Performance Of Engineering Students Research Articles

The Impact of Non-Formal Educational Approach on the Academic Performance and Employability of Engineering and Computer Science Students

Education is no longer a one-time event due to the quick changes in the modern world, the diversity of knowledge it contains, and the ongoing need for personal growth. It turns into a dynamic process that happens all through life. The old curricula and systems of formal education are finding it difficult to keep up with the quick changes occurring in the field of computer science. Non-formal education is a solution to the requirements of the era and can be implemented through seminars, training camps and workshops. It could be additional activities like competitions or extracurricular learning. The aim for this study is to investigate the impact of the non-formal educational approaches on engineering and computer science students’ academic performance as well as their chances to obtain a job after graduation.

An Experiential Learning Approach for Enhancing Performance of First Year Engineering Students in Engineering Graphics Course

Abstract— Engineering Drawing is a crucial and mandatory course for first-year engineering students. This subject plays a vital role in enhancing students' ability to visualize, imagine, and effectively illustrate concepts. It aids them in expressing their ideas clearly and swiftly, comprehending drawings produced by others, and devising effective designs. The curriculum covers essential topics like projection, sectioning, and the development of solids such as prism, pyramid, cylinder, cone, cube, and tetrahedron. These topics help students develop the ability to conceptualize, visualize, and create drawings according to specific requirements. The achievement of learning outcomes related to these subjects is hindered by the challenges faced by first-year engineering students, including their lack of fundamental knowledge in technical drawing and limited abilities in imagination and visualization. As a result, their performance in these areas tends to be subpar. To address this issue, a practical "learning by doing" approach is introduced alongside traditional classroom instruction. This strategy aims to boost the visualization, imagination, and technical drawing proficiency of first-year engineering students. This article outlines the author's endeavors to enhance students' visualization, imagination, and drawing skills. The focus is on involving students actively in both classroom and extracurricular learning. By methodically incorporating a "learning by doing" approach, there has been a notable enhancement in student engagement, achievement of course objectives, and overall performance in the course assessments. The topic of development of solids was completely taught with this method. This activity resulted increase in the CO attainment, active participation and engagement of the students in the class room as well as outside of the classroom. Following the implementation of this activity, there was a substantial rise of 17.30% in the accomplishment of course outcome, coupled with a notable increase of 25.34% in the students' learning index. Keywords— Course Learning Outcome, Engineering Graphics, learning by doing

Influence of Self-Regulated Learning on the Academic Performance of Engineering Students in a Blended-Learning Environment

The pandemic environment experienced for more than two years strongly accelerated the use of technological resources to support learning. Using these resources made it evident that higher education students expecting to succeed academically must master digital strategies. The combination of learning experiences and autonomous work required students to selfregulate their learning well to attain the expected performance levels for competitive work that characterizes the engineering profession. So, we designed an exploratory study to evaluate the effect of self-regulated learning on mechanical design students in a Blended Learning (BL) environment using Flipped Learning/Classroom didactics (FPC). Fifty-one students studying under two different educational-model curricula participated. The research employed a mixed methodology. For the quantitative part, the students’ academic grades and results of the Motivation and Learning Strategies Questionnaire (MSLQ SF) applied in its short Spanish version were employed. A questionnaire for self-study management and a competency observation rubric based on the Marzano & Kendall New Taxonomy were used for the qualitative part. The results showed that the students with the best levels of self-regulated learning in BL and FPC contexts obtained the best results in cognitive, organizational, and motivational resource management strategies. They also improved their disciplinary skills and had a higher academic performance.

Effects of Gender and Military Leave on the Academic Performance of Undergraduate Engineering Students

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Contribution:</i> This article examines how military leaves of absence affect the academic performance of engineering students compared to those who did not take a military leave of absence or took only a general break. Gender-related differences were also analyzed since only male students take a military break. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <i>Background:</i> Recognizing the effects of military breaks can help students make informed decisions and, in turn, enhance their academic performance. Consequently, it can help students make data-based decisions about when taking a military break would be least disruptive or, perhaps, even beneficial to their academic careers. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <i>Research Questions:</i> How does taking a long-term academic break to complete military service in the middle of one’s undergraduate education impact the student’s performance? Does the gender of students affect their academic performance? <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <i>Methodology:</i> This research was conducted at the Korea University of Technology and Education (KOREATECH) with data from 1039 undergraduate students in the School of Electrical, Electronics, and Communication Engineering. The students were admitted between 1994 and 2013 and graduated before 2018. The Shapiro–Wilk test, along with the Kolmogorov–Smirnov test, assessed the normality of the distribution of the data. In addition, analysis of variances (ANOVA) and the Kruskal–Wallis tests were implemented for hypothesis testing. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <i>Findings:</i> The research findings demonstrate that contrary to the assumption that having a break might be detrimental to academic success, returning to school after a military leave of absence positively affected students’ grade point averages (GPAs). Moreover, students with lower grades significantly increased their GPAs after returning to school from conscription.

Predicting academic performance in first-year engineering students: The role of stress, resiliency, student engagement, and growth mindset

The first-year post-secondary experience of engineering students poses an interesting area of inquiry due to the challenges and experiences associated with the transition into a professional degree program. This study aimed to investigate if four psychological variables (perceived stress, student engagement, resilience, and growth mindset) predicted first-year engineering student performance via end-of-first-year grade point average (GPA). An optional online research survey was administered through a mental health and professional skills initiative of the engineering department to undergraduate first-year engineering students. Perceived stress was found to be a significant predictor of GPA. Post-hoc moderation analyses revealed that the relationship between stress and GPA was buffered by resilience (i.e., weaker stress-GPA relationship at higher levels of resilience) and enhanced by student engagement (i.e., stronger stress-GPA relationship at higher levels of engagement). Implications for the importance of resiliency initiatives are discussed, including embedding resiliency skill development within curriculum.

Enhancing concrete structures education: Impact of virtual reality on motivation, performance and usability for undergraduate engineering students

AbstractBackground StudyThe research discusses the need for a paradigm shift in engineering education current practices to accommodate the digital native students. The paper emphasizes the importance of integrating disruptive technologies, namely Virtual Reality (VR) through Head Mounted Displays VR (HMD VR) and Desktop Based VR (DB VR) and comparing it with the traditional teaching methods. The research focuses on second‐year undergraduate students enrolled in a concrete structures course.ObjectivesThe objective of the study is to analyse the impact of DB VR and HMD VR on students' motivation, performance and workload in comparison with traditional 2D drawings. The study also aims to investigate how simulation sickness and system usability could impact students' motivation and performance when interpreting concrete structures.MethodsThe study divided second‐year civil engineering students into three groups, 2D, DB VR and HMD VR. The performance and motivation levels of students were assessed based on the number of mistakes identified and an intrinsic motivation survey. Furthermore, data on system usability and simulation sickness were collected. Spearman rank correlation was conducted to analyse the relationships between the variables tested.ResultsThe results have shown that students' motivation and performance were much higher when using VR in general and HMD VR specifically, students' efficiency and accuracy were also observed. On the other hand, usability was found to be moderately correlated with motivation, with students rating HMD VR as the most usable approach. A moderate inverse correlation was observed between simulation sickness and motivation, indicating that higher simulation sickness led to lower motivation levels.ConclusionThe study concludes that integrating VR in general, DB VR, or HMD VR into a concrete structures course for undergraduate students can significantly improve students' performance and motivation. Furthermore, enhancing usability of any of the methods used can also improve the performance and motivation. On the other hand, simulation sickness inversely affects motivation and performance, therefore, VR developers and educators should not neglect it.

GPT AI Chat: Revolutionizing Education for Civil Engineering Student Performance

This literature review investigates the influence of Chat GPT AI on the effectiveness of the civil engineering curriculum and student performance. The study explores the use of Chat GPT AI in education and emphasizes the significance of rubric assessment in evaluating student achievements. The findings reveal that incorporating Chat GPT AI can significantly enhance the learning process by providing prompt and accurate responses to students' queries. However, the study emphasizes the continued importance of human interaction in the assessment process, as rubric assessment remains crucial for evaluating student performance and fostering motivation for better outcomes. The implications underscore the need to align the curriculum with industry standards and leverage technology to enrich the learning experience. These findings hold potential for educators and policymakers seeking to enhance educational quality and produce highly qualified civil engineering graduates.&#x0D; Highlights:&#x0D; &#x0D; Chat GPT AI: Improving Efficiency - The study explores the impact of Chat GPT AI in civil engineering education, highlighting its potential to enhance the efficiency of the learning process by providing quick and accurate answers to students' questions.&#x0D; Importance of Rubric Assessment - The research emphasizes the crucial role of rubric assessment in measuring student performance and motivating them to achieve better results, highlighting its significance alongside the integration of technology.&#x0D; Adapting Curriculum and Utilizing Technology - The study highlights the importance of adapting the curriculum to meet industry needs and standards, while also leveraging technology, such as Chat GPT AI, to enhance the learning experience and improve the quality of civil engineering education.&#x0D; &#x0D; Keywords: Chat GPT AI, civil engineering education, curriculum efficiency, student performance, rubric assessment.&#x0D;

Attitudes and Academic Performance of Engineering Students in both Prerequisite Courses to Final Year Project and Final Year Project

The aim of this study was to examine the attitudes of engineering students and their academic performance towards both prerequisite courses for and the final year project (FYP), given the need to increase our understanding of attitudes and performance in the context of engineering students, currently underexplored. Questionnaire surveys of 714 eligible students enrolled in the FYP across six engineering programs were conducted. The results show that students enrolled in Industrial, Mechanical and Civil engineering programs, have a negative attitude towards the FYP and its prerequisites, while students enrolled in Electrical, Electronic and Industrial Design and Technology programs have a positive attitude. A statistically strong positive correlation between project prerequisites and engineering FYP was found, confirmed by factor analysis. Majority of students struggle with project progress as compared to other stages of the FYP, due to inadequacy in fundamentals such as design. This study contributes to an understanding of existing knowledge by providing empirical evidence of not only challenges faced by engineering students (as opposed to other disciplines that have been widely covered) but also remedies to improve students’ academic performance. The findings also have implications on engineering education, in relation to informing policy decisions on engineering program structure.

Examination of Study Skills, Emotions, Engagement, and Academic Performance of Mechanical Engineering Students of CIT-University Taking Online Courses: Bases for Student and Faculty Development Program

Amidst the disruptive backdrop of the pandemic, faculty members are required to exhibit heightened awareness and adaptability in response to the challenges posed by the evolving academic landscape. Concurrently, students are tasked with cultivating resilience to effectively navigate their educational pursuits. To bolster the capacities of both faculty and students, a comprehensive exploration of various factors becomes imperative to grasp the intricacies of academic performance within the framework of online distance learning for undergraduate mechanical engineering courses. Scholarly literature suggests that academic performance is influenced by study skills, emotional well-being, and levels of engagement. By employing the revised Online Student Engagement Scale survey, data gathered from 243 students underwent meticulous analysis through Spearman rank-order correlation. This scrutiny unveiled a robust and affirmative correlation between students' study skills, emotional states, engagement levels, and academic accomplishments. Significantly, among these factors, student engagement emerged as the most influential predictor of elevated academic achievement. The research outcomes culminate in the formulation of a strategic intervention strategy. This strategy aims to augment the adeptness of both educators and learners in effectively navigating the realm of online learning. In conclusion, the upheaval caused by the pandemic underscores the urgency for faculty and students to adapt. Through an in-depth investigation, this study underscores the pivotal role of student engagement, alongside study skills and emotional well-being, in determining academic success. These insights guide the formulation of a targeted plan of action, poised to enhance the competence of both stakeholders in embracing the demands of online education.

Academic performance of computer engineering students on the K-12 implementation

Academic performance of computer engineering students on the K-12 implementation

Analysis of the Academic Performance of Mechanical-Electrical Engineering Students during the COVID-19 Pandemic: A Case Study in a Private University in Peru

The COVID-19 pandemic, brought with a number of problems in different sectors, one of the most affected was the education sector, especially in engineering programs, since these have a practical nature and need laboratories to consolidate meaningful learning. In many cases, the virtualization generated some anomalous behavior in the academic indicators that could be used for the analysis of the successes and errors that could lay the foundations for a modern education in engineering careers. The main objective of this research is to analyze the average academic performance per course of a mechanical-electrical engineering program, for which some data was taken from 2018 to 2021. To explain the behavior of the curves, a qualitative survey was applied to 357 students. Three academic indicators are used in the study: grades average, “not pass” rate, desertion rate. The results of the analysis showed that in the first period of the year 2020 (starting period of confinement) they presented very different parameters from those already known in previous years, which could be based on three main causes. The first was due to the full-time dedication of the students to carry out their academic activities, the second is based on the proper technology, resources and strategies adopted by the university and finally, the economic aid from the Peruvian government.

The Effects of Blended Learning on the Performance of Engineering Students in Mathematical Modeling

This paper presents the implementation of an active learning methodology known as blended learning in an ordinary differential equations (ODE) course for engineering students. Our purpose was to evaluate the effect of b-learning on students’ mathematical modeling performance. To this end, synchronous and asynchronous activities were made available to the students as face-to-face and remote learning sessions, in which the experience acquired by students during the sanitary isolation due to COVID-19 was crucial. Benjamin Bloom’s cognitive domain taxonomy was used to design the present didactic proposal. Results show that the students moved upward from the lower knowledge and understanding taxonomical levels, to the upper analysis and application levels, as they learned systems modeling using ODEs.

Influence of mathematics on the academic performance of mechanical engineering students: a PLS-SEM approach

Influence of mathematics on the academic performance of mechanical engineering students: a PLS-SEM approach

Influence of institutional factors on the civil engineering student performance in Brazil

ABSTRACT The reasons why Brazilian civil engineering education has not achieved competitive performance worldwide remain unclear. Thus, this study aims to identify what factors influence student performance in civil engineering undergraduate programs in public institutions in Brazil. Multiple linear regression methods were used to analyse the interactions between the student performance (dependent variable) and the professors’ and universities’ attributes (predictors). The analysis shows that the professor’s qualification and didactics are significant attributes, as are the time of the program’s existence, the academic organisation (if it is annual or semester courses), and the institutions’ administrative jurisdiction. The discussion presented possible explanations for each attribute’s contribution. The study adds to the theory of predicting student performance in a developing country scenario, in this case, Latin America, where engineering education has less investments in academic infrastructure and human capital.

Examining Multiple Intelligences and Performance of Science, Technology, Engineering, and Mathematics (STEM) Students in the Specialized Subjects

This study generally examined the multiple intelligences of the Senior high school (SHS) students under the Science, Technology, Engineering, and Mathematics (STEM) strand and their performance in the specialized subjects. Descriptive and comparative research designs were utilized to measure the variation among the identified study variables. It involved 193 STEM students (composed of 94 males and 99 females) who were selected using complete enumeration sampling. Secondary data on students' performance in the specialized subjects and an adopted Multiple Intelligence Inventory survey questionnaire were employed to collect the data. The T-test for two independent samples was likewise used to examine the significant difference between the performance in the specialized subjects of students with STEM strand as their preferred choice and those who do not prefer STEM. Based on the results, interpersonal intelligence was shown to be the most dominant intelligence type among STEM students, whereas logical intelligence was determined to be the least dominant. On the specialized subjects’ performance, the students demonstrated very good to superior performance in pre-calculus, general biology, and basic calculus subjects. Meanwhile, the study indicated no significant difference in the specialized subjects’ performance between students with STEM strand as their preferred choice and those who do not prefer STEM. Career guidance orientation for students must be reinforced so that they can be advised on what career track or stand to take in senior high school. Future related studies are suggested to further substantiate the results.

Academic Performance before and during the State of Emergency due to Covid-19: Analysis from the Perspective of Distance Education

Faced with Covid-19, and the need to adapt to environments that guarantee continuity of educational service in the context of social distancing, many universities did not initially plan the mechanisms for adapting to the virtual modality adequately. Therefore, this period of transition to e-learning was characterised by a decrease in academic performance . This article reports on a study that focused on determining whether the transition from a classroom to a virtual teaching–learning model had an effect or influence on the academic performance of university students in mechanical and electrical engineering at a public university in Peru during the period 2018 to 2021. The purpose of the study was to ensure the quality of the education system in the face of the implementation of a hybrid mode of teaching. Methodologically, a descriptive type of investigation and longitudinal non-experimental design were undertaken. The research methodology followed a hypothetical-deductive approach. The number of participants was 157 and a registration form was used to collect data on the indicators that made up the academic performance variable. The results reveal that the switch to a virtual teaching–learning modality significantly influenced the academic performance of the students. Student’s t-test found a significance equal to 0.000. Passing grades were achieved by 98.57% of students under the virtual teaching–learning modality, compared to 68.4% under classroom learning.

Comparing Engineering Student and Practitioner Performance on the Strength of Materials Concept Inventory: Results and Implications

Comparing Engineering Student and Practitioner Performance on the Strength of Materials Concept Inventory: Results and Implications

Civil Engineering Student Performance Observation During COVID-19 Pandemic Period

The coronavirus disease 2019 (COVID-19) pandemic shifted the learning method from conventional face-to-face to online. Such abrupt changes provide insufficient time for students to adapt and hence affect their academic performance. Situation seems to be critical towards engineering education, as it at most applicable to blended learning mode, with limited application of fully online mode. The objectives of this study are to compare students’ academic performance with different delivery methods and identify potential learning-related issues in civil engineering material subject during the COVID-19 pandemic period. Three batches of students in the academic year of 2019, 2020 and 2021, are the targeted population, with the delivery modes of conventional face-to-face mode, mixed mode and fully online mode respectively. All three batches of students were undergoing similar assessments of a fundamental subject, Civil Engineering Materials, in Curtin University Malaysia. The findings revealed that students with fully online mode were not performing well in their assessments, notably final examination. There seems to have a lack of peer assistance and non-adaptability in the online mode. Recommendations such as effective online model and collaborative activities have been included to cope for studies during the pandemic. As it is unpredictable for the evolvement of COVID-19 pandemic, this study suggests future research to look into ways of strengthening online teaching tools in engineering degree programmes.

Grade Prediction Modeling in Hybrid Learning Environments for Sustainable Engineering Education

Since mid-March 2020, due to the COVID-19 pandemic, higher education has been facing a very uncertain situation, despite the hasty implementation of information and communication technologies for distance and online learning. Hybrid learning, i.e., the mixing of distance and face-to-face learning, seems to be the rule in most universities today. In order to build a post-COVID-19 university education, i.e., one that is increasingly digital and sustainable, it is essential to learn from these years of health crisis. In this context, this paper aims to identify and quantify the main factors affecting mechanical engineering student performance in order to build a generalized linear autoregressive (GLAR) model. This model, which is distinguished by its simplicity and ease of implementation, is responsible for predicting student grades in online learning situations in hybrid environments. The thirty or so variables identified by a previously tested model in 2020–2021, in which distance learning was the exclusive mode of learning, were evaluated in blended learning spaces. Given the low predictive power of the original model, about ten new factors, specific to blended learning, were then identified and tested. The refined version of the GLAR model predicts student grades to within ±1 with a success rate of 63.70%, making it 28.08% more accurate than the model originally created in 2020–2021. Special attention was also given to students whose grade predictions were underestimated and who failed. The methodology presented is applicable to all aspects of the academic process, including students, instructors, and decisionmakers.

A Comparison Study of Students Performance for Vector Calculus Subject

The research objective was to compare the performance of Engineering students in a pretest and post-test of Vector Calculus subject between programmes during their first year of study at the Faculty of Engineering and Built Environment (FKAB), Universiti Kebangsaan Malaysia (UKM). This paper also aims to investigate the student's knowledge in Vector Calculus, particularly in main topics including partial derivatives, vector functions, line integrals, double integrals, triple integrals, Green's Theorem, Stokes' theorem, Gauss' theorem, and basic differentiation and integration of complex functions. Each topic is included in Course learning outcomes to analyze either the students show a good or bad performance for Vector calculus subject. 412 first year engineering students from different programmes JKAS, JKMB, JKKP and JKEES were needed to seat for pretest and post-test (Test 1, 2 and 3). The pretest was performed in early of the semester, while the post-test was held afterwards. The analysis results revealed that the performance of students in the post-test was outstanding to their pretest performance. Data analysis of student performance indicated that most students did not seem to understand the basic ideas in each chapter prior to the beginning of the semester.