Browsing by Author "Hilliger Carrasco, Isabel"

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    Are all engineering students capable of recognizing ethical and professional issues? An assessment approach to Engineering ethics
    (2017) Hilliger Carrasco, Isabel; Strello Toledo, Andrés Ignacio; Castro, Ignacio; Pérez San Agustín, Mar
    Engineering schools offer ethical training along with the transfer of technical knowledge and the development of other professional skills. The primary objective of this training is to prepare engineering graduates to face diverse ethical issues in the workplace. Thus, exhaustive information is needed to assess whether students are able to recognize potential conflicts that may arise during practice. Despite its importance, there are few studies about the assessment of this ability. This study presents a sequential mixed methodology to assess rigorously the ethics teaching and learning experience in a selective engineering school in Chile. First, we interviewed school authorities, faculty and undergraduate students about their perceptions of the school’s approaches to teach ethics. Second, we designed a quantitative instrument to measure students’ ability to recognize ethical and professional issues, to accept personal responsibility, to be aware of ethical codes, and to obtain learning benefits from different ethics training activities. Significant differences were found in individual ethical reasoning to identify issues by gender and socioeconomic status. Implications regarding improvement actions in the research site were discussed. Additionally, considerations for adopting the assessment approach by other institutions were also presented.
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    Building Institutional Capacity for Learning Analytics: Top-Down & Bottom-Up Initiatives
    (2022) Perez-Sanagustin, Mar; Hilliger Carrasco, Isabel; Maldonado-Mahauad, Jorge; Perez-Alvarez, Ronald
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    Design of a Curriculum Analytics Tool to Support Continuous Improvement Processes in Higher Education
    (2020) Hilliger Carrasco, Isabel; Aguirre, Camila; Miranda, Constanza; Celis, Sergio; Perez-Sanagustin, Mar
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    Enhancing Feedback Uptake and Self-Regulated Learning in Procedural Skills Training
    (2024) Villagrán Gutiérrez, Ignacio Andrés; Hernández Román, Rocío Belén; Schuit Condell, Gregory Kees; Neyem, Hugo Andrés; Fuentes Cimma, Javiera Carolina; Larrondo Vergara, María Loreto; Margozzini Delorenzo, Elisa; Hurtado Bunster, María Teresa; Iriarte Vásquez, Zoe; Miranda Mendoza, Constanza Sofía; Varas Cohen, Julián Emanuel; Hilliger Carrasco, Isabel
    Remote technology has been widely incorporated into health professions education. For procedural skills training, effective feedback and reflection processes are required. Consequently, supporting a self-regulated learning (SRL) approach with learning analytics dashboards (LADs) has proven beneficial in online environments. Despite the potential of LADs, understanding their design to enhance SRL and provide useful feedback remains a significant challenge. Focusing on LAD design, implementation, and evaluation, the study followed a mixed-methods two-phase design-based research approach. The study used a triangulation methodology of qualitative interviews and SRL and sensemaking questionnaires to comprehensively understand the LAD’s effectiveness and student SRL and feedback uptake strategies during remote procedural skills training. Initial findings revealed the value students placed on performance visualization and peer comparison despite some challenges in LAD design and usability. The study also identified the prominent adoption of SRL strategies such as help-seeking, elaboration, and strategic planning. Sensemaking results showed the value of personalized performance metrics and planning resources in the LAD and recommendations to improve reflection and feedback uptake. Subsequent findings suggested that SRL levels significantly predicted the levels of sensemaking. The students valued the LAD as a tool for supporting feedback uptake and strategic planning, demonstrating the potential for enhancing procedural skills learning.
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    Ética y seguridad en la investigación: aprendizajes y desafíos
    (Ediciones UC, 2022) Alarcón Bustos, Mariela; Arenas Morales, Verónica; Arévalo Nally, Constanza; Bonacic Salas, Cristián; Bravo Valenzuela, Paulina; Cabrera Oyarzún, Alejandro; Cáceres Soto, Nataly Edith; Caprile Etchart, Paola Francisca; Díaz Sacco, Alessandra; Gimpel Rivera, Jessica; Guzmán Durán, Ana María; Hilliger Carrasco, Isabel; Ibacache REyes, Felipe Andrés; López González, Dany; Martínez Pereira, Alejandra; Medina Silva, Rafael; Miranda Molina, Carlos Alberto; Muñoz Baeza, Ana; Nogueira Llovet, Amanda Antonia; Pastén González, Pablo Arturo; Pavez Guerrero, Paulina; Ramaciotti Godoy, Clara; Ramos Vergara, Paulina; Roschzttardtz Choucroun, Hannetz France; Troncoso Troncoso, Carlos Patricio; Valera, Luca; Várgas Sepúlveda, Jonathan; Santana López, Alejandra Isabel; Valera, Luca
    ¿Por qué es importante y necesaria la ética de la investigación en Chile? Se convoca aquí a más de setenta académicos y profesionales a presentar sus reflexiones, orientaciones y aprendizajes asociados al resguardo ético y de la seguridad en investigación. Este libro permite una aproximación al quehacer de las universidades chilenas abordando las temáticas que moviluzan a los comités éticocientíficos y ofrece una panorámica de sus aportes en la formación de las buenas prácticas de investigación en las comunidades universitarias. Esta publicación constituye un aporte a la literatura en la gestión de la ética y seguridad en investigación académica desde y para un público hispanohablante que sin duda contribuirá a mejorar estrategias de gestión y desarrollo en estos ámbitos, además de contribuir a la construcción de una sociedad más humana y respetuosa del entorno social, cultural y natural, en el contexto de la generación de conocimientos de alto nivel.
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    Evaluating usage of an analytics tool to support continuous curriculum improvement
    (2019) Hilliger Carrasco, Isabel; Miranda Mendoza, Constanza Sofía; Celis, Sergio; Pérez San Agustín, Mar
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    Facing the change beyond COVID-19: continuous curriculum improvement in higher education using learning analytics
    (Edward Elgar, 2022) Hilliger Carrasco, Isabel; Pérez Sanagustin, Mar
    Due to the rapid digitalization of Higher Education, universities and colleges have access to more student data than ever before, allowing for real-time analysis of student behaviour and learning results. To evaluate the quality of curriculum and teaching practices, some institutions have relied on curriculum analytics a subfield of learning analytics aiming to leverage educational data for improving program quality and student learning. So far, some promising tools have been developed to inform curriculum renewal strategies. However, this is still an emerging research area, so little is known about how it supports continuous curriculum improvement in different university settings. More robust design-based research is needed to understand how curriculum analytics helps higher education stakeholders gain better understanding of student outcome attainment. This chapter presents a research agenda that reflects on the importance of promoting continuous curriculum improvement and the research challenges for using curriculum analytics for this purpose.
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    For learners, with learners: Identifying indicators for an academic advising dashboard for students
    (2024) Hilliger Carrasco, Isabel; De Laet, Tinne; Henríquez, Valeria; Guerra, Julio; Ortiz-Rojas, Margarita; Zuñiga, Miguel Ángel; Baier Aranda Jorge Andres; Perez Sanagustin, Maria Del Mar
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    Fostering the use of online learning resources: results of using a mobile collaboration tool based on gamification in a blended course
    (2023) Ramirez-Donoso, Luis; Perez-Sanagustin, Mar; Neyem, Andres; Alario-Hoyos, Carlos; Hilliger Carrasco, Isabel; Rojos, Felipe
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    How Could Be Used Student Comments for Delivering Feedback to Instructors in Higher Education?
    (Springer, 2024) Astudillo Laroze, Gabriel Alejandro; Hilliger Carrasco, Isabel; Baier Aranda, Jorge Andres
    In higher education, open-text comments from Student Evaluations of Teaching (SET) provide valuable insights into instructional strategies. However, processing these comments can be challenging, leading to limited feedback for instructors. This research aims to develop Natural Language Processing (NLP) strategies to transform student comments into actionable feedback. Two research questions guide this study: 1) How can NLP methods diagnose the effectiveness or mismatch of instruction in higher education? and 2) How can these diagnoses inform personalized recommendations for contextually relevant teaching practices? Using cosine similarity between vector representations of student comments and literature-based statements it is diagnosed the presence of effective teaching practices. This diagnosis will inform personalized feedback recommendations. Preliminary work has used Exploratory Factor Analysis was used to analyze latent dimensions in the comment-statement similarity matrix and results suggest that correlations are linked to pedagogically relevant latent variables. This methodology seems to be a valid strategy for diagnosing the effectiveness or mismatch of teaching practices in higher education. Future research directions include exploring text data representations from different theoretical perspectives on education and investigating the impact and implementation of teaching practices suggested by language models compared to those recommended by human agents.
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    Insights in Learners' Behaviour and Early Dropout Detection based on Coursera MOOCs
    (Institute of Electrical and Electronics Engineers Inc., 2021) Frank, Sarah; Gutl, Christian; Perez-Sanagustin, Mar; Hilliger Carrasco, Isabel
    Increased utilization of distance learning makes the creation of effective learning tools ever more important. However, while Massive Open Online Courses (MOOCs) are a popular online learning tool, they often suffer from high user attrition. This paper investigated this effect for 6 different MOOCs with more than 35 thousand users, using AdaBoosted decision trees to create a model which was then used for the prediction of dropouts, as well as the calculation of feature importance scores. The resulting model generally scored high accuracy scores which were plotted for each course, and feature importance scores were especially high for the features encompassing the number of user requests, the user's total active time and the average time between clicks. Furthermore, the paper explored the results of the inclusion of forum data in this setting. While the forum features did not lead to a major increase in model accuracy, there was a statistical difference between the number of forum interactions for those who completed the MOOCs and those who did not, which opens up possibilities for future research into utilization of forum interaction data, and forums in MOOCs in general.
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    Lacking time: A case study of student and faculty perceptions of academic workload in the COVID-19 pandemic
    (2023) Hilliger Carrasco, Isabel; Astudillo, Gabriel; Baier, Jorge
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    Lak23 conference proceedings towards trustworthy learning analytics
    (Association for Computing Machinery, 2023) Marinho, Wemerson; Khosravi, Hassan; Rienties, Bart; Dawson, Shane; Hilliger Carrasco, Isabel
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    Lessons learned from designing a curriculum analytics tool for improving student learning and program quality
    (2022) Hilliger Carrasco, Isabel; Aguirre, Camila; Miranda, Constanza; Celis, Sergio; Perez-Sanagustin, Mar
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    Offering an Entrepreneurship Course to All Engineering Students: Lessons Learned from ING2030 in Puc-Chile
    (American Society for Engineering Education, 2021) Hilliger Carrasco, Isabel; Fleet, Constance; Melian, Constanza; Baier Aranda, Jorge Andrés; Perez Sanagustin, Maria Del Mar
    All rights reserved.Entrepreneurial learning experiences have become one of the key aspects of the state of the art in engineering education. As such, technology-focused entrepreneurship courses have been incorporated to engineering curricula — both in developed and developing countries. Following this trend, the Engineering School at Pontificia Universidad Católica de Chile (PUC-Engineering) designed a third-year compulsory course on research, entrepreneurship, and innovation, whose objective is to provide students with entrepreneurial skills that transcend time. To continuously improve this course, the Engineering Education Unit at PUC-Engineering has been conducting pre- and post-surveys, assessing self-efficacy and learning benefits related to various course methods. This paper describes the main lessons learned as a result of using this data-centric approach throughout the last six academic periods. We found that the course is perceived as beneficial by most of its students, and that project feedback sessions and project presentations report the highest perceived learning benefits. Besides, we describe some of the improvements to the course that have been pushed by assessment data, showing the importance of using a data-driven approach for engineering entrepreneurship education.
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    Redesigning a Cornerstone Course, Lessons Learned from a Pandemic
    (American Society for Engineering Education, 2023) Cortázar Valdés, Catalina; Hilliger Carrasco, Isabel; Astudillo Laroze, Gabriel Alejandro
    This evidence-based paper describes the process of implementing and evaluating a flipped classroom approach, in conjunction with a project-based learning methodology, in a remote Cornerstone Engineering course and how it was kept in the face-to-face return. In the first year, cornerstone engineering courses are taught mainly using project-based learning. This methodology allows students to develop teamwork and communication skills and promotes critical thinking allowing students to solve real-world problems. Traditionally, project-based learning courses are taught face-to-face. Due to COVID-19, educational institutions were forced to move from face-to-face teaching to remote teaching and learning. In this new setting, enhancing online teamwork became a challenge. In order to promote teamwork, a flipped classroom methodology with project-based learning was introduced into a Cornerstone Course during the lockdown in 2020. The flipped classroom is a teaching methodology where students learn the concepts before class meetings. In the classroom, the students apply the concepts learned asynchronously. This methodology allows students to take responsibility for their learning and to interact with their peers during classroom hours. It also allows professors to have a more productive time with students. In 2022, educational institutions returned to face-to-face teaching; this course was no exception. The teaching team maintained the flipped classroom methodology with project-based learning face-to-face. A survey was conducted to understand the students' perceptions concerning this methodology. The survey took place at the middle and end of the semester in conjunction with a small discussion group once the semester finished. The student body values the activities in class, where collaboration and teamwork are encouraged. However, they perceive an additional burden by having to watch videos before class. This article contributes to Engineering Education by providing guidelines for implementing a flipped classroom in a Cornerstone project-based learning (PBL) course.
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    Redesigning engineering education in Chile: How selective institutions respond to an ambitious national reform
    (American Society for Engineering Education, 2016) Celis, Sergio; Hilliger Carrasco, Isabel
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    Self-tracking Time-On-Task: Web-Based Weekly Timesheets for Higher Education Students
    (2021) Hilliger Carrasco, Isabel; Miranda, Constanza; Schuit, Gregory; Perez-Sanagustin, Mar
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    Student Dataset from Tecnologico de Monterrey in Mexico to Predict Dropout in Higher Education
    (2022) Alvarado-Uribe, Joanna; Mejia-Almada, Paola; Masetto Herrera, Ana Luisa; Molontay, Roland; Hilliger Carrasco, Isabel; Hegde, Vinayak; Montemayor Gallegos, Jose Enrique; Ramirez Diaz, Renato Armando; Ceballos, Hector G.