Authors:
Liliana Fernández-Samacá, Sonia E. Díaz-Márquez
Abstract:
This article proposes a learning assessment model that enables staff to systematize information analysis from learning and teaching scenarios for curriculum evaluation. The learning assessment is represented as a closed-loop control system, with students at the center of the process, staff as the actuator, and students’ impressions and assessment instruments as the sensors. By a matrixial interpretation of curricular mapping for learning assessment. The collected information is represented as course indicators, which are used to calculate learning outcome indicators as the system’s output. In this model, the curricular mapping of the program is represented by a weighted contributions matrix called the ‘program matrix,’ whose coefficients denote the different levels or contributions of the courses to the learning outcomes. Thus, learning outcome indicators are obtained as a linear combination of the weighted contributions to the course. This article also presents an example illustrating the application of the model, in which data from over 12 semesters are analyzed for two engineering programs. We discuss the way in which this model simplifies data acquisition and provides a scalable solution for learning assessment management in curriculum evaluation and warn of the importance of establishing curricular alignment in the curricular mapping and course design stages for the success of the learning assessment.
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Authors:
Zvi Bekerman
Abstract:
The Palette of Virtues project boldly reimagines STEM education by rejecting its value-neutral facade, rooted in Cartesian dualism and positivist traditions that foster alienating, competitive pedagogies. The project is enacted in early childhood educational settings through collaborative programming, storytelling, and artistic activities, in which children, teachers, and facilitators jointly engage with computational tools as part of shared, value-laden practice. Drawing on insights from anthropology, dialogical philosophy, and arts education, we propose that effective STEM reform requires a fundamental shift: moving education from transmission to co-construction, from individual mastery to collaborative and relational meaning-making, and from abstract neutrality to culturally grounded inquiry.
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Authors:
Benjamín Maraza-Quispe, Edwin Reyes-Villalba, Victor Hugo Rosas-Iman, Lita Marianela Quispe-Flores, Walter Choquehuanca-Quispe, Olga Melina Alejandro-Oviedo, Giuliana Feliciano-Yucra, Atilio Cesar Martínez-Lopez, Roberto Carlos Pari-Viza
Abstract:
Artificial intelligence (AI) has progressively transformed higher education by enabling personalized and interactive learning experiences. However, there is still limited empirical evidence on the effectiveness of structured AI-supported pedagogical models in the development of digital competence. The objective of the study was to determine the impact of an AI-supported teaching model on the development of digital competence in university students. A quasi-experimental design with pretest–posttest and a control group was employed, with a sample of 120 students. The experimental group participated in a structured instructional model based on the guided use of generative AI tools, while the control group followed a traditional approach. A validated instrument based on the DigCompEdu framework was used, evaluating five dimensions: Information literacy, digital communication, content creation, security, and problem solving. The results showed statistically significant improvements in all dimensions in the experimental group compared to the control group (p < 0.001). Mean scores increased from approximately 3.0 to 3.8 in the experimental group, while the control group showed minimal improvements. High effect sizes were identified (Cohen’s d = 1.7–1.8), indicating a significant impact of the intervention. In conclusion, structured AI-supported pedagogical models significantly improve digital competence in higher education, highlighting the importance of integrating AI through guided and well-founded pedagogical approaches.
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Authors:
Júlia Vicens-Figueres, Adrián Pérez-Suay, Ana B. Pascual-Venteo, Steven Van Vaerenbergh, Ismael García-Bayona
Abstract:
This pilot study investigates the learning process of the arithmetic mean through frequency tables in students enrolled in the fourth year of compulsory secondary education (4° ESO) in Spain (ages 15–16). The investigation examines the effect of grouped data supported by verbal examples and contextualized problems. Although based on a small sample, preliminary findings suggest that students tend to rely more on numerical examples than on formal algebraic expressions, and that verbal contexts may decrease attention to graphical representations. Using eye-tracking technology enabled the real-time collection of eye-fixation data on specific Areas of Interest (AOIs), providing detailed insights into individual problem-solving behaviours. Error analysis revealed persistent misconceptions related to grouped data calculations and interpretations of the mean as an expected value, highlighting challenges in deep conceptual understanding. Additionally, integrating eye-tracking demonstrated potential to address classroom diversity by informing the development of instructional materials adapted to different learning profiles.
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Authors:
Adrián Suárez, Joaquín Pérez-Soler, Raimundo García-Olcina, Abraham Menéndez, Pedro A. Martínez, Roberto Herráiz, Andrea Amaro, Victor Solera, Luís M. Giraldo, Daniel Ibáñez, Jesús López, Daniel Esperante, Julio Martos, Jesús Soret, José Torres
Abstract:
This paper presents the implementation and continuous refinement of a questionnaire-based assessment approach for laboratory instruction in undergraduate engineering education. In this method, students complete individual questionnaires at the end of each lab session. It was introduced to address challenges associated with traditional evaluation methods such as group reports. Over multiple academic years, the approach was applied in core laboratory subjects within the Degree in Electronic Engineering for Telecommunications at the University of Valencia. Based on student feedback collected through structured surveys, the teaching team introduced key modifications—most notably, the reformulation of test items and the inclusion of performance checkpoints—to improve alignment between assessed outcomes and the learning process. Analysis of student responses before and after these changes indicates improved perceptions regarding fairness, relevance, and overall satisfaction with the assessment method. The results support the effectiveness of this approach in enhancing student engagement and instructional consistency, while highlighting areas for further pedagogical development.
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Authors:
Rogério de Camargo Cortina, Andréa Sabedra Bordin, Jones Baroni Ferreira de Menezes, Vinicius Ramos, Emanuel Marques Queiroga, Tiago Primo, Roberto Muñoz, Cristian Cechinel
Abstract:
As the demand for data-driven strategies in education grows, learning analytics dashboards have proven to be essential tools for enhancing transparency, monitoring, and decision-making at various administrative levels. This study examines the acceptance of a prototype control panel developed to provide relevant information to municipal education departments. Utilizing the Technology Acceptance Model (TAM), the study evaluates dashboard experience satisfaction, perceived ease of use, and behavioral intention to use the implemented dashboards. Data were collected through a survey that included secretaries of education, technical agents, administrative directors, pedagogical coordinators, school principals, and secretaries, after testing and analyzing a functional prototype. The results indicate a high level of satisfaction with the dashboards during phase 3 of the experiment, with an overall dashboard experience satisfaction score of 5.13 on a 7-point scale and a perceived ease of use score of 4.89. Additionally, the behavioral intention to use the dashboards was significant, with a score of 4.89. These findings indicate that participants viewed the dashboards positively as support tools for municipal educational management. The study discusses the practical implications of these results.
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Authors:
Guillermo Vera-Amaro, José Rafael Rojano-Cáceres
Abstract:
While accessibility research often emphasizes the experiences of blind users as consumers of online content, far less attention has been given to their role as content authors in Content Management Systems (CMS). For blind users, the accessibility of CMS platforms is fundamental to ensure efficient navigation, content creation, and overall usability. This study investigates the accessibility challenges faced by blind authors when working with WordPress as a representative CMS, identifies barriers related to navigation and content management, and offers insights to improve inclusive design. A mixed evaluation strategy was employed, combining automated testing tools with a manual assessment based on the barrier walkthrough method. Three blind participants and one sighted participant completed representative CMS tasks—such as navigation, content editing, and menu creation—using NVDA and JAWS screen readers. In addition, an expert evaluation analyzed the severity of the identified barriers. Findings indicate that block-based and drag-and-drop interfaces remain highly inaccessible for screen reader technologies, while AI-powered image descriptions help reduce dependence on sighted assistance. Results also highlight a clear mismatch between pages considered accessible by automated tools and the barriers observed in manual testing, underscoring the limitations of automated evaluations. Overall, the study stresses the need for CMS platforms to improve navigation consistency, reduce dependence on dropdown submenus, and integrate AI support to better address the needs of blind authors.
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Authors:
Danilo Valdes-Ramirez, Christian Samhir Grijalva Quiñonez, Genaro Zavala
Abstract:
Previous studies on competency-based education (CBE) in Higher Education (HE) have primarily relied on small samples, short time frames, and self-perceived measures of competencies, leaving a gap in understanding how STEM students’ competencies evolve through direct evaluations. This study addresses the challenge of evaluating how students’ competencies evolve throughout CBE programs in HE. We conducted longitudinal analyses of competency evaluation data from a cohort of $4,044$ STEM students enrolled in CBE programs. The study examines the evolution of students’ observed competency ratios across six academic periods and analyzes variations according to four between-subject variables: sex, preparatory school background, geographic region, and knowledge area. Competency data were collected through institutional evaluation processes and transformed for longitudinal analysis. Statistical procedures, including repeated measures ANOVA, post-hoc tests, and linear mixed-effect models, were applied to identify significant changes in competency ratios across time and between groups. Results revealed statistically significant improvements in the observed competency ratios throughout the six academic periods, indicating consistent growth in students’ demonstrated competencies. However, differences across some demographic and institutional factors highlight points where competency development progresses unevenly. These findings provide empirical evidence of how CBE models influence STEM students’ competency acquisition over time. They offer valuable insights for educators, curriculum designers, and policymakers seeking to strengthen CBE implementation. In particular, the study emphasizes the importance of continuous monitoring and targeted instructional support during specific academic stages to ensure that all students achieve the intended competencies by graduation.
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Authors:
Pedro Gómez Álvarez, Julio Hurtado Alegria
Abstract:
Engineering educators increasingly recognize that computational thinking (CT) cannot be taught in isolation; however, most higher education programs continue to treat it as a purely individual technical skill. This article presents CT4E-COLLAB, an evolution of the CT4E model that integrates STEM competencies, the principles of collaborative engineering (CE), and reusable ThinkLets in the development of CT. We present a quasi-experimental study conducted with 60 first-semester Systems Engineering students at the University of Cauca, Colombia, in which half of the participants received traditional instruction and the other half completed 10 structured CT4E-COLLAB sessions. Assessed using the Computational Thinking Test (CTt), the Technology Acceptance Model (TAM), the Intrinsic Motivation Inventory (IMI), and a collaboration observation rubric, the experimental group outperformed the control group in all dimensions: The differences between the groups were statistically significant (p < 0.05 for all instruments), with effect sizes in the medium-to-large range (d = 0.73 to 0.95) and 95% confidence intervals that excluded zero in all cases. The improvements were greatest in collaboration and motivation, dimensions that standard CT instruction rarely addresses explicitly. These findings suggest that formalizing collaboration as a process—rather than leaving it to chance—is a lever worth pulling in engineering education in Latin America.
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Authors:
Paolo Manfredi, Enrico Perano
Abstract:
E-learning courses and tools have increased their importance and have been adopted by a growing number of universities, mainly due to the unfortunate occurrence of the COVID-19 pandemic. This work presents an asynchronous and online remedial course implemented in Moodle to assist students enrolled in undergraduate engineering classes of electrical circuit theory. The course is organized in weekly modules that are delivered in parallel to regular classes. Each module consists of a preliminary test to ascertain the student’s preparation on the topic and learning units whose access is restricted to students who fail the preliminary test. The approach is suitable for large classes and is aimed to avoid students’ procrastination and promote additional and constant practice throughout the course, thereby eventually improving also their performance at the final examination as well as their preparation for subsequent courses involving the same topics. Two experiments conducted in consecutive academic years, involving 407 and 379 students, are discussed. The exam performance of students who attended the remedial classes, even those with low initial performance, was significantly better compared to those who did not participate at all. Additionally, the correlation with past exam scores demonstrates that students who engage with the Moodle course show substantial improvements in their exam scores.
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