Board 145: Possible Relations between Self-Efficacy, Sociodemographic Characteristics, Dropout and Performance of Freshman Students in Engineering Courses

Cristiane Maria Barra Da Matta; Daniel Kashiwamura Scheffer; Susana Marraccini Giampietri Lebrão; Maria do Carmo Fernandes-Martins; Fernando Silveira Madani

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Conference: 2023 ASEE Annual Conference & Exposition
Location: Baltimore , Maryland
Publication Date: June 25, 2023
Start Date: June 25, 2023
End Date: June 28, 2023
Conference Session: Multidisciplinary Engineering Division (MULTI) Poster Session
Tagged Division: Multidisciplinary Engineering Division (MULTI)
Tagged Topic: Diversity
Page Count: 11
DOI: 10.18260/1-2--42475
Permanent URL: https://peer.asee.org/42475
Download Count: 134

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Paper Authors

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Cristiane Maria Barra Da Matta Instituto Mauá de Tecnologia

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Master's degree in Food Engineering at the Instituto Mauá de Tecnologia and PhD in Psychology at the Universidade Metodista de São Paulo (2019). Assistant professor and coordinator of the Student Support Program (since 2007) at Instituto Mauá de Tecnologia. It investigates themes of School and Educational Psychology: academic experiences, self-efficacy, school performance and dropout in higher education.

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Daniel Kashiwamura Scheffer Instituto Mauá de Tecnologia

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I have a bachelor's and master's degree in Statistics from the Instituto de Matemática e Estatística - USP, with experience in the area of probability and statistics with an emphasis on data analysis. I am currently a professor in the Business Administration and Engineering courses at the Instituto Mauá de Tecnologia.

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Susana Marraccini Giampietri Lebrão

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Graduated in Metallurgical Engineering from Mauá Institute of Technology (Brazil) in 1987, Master of Science in Metallurgical Engineering at the Polytechnic School of the University of São Paulo (Brazil) in 1993, a doctoral in Metallurgical Engineering (Dr. Engineer) in 1998, at the same University, and a Postdoc in Psychology from the Methodist University of São Paulo in 2018. Has been a professor and researcher at Mauá Institute of Technology (Brazil) since 1990, from 2020 to 2023 was the Coordinator from Mechanical Engineering Department at the same Institute.

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Maria do Carmo Fernandes-Martins Universidade Metodista de São Paulo

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Psychologist from the University of São Paulo (1977), Master and Doctor in Psychology from the University of Brasília (1984/1999). Researcher and reviewer at the Fundação de Amparo à Pesquisa do Estado de São Paulo - FAPESP. Retired Associate Professor at the Federal University of Uberlândia. Professor at the Methodist University of São Paulo since 2009. Coordinator (2003-2008) of the Postgraduate Program in Psychology at the Federal University of Uberlândia. Coordinator of the Postgraduate Program in Health Psychology at Universidade Metodista de São Paulo (UMESP) from February 2016 to December 2021. Director of research and postgraduate studies at UMESP since April 2022. Founding member of the Brazilian Society of Organizational and Work Psychology (SBPOT) and member of the National Association for Research and Graduate Studies in Psychology (ANPEPP). She has experience in Organizational and Work Psychology and in Health Psychology with a research focus on measures in psychology, job satisfaction, social power bases, resilience at work, intragroup conflicts, organizational climate, well-being at work, self-efficacy and engagement at work and in your relationships.

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Fernando Silveira Madani Instituto Mauá de Tecnologia

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Fernando Silveira Madani received the B.S (1998) in Mechatronics Engineering from the Univ. Paulista – Brazil, the M.S. (2002) and Ph.D. (2010) from the Aeronautical Institute of Technology (ITA) - Brazil. In 2002, he joined the faculty of the Dept. of Mechanical Engineering, Mauá Institute of Technology – Brazil, where he is currently as a full professor and Head of the Mechatronics Engineering program. His main research interests include, robotics, advanced manufacturing systems, embedded systems, and autonomous mobile robots. Since 2014 is an INEP (agency linked to the Ministry of Education) advisor, to promote the evaluation and improvement of undergraduate courses in mechatronics engineering in Brazil.

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Abstract

The beginning of academic life has a significant impact for the student, which can affect both academic performance and dropout. This study aimed to search for relationships between sociodemographic characteristics, dropout, self-efficacy and performance of freshman students in engineering programs, and to test a model to identify school performance predictors, including the five dimensions of self-efficacy in higher education and age. A total of 407 students, mostly male freshmen from a private engineering school located in São Paulo - Brazil, with an average age of 18.5 years old, participated in the study. Sociodemographic Data Questionnaire and Higher Education Self- Efficacy Scale (HESES) were used, including 34 items and five dimensions: Academic Self-efficacy (capacity to learn and apply knowledge), Higher Education Regulation Self-Efficacy (ability to self-regulate one´s actions), Social Interaction Self-efficacy (ability to mantain relationship with classmates and professors), Proactive Self-efficacy (ability to enjoy and promote educational opportunities) Academic Management Self-efficacy (ability to get involved and meet deadlines). The mean of 7.5  1.1 of self-efficacy was considered high. It was observed that there is no significant difference between self-efficacy in participants: daytime and nighttime (p = 0.253), female and male (p = 0.056), and enrolled and dropped out (p = 0.084). However, confidence in the ability to learn and demonstrate it, self-regulate actions and proactivity was somewhat reduced compared to self-efficacy in social interactions and academic management. Multiple linear regression analysis showed that the model is significant (p≤0.001) and explains 37.8% of the variance of yield, the greatest weight in explaining achievement is academic self-efficacy (B = 0.63), academic management self-efficacy (B = 0.38), self-efficacy in training regulation (B = -0.31), self-efficacy in proactive actions (B = -0.23), and age (B = -0.09). It is suggested to promote activities that can nurture students' self-efficacy beliefs, so that they can better take full advantage of the course, with a focus on academic success.

Citation
Format

Matta, C. M. B. D., & Scheffer, D. K., & Lebrão, S. M. G., & Fernandes-Martins, M. D. C., & Madani, F. S. (2023, June), Board 145: Possible Relations between Self-Efficacy, Sociodemographic Characteristics, Dropout and Performance of Freshman Students in Engineering Courses Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--42475

TY  - CPAPER
AB  - The beginning of academic life has a significant impact for the student, which can affect both academic performance and dropout. This study aimed to search for relationships between sociodemographic characteristics, dropout, self-efficacy and performance of freshman students in engineering programs, and to test a model to identify school performance predictors, including the five dimensions of self-efficacy in higher education and age. A total of 407 students, mostly male freshmen from a private engineering school located in São Paulo - Brazil, with an average age of 18.5 years old, participated in the study. Sociodemographic Data Questionnaire and Higher Education Self- Efficacy Scale (HESES) were used, including 34 items and five dimensions: Academic Self-efficacy (capacity to learn and apply knowledge), Higher Education Regulation Self-Efficacy (ability to self-regulate one´s actions), Social Interaction Self-efficacy (ability to mantain relationship with classmates and professors), Proactive Self-efficacy (ability to enjoy and promote educational opportunities) Academic Management Self-efficacy (ability to get involved and meet deadlines). The mean of 7.5  1.1 of self-efficacy was considered high. It was observed that there is no significant difference between self-efficacy in participants: daytime and nighttime (p = 0.253), female and male (p = 0.056), and enrolled and dropped out (p = 0.084). However, confidence in the ability to learn and demonstrate it, self-regulate actions and proactivity was somewhat reduced compared to self-efficacy in social interactions and academic management. Multiple linear regression analysis showed that the model is significant (p≤0.001) and explains 37.8% of the variance of yield, the greatest weight in explaining achievement is academic self-efficacy (B = 0.63), academic management self-efficacy (B = 0.38), self-efficacy in training regulation (B = -0.31), self-efficacy in proactive actions (B = -0.23), and age (B = -0.09). It is suggested to promote activities that can nurture students&#39; self-efficacy beliefs, so that they can better take full advantage of the course, with a focus on academic success.
AU  - Cristiane Maria Barra Da Matta
AU  - Daniel Kashiwamura Scheffer
AU  - Susana Marraccini Giampietri Lebrão
AU  - Maria do Carmo Fernandes-Martins
AU  - Fernando Silveira Madani
CY  - Baltimore , Maryland
DA  - 2023/06/25
PB  - ASEE Conferences
TI  - Board 145: Possible Relations between Self-Efficacy, Sociodemographic Characteristics, Dropout and Performance of Freshman Students in Engineering Courses
UR  - https://peer.asee.org/42475
DO  - 10.18260/1-2--42475
ER  -