Browsing by Author "Sotomayor, Trinidad "

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    Developing a More Comprehensive Instrument to Assess the Entrepreneurial Mindset of Engineering Students
    (ASEE's Virtual conference, 2020) Miranda Mendoza, Constanza; Goñi, Julian; Berhane, Bruk T.; Sotomayor, Trinidad
    This is a Work in Progress: Goals of becoming more entrepreneurial have placed considerable pressure on institutions of higher education to generate educational programs that are consistent with the entrepreneurial mindset. Surpassing business programs, engineering education has had an exponential growth in entrepreneurship instruction in curricula and publications related to the topic. However, there are still many conceptual and methodological challenges described in recent literature left unresolved by current assessment methods. As an international and interdisciplinary research team, we seek to develop a new survey instrument to assess the entrepreneurial mindset in engineering students. In the next two years, a preliminary quantitative version of the instrument will be applied to an incrementally larger body of Chilean and United States students in order to evaluate its utility across a much larger sample size. Through this research effort and a critical review of the literature, we aim to produce a more comprehensive and situated method for defining and articulating the entrepreneurial mindset for stakeholders in engineering education. Long-term implications for this project include alignment of the entrepreneurial mindset with objectives articulated by the Accreditation Board for Engineering and Technology (ABET)
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    Development and statistical validation of an instrument to assess entrepreneurial behaviors in engineering education
    (2021) Sotomayor, Trinidad; Miranda Mendoza, Constanza; Pontificia Universidad Católica de Chile. Escuela de Ingeniería
    En la última década, la enseñanza del emprendimiento en ingeniería ha crecido exponencialmente en universidades de todo el mundo. Sin embargo, este crecimiento ha ido acompañado de grandes desafíos al diseñar métodos de evaluación teóricamente sólidos y sensibles al contexto. El propósito de esta tesis es diseñar una investigación exploratoria, con fase cualitativa y cuantitativa para construir un instrumento para evaluar la mentalidad emprendedora en el contexto de la educación en ingeniería. En una primera etapa, esta investigación explora críticamente la literatura en educación, negocios e ingeniería para identificar los componentes clave de la mentalidad emprendedora y los comportamientos asociados. El proceso fue seguido por una recopilación de datos cualitativos con estudiantes y profesores para contrastar la información mediante focus groups. En el análisis cualitativo se utilizó la Teoría Fundamentada con el objetivo de crear ítems de manera inductiva a través de la codificación de temas. Con base en estos resultados y la validación de expertos, se desarrolló un instrumento inicial de 27 ítems. Antes de poder utilizar un instrumento cuantitativo, es necesario validarlo. La fase cuantitativa involucró la validación del constructo estadístico y la confiabilidad de la escala, a través del análisis factorial exploratorio (EFA) y el análisis factorial confirmatorio (CFA). El EFA y CFA proporcionaron pruebas sólidas de validez para los indicadores utilizados para evaluar los tres constructos propuestos de la mentalidad empresarial. El resultado general de esta investigación es un instrumento inicial de 15 ítems que podría aplicarse en la educación en emprendimiento en ingeniería. El proceso general podría replicarse en la creación de nuevos instrumentos de evaluación para la educación superior en ingeniería.
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    Effective teaching in computational thinking: A bias-free alternative to the exclusive use of students' evaluations of teaching (SETs)
    (2023) Diaz, Noemi V. Mendoza; Sotomayor, Trinidad
    The tenure system in the United States places significant importance on teaching effectiveness. To date, students' evaluations of teaching (SETs) have been the reigning mechanism for assessing effective teaching. However, prior work has shown that SETs are often biased against underrepresented groups and minorities. The present study analyzes options for effective teaching assessments, which include evaluating final grades and measuring the differences between students' pre- and post-tests (normalized gain) using standard instruments. The content area and the instrument used in this study originated in the computational thinking field, which has a widespread presence in engineering, where minorities are at a disadvantage. This study obtained a total of 88 student participants from four sections of an introductory engineering course at a Southwestern institution. The study utilized a computational thinking diagnostic (CTD) to inform the course teaching approach (the intervention). Results show that (a) normalized learning gains correlated moderately with SETs, (b) final grades correlated strongly with SETs, (c) final grades correlated strongly with normalized learning gains, (d) the educational intervention based on the CTD significantly affected student learning, and (e) SET comments affect evaluations. The implications include the notion that standardized instrument-driven instruction and evaluations can increase the success of minorities on both sides of the classroom. The purpose of this manuscript is to invite the Heliyon readership to get involved in the development of related instruments and to incorporate these measures of learning into their instruction so biases are avoided or minimized.
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    The ethical implications of collecting data in educational settings: discussion on the technology and engineering attitude scale (TEAS) and its psychometric validation for assessing a pre-engineering design program
    (2021) Miranda, Constanza ; Goñi, Julian; Pickenpack, Astrid ; Sotomayor, Trinidad
    K-12 Engineering Education has placed a lot of attention on students' attitudes or predispositions towards science and technology. However, most assessment methods are focused on STEM as a whole or only on technology. In this article, we will discuss the instrument called Technology and Engineering Attitude Scale (TEAS) which focuses on attitudes towards technology. Previous studies and applications of this particular scale lacked proper statistical validation of the instrument. The following research looks at the application of an adapted version of the TEAS to assess a GEDC awarded pre-engineering design program in Chile. This version was psychometrically analyzed in 436 cases to validate the interpretations driven by a particular cultural context and specific to the discipline of engineering. The article focuses on the modifications applied to the instrument after the statistical validity process. The discussion is centered on the ethical importance of adapting an existing scale in a valid and reliable way to assess a pre-engineering design program in a local context. Lessons learned and recommendations for future research in this area are proposed based on this particular experience.
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    Time to Graduate for Latinos/Hispanics in Comparison to Other Diverse Student Groups: A Multi-Institutional/Multilevel MIDFIELD Study
    (2021) Diaz, Noemi V. Mendoza; Sunny, Cijy Elizabeth; Sotomayor, Trinidad; Richard, Jacques
    Higher institutions of education represent the social mobility mechanisms that create more just societies. The STEM fields are particularly critical in the development of these modern, more just societies. In the United States, the social and racial justice debates are ever more relevant and present in academia. Studies focused on under-represented and under-served groups in education, especially STEM fields, are timely and of paramount importance. This is a study that analyzed student data of 19 institutions, concentrated in what is known as the Multiple-Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD). It utilized multilevel (HLM) analysis focused on the Time to Graduate outcome of under-represented populations, emphasizing the Latino/Hispanics group. Multilevel analysis is a powerful tool to evaluate differences in groups such as institutions and races/ethnicities, which is the type of data MIDFIELD affords. Results show that depending on the multilevel model, either fixed or random slope, there is a significant difference between the number of terms taken to graduate for under-represented groups, including Latinos/ Hispanics, compared to White groups and for Black compared to White groups. This suggests that Black students tend to be more impacted by their institution than other racial/ethnical groups. Since the emphasis was Latinos/Hispanics, the question remaining is if these results transfer to a sample with more Latino/Hispanic representation.