategies, according to the competencies to be developed in different educational programs. Within the expected research proposals, the following approaches are suggested, but not limited to:

  • Analysis by school or program.
  • Analysis of transversal or disciplinary competencies.
  • Analysis of the competencies related to each subject.
  • Analysis of soft skills in study programs.
  • Analysis of the development of the competencies completed or not completed.
  • Analysis of training activities and their impact on the development of competencies.
  • Analysis of competencies from the labor market point of view.

Audience: This call is open to all researchers, faculty, analysts, and graduate students with an interest in educational data and knowledge of Statistical models, Artificial Intelligence algorithms, and/or Visualization techniques. Joint proposals are welcome, with at least one researcher from Tecnologico de Monterrey, who can provide further context on the TEC21 Educational Model. You can meet our researchers at our research platform.

Keywords: Competencies; Skills; Performance-based Assessment; Challenge-based Learning; Higher Education; Labor Market.

  1. Scopus. Competency-based education analyzes research results. Available online: https://www.scopus.com/ (accessed on 29 November 2022).
  2. Gervais, J. (2016). The operational definition of competency-based education. The Journal of Competency-Based Education, 1(2), 98–106.
  3. UNESCO-IBE. Competence terminology. Available online: http://www.ibe.unesco.org/en/glossary-curriculum-terminology/c/competence (accessed on 29 November 2022).
  4. Valenzuela González, J.R. (2016). (Ed.), Competencias transversales para una sociedad basada en  conocimiento. Ciudad de México, México: Cengage Learning Editores.
  5. González-Eras, A., Dos Santos, R., & Aguilar, J. (2022). Evaluation of Digital Competence Profiles Using Dialetheic Logic. International Journal of Artificial Intelligence in Education, 1-29.
  6. González-Eras, A., Dos Santos, R., & Aguilar, J. (2020). Análisis de las contradicciones en las competencias profesionales en los textos digitales usando lógica dialéctica. Revista Ibérica de Sistemas e Tecnologias de Informação, (E27), 150-163.
  7. González-Eras, A., & Aguilar, J. (2019). Determination of professional competencies using an alignment algorithm of academic profiles and job advertisements, based on competence thesauri and similarity measures. International Journal of Artificial Intelligence in Education, 29(4), 536-567.
  8. González-Eras, A., & Aguilar, J. (2019). Esquema para la actualización de Ontologías de Competencias en base al Procesamiento del Lenguaje Natural y la Minería Semántica. Revista Ibérica de Sistemas e Tecnologias de Informação, (E17), 433-447.
  9. González-Eras, A., Buendia, O., Aguilar, J., Cordero, J., & Rodriguez, T. (2017). Competences as services in the autonomic cycles of learning analytic tasks for a smart classroom. In the International Conference on Technologies and Innovation (pp. 211-226). Springer, Cham.
  10. Tecnológico de Monterrey. TEC21 Education Model. Available online: https://internationalfaculty.tec.mx/sites/g/files/vgjovo1851/files/tec21-model.pdf (accessed on 30 November 2022).
  11. CONECTA NEWS DESK. Tec de Monterrey has reinvented its student experience, presents LiFE. Available online: https://conecta.tec.mx/en/news/national/institution/tec-de-monterrey-has-reinvented-its-student-experience-presents-life (accessed on 2 December 2022)

Dataset Overview

The dataset that will be provided to applicants includes anonymized information related to undergraduate students who have taken at least one semester in the TEC21 Educational Model at Tecnologico de Monterrey in Mexico from August-December 2019 to February-June 2022 (six cohorts). Among the data categories available in this dataset are:

  • Sociodemographic information (age, gender, nationality).
  • Admission information (Tec system, cohort, program/school).
  • Academic information (last term average, current average, academic status).
  • Subject information (type, modality, period).
  • Competency information (type, sub-competency, level)
  • Activity information (title, assignments, evidence).

You can download a simplified version of the data dictionary and a data teaser of the dataset below.

  • Data Dictionary

  • Data Teaser

Due to the sensitivity of the data, authors of the accepted proposals must sign our Terms of Use document prior to receiving the dataset.

Advisory Board

For this Call for Proposals, the IFE Living Lab & Data Hub team counts on the valuable expertise of five academic advisors from Mexico, Hungary, and Ecuador:

Claudia Camacho Zuñiga

Claudia Camacho Zuñiga

Professor at Tecnologico de Monterrey, Mexico
Genaro Zavala Enríquez

Genaro Zavala Enríquez

Interim Director of the Research Lab of the Institute for the Future of Education. Tecnologico de Monterrey, Mexico
Katherina Edith Gallardo Córdova

Katherina Edith Gallardo Córdova

Leader of the Research Unit on Competency-based Learning. Tecnologico de Monterrey, Mexico
Roland Molontay

Roland Molontay

Founder and Director of the Human and Social Data Science Laboratory (HSDSLab). Budapest University of Technology and Economics, Hungary
Alexandra Cristina González Eras

Alexandra Cristina González Eras

Professor at Universidad Técnica Particular de Loja, Ecuador

Overall Process: Important Dates

  • January 9, 2023
  • January 24, 2023
  • February 5, 2023
  • March 3, 2023
  • August 14, 2023
Q&A Session

January 9, 2023. 10:00 (GMT-6)
 Q&A session.

The Q&A session has already taken place; however, you can view the presentation and the recording of the session

 

Deadline for submission of the extended abstracts

January 18, 2023 23:59 (GMT-6)
January 24, 2023 23:59 (GMT-6)
Deadline for submission of the extended abstracts.

  • The length of the abstract is one page and it is recommended to make a brief description of the research proposal, mainly including its objective, as well as the techniques, models, algorithms, or methods to be used.
  • It is suggested to use the following template to send your abstract: Extended Abstract Template.
  • Extended abstracts will be managed by correspondence to ife.datahub@servicios.tec.mx (Cc: joanna.alvarado@tec.mx).
Deadline for submission of the full proposal

January 31, 2023 23:59 (GMT-6)
February 5, 2023 23:59 (GMT-6)
Deadline for submission of the full proposal.

  • You can send your proposal in two PDF documents: a document without author(s) information and a document with author(s) information.
  • It is necessary to use the template defined by the IFE Living Lab & Data Hub for the proposal. The Word template is found here.
  • Full proposals will be managed by correspondence to ife.datahub@servicios.tec.mx (Cc: joanna.alvarado@tec.mx).
Notification of the result and release of the dataset

March 3, 2023
Notification of the result and release of the dataset to the selected applicants.

  • If the proposal is accepted, it is mandatory to acknowledge the support of the Tecnologico de Monterrey's IFE Living Lab & Data Hub in any publications, presentations, or technical reports that result from this call. Please include the following legend: The authors would like to acknowledge the Living Lab & Data Hub of the Institute for the Future of Education, Tecnologico de Monterrey, Mexico, for the data used in this work and provided through the Call "Fostering the Analysis of Competency-based Higher Education". Additionally, please use the DOI https://doi.org/10.57687/FK2/R9LOXP for referring to the dataset.
  • The IFE Data Hub will provide the dataset to researchers, whose proposals were accepted, on the condition that their codebooks will be available for disclosure.
  • The academic advisors may be mentors of one of the best-evaluated proposals.
  • The results of the experimentation should be documented in the form of an article according to the guidelines of the Q1/Q2 Journal selected by the applicants to publish the manuscript.
Deadline for submission of the full manuscript

August 14, 2023
Deadline for submission of the full manuscript.

  • Authors are requested to include the following legend in the acknowledgments of the manuscripts resulting from this call: The authors would like to acknowledge the Living Lab & Data Hub of the Institute for the Future of Education, Tecnologico de Monterrey, Mexico, for the data used in this work and provided through the Call "Fostering the Analysis of Competency-based Higher Education". Additionally, please use the DOI https://doi.org/10.57687/FK2/R9LOXP for referring to the dataset.
  • The dataset processed and enriched by the applicant for experimentation can be deposited in the IFE's Educational Innovation collection of the Tecnologico de Monterrey's Data Hub. Please, contact us at ife.datahub@servicios.tec.mx for more information.
  • To document the experimentation carried out by the applicant, the published article should be sent to the IFE’s Data Hub email address ife.datahub@servicios.tec.mx.

Further Information

For any questions or comments regarding this Call for Proposals, please write to us at the following emails:

  • Dr. Joanna Alvarado-Uribe, Coordinator of the Call for proposals
     joanna.alvarado@tec.mx
  • B.S. Paola Mejía-Almada, Coordinator of the dataset for this Call
     gabriela.almada@tec.mx
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