First-year Engineering Research Articles

Assessing Learning in Mathematical Sensemaking Electromagnetism Instructions among Rwanda Polytechnic Students at Huye College

In the realm of electromagnetic (EM) courses in engineering, many studies have reported students’ learning difficulties related to mathematical frameworks representing physical phenomena. Students’ learning engagement and learning gains are not satisfying. The present study assessed first-year engineering students’ behavioural engagement and perceived learning gains in mathematical sensemaking electromagnetism instructions at RP-Huye College. Within a single-case research design, a six-weeks intervention incorporating mathematical sensemaking instructions, supported by physical experimentation and computer simulations, was implemented to 61 first-year engineering students who were enrolled in the department of electrical and electronics engineering. All enrolled students were purposively recruited to participate because this target population was less than 100. Data were collected through classroom observations, which used the behavioural engagement related to instruction (BERI) and a post-topic evaluation, which used a semi-structured questionnaire. Data analysis involved the use of graphs, descriptive statistics and inductive thematic analysis. Findings revealed that students were mostly engaged during mathematical sensemaking by hands-on and simulation-based activities, particularly in topics related to electromagnets, where engagement levels peaked at 7.5 in average. Conversely, lecture-based tasks, especially on magnetic forces and electromagnetic induction, recorded the lowest engagement at 6.2 in average. The post-topic assessment on perceived learning gains showed that students had highly positive perceptions on their learning experiences (M=4.82, SD=0.48) and recognized the significance of EM in engineering (M=4.85, SD=0.38). These numerical results were complemented by students’ narrations, which indicated that they gained particular attention about specific EM formulas and how they can apply them in engineering. However, the present study also noted that further refinement in instructional design, particularly by incorporating specific dimensions of mathematical sensemaking, could optimize learning outcomes for EM courses in engineering. Additionally, formal assessments of students’ mastery and experimental studies can benefit future work.

Bridging Between High School and University: Assessment of Students’ Readiness to First-Year Engineering Programs

This descriptive case study uses self-assessment tools to explore 26 prospective students’ preparedness regarding their knowledge and competencies for entering the first year of engineering programs at a large, research-intensive Canadian university. We aim to provide insight for developing the Brigde2Engg (B2E) Program to empower and support students in their transition to university. Applying Conley’s college readiness model as a theoretical framework, findings from this study reveal that most students appear confident about their knowledge and skill preparedness for the first-year engineering programs, including their critical thinking abilities, problem-solving skills, and understanding of engineering professions. However, they are less confident in physics and the use of engineering tools. Therefore, we suggest that, when they choose to participate in the bridging program, these students should focus mainly on the subject they deem inadequate. Results also show that an introduction to engineering tools is essential to familiarize students with the programming and spreadsheet software they will use throughout their university programs.

First-year engineering student persistence amidst COVID-19 interruptions: evidence from two diverse institutions in the United States

First-year engineering student persistence amidst COVID-19 interruptions: evidence from two diverse institutions in the United States

Systematic integration of a rubric in first-year engineering calculus courses

ABSTRACT For many first-year engineering students, their first calculus or pre-calculus courses can be a substantial barrier for initial success and persistence to subsequent engineering courses. One approach that may mitigate this challenge for some students is to support their development as stronger metacognitive learners – learning how to self-evaluate and improve based on informed feedback. A structured mathematical problem-solving rubric designed to offer feedback on how to develop and communicate mathematical solutions to engineering problems can be a helpful tool to support metacognitive development. After a semester of careful and systematic instruction, practice, and use of such a rubric in engineering calculus courses, we found significant improvement in pre-calculus students' metacognitive awareness. A median split analysis showed that for both calculus and pre-calculus courses, the lower metacognitive half of each class improved significantly in their metacognitive abilities, as was the intent for the rubric. Students reported an overwhelmingly positive perception of the value of the rubric for their own learning, and the subset of calculus I students who improved in their sophistication of rubric use had significantly higher (12.5%) final exam scores compared to those who did not improve.

Not Liking the Likert? A Rasch Analysis of Forced-choice Format and Usefulness in Survey Design

We have less time and focus than ever before, while the demand for attention is increasing. Therefore, it is no surprise that when answering questionnaires, we often choose to strongly agree or be neutral, producing problematic and unusable data. The current study investigated forced-choice (ipsative) format compared to the same questions on a Likert-type as a viable alternative. An established motivation questionnaire was administered in two versions, forced-choice and Likert-type, to 1088 first-year engineering students. Descriptive, non-parametric statistics and Rasch measurement models were applied to assess usefulness, validity and reliability. Results: The ipsative version had a higher response rate, less missing data, and the motivations emerged more clearly. Evidence for the reliability and validity of the forced-choice version was excellent. The forced-choice format is recommended as an alternative to the Likert types when collecting human or social survey data.

온라인 동영상 수업 후 서술형 평가상의 쓰기에서 나타나는 오류 분석: 공과대학 1학년 기초미적분학 강좌를 중심으로

Objectives This study attempted to qualitatively examine the errors that appear in the descriptive type assessment after online video classes. Methods For this purpose, we qualitatively analyzed the errors appearing in 5 descriptive type questions in the mid-term and final exams for first-year engineering students at a local college. They are taking basic precalculus in the first semester of 2022. The 5 questions were divided into drawing a graph(3 questions) and descriptive type writing(2 questions), and the types of errors that emerged as a result are as follows. Results First, in the drawing a graph questions, there were errors in conceptual errors, errors regarding the domain, asymptote notation errors, coordinate notation errors, writing explanation errors, omitting convexity mentions, omitting inflection points mentions, and errors of omitting algebraic expressions for determining graph shape). Second, in the descriptive type writing questions, errors in problem recognition, incorrect use of problem conditions, substitution errors, rationalization errors, technical errors, omission of the solution process, logically inappropriate reasoning, and errors due to mistakes or carelessness appeared. Conclusions In addition, as a result of a detailed analysis according to the type of error shown in each question, it was emerged that college students also had errors similar to those made by high school students in drawing graphs and solving descriptive type problems.

Identifying what social emotional support first-year engineering students need to overcome setbacks in lab settings: a case study

ABSTRACT Engineering has high attrition rates in the United States, especially in underrepresented subpopulations in the first year of undergraduate study. An important component of combatting attrition is better understanding what social emotional supports are needed to retain students. In this case study, five first-year engineering students were interviewed across three semi-structured sessions. Transcripts were thematically analysed using the framework developed by the Collaborative for Academic, Social, and Emotional Learning (CASEL) to identify what social emotional learning (SEL) skills and forms of support are needed to overcome setbacks. Students shared that applying emotion regulation skills to manage frustration and relying on relationship skills to ask for help facilitated overcoming setbacks. Analysing the skills described and the desired supports students expressed within the context of the SEL framework provides a way to categorise and discuss how instructors can practically support their undergraduate engineering students in the classroom to better retain them.

Academic and Social Adjustment to Post-Pandemic Hybrid Learning: A Phenomenological Study of Filipino First-Year Engineering Students’ Experiences

Academic and Social Adjustment to Post-Pandemic Hybrid Learning: A Phenomenological Study of Filipino First-Year Engineering Students’ Experiences

Bridging Learning and International Practice for Enhancing Physics Education

This paper discusses the implementation and outcomes of an Erasmus+ Blended Intensive Program (BIP) focused on physics education. The program aimed to address the challenges faced by first-year engineering students in mastering physics through a combination of online and face-to-face phases. Participants included students and faculty from three European universities: the Hungarian University of Agriculture and Life Sciences (MATE), the Universitat Politècnica de València (UPV), and the Slovak University of Agriculture in Nitra (SUA). A survey was proposed to students to obtain information that would benefit future programs. Survey results revealed significant improvements in students’ social skills and a high level of satisfaction with the program’s organization and methodology. However, areas for improvement were identified, particularly in administrative processes. The study highlights the importance of international cooperation and collaboration frameworks to ensure the program’s effectiveness across diverse educational systems. Overall, the BIP provided a valuable educational experience that enhanced students’ theoretical knowledge, practical skills, and interpersonal abilities, demonstrating the benefits of integrating innovative teaching methods in higher education.

A tutorial for integrating generative AI in mixed methods data analysis

The current article used real data to demonstrate the analysis and synthesis of Mixed Methods Research (MMR) data with generative Artificial Intelligence (Gen AI). I explore how reliable and valid Gen AI data outputs are and how to improve their use. The current content is geared towards enhancing methodological application regardless of field or discipline and includes access to a prompt library and examples of using outputs. The demonstration data used emanated from a study done in South Africa, with a quantitative sample size of 969 first-year engineering students and, for the qualitative part, 14 first-year students. In the current article, I compare my original analysis to ChatGPT results. Generative AI as a mind tool is best used with human insight, and I found this to be especially true when coding qualitative data. ChatGPT produced generic codes if asked to do inductive coding, and the results improved when training the Gen AI on human examples, which led to moderate and significant correlations between human and machine coding. The quantitative analysis was accurate for the descriptive statistics, but the researcher had to use best judgment to select the correct inferential analysis. Quantitative and qualitative analysis should be conducted separately in generative AI before asking the Chatbot for help with mixed methods results. In the current paper, I give guidelines and a tutorial on how to use chatbots in an ethically responsible and scientifically sound manner for research in social and human sciences.

Exploring first-year engineering student perceptions of peer-led study groups in a Global South context

Exploring first-year engineering student perceptions of peer-led study groups in a Global South context

Enhancing Engineering students’ Self-directed learning of Communication Skills

Research shows that perceived teacher and peer support are essential to self-directed learning. Previous research has also examined the function of self-directed learning of Communication skills among Engineering undergraduates. Yet, there is a paucity of research into the influence of perceived teacher support and peer support in facilitating self-directed learning for the effective development of Communication skills. Thus, this study evaluated the effects of perceived teacher support and peer support on self-directed learning of Communication skills among Engineering students at technical universities in Ghana. This is a quantitative study with a cross-sectional survey design. A simple random sampling technique was employed to choose six technical universities, while a stratified random sampling technique was used to draw the sample sizes from each institution. Data were gathered from 1,189 first-year Engineering students. Multiple regression was used in analysing the data. The results revealed positive effects of teacher support and peer support on self-directed learning. Notwithstanding, the effect of teacher support was much stronger, indicating that teacher support best determines self-directed learning. Thus, it is imperative for teachers to discern the specific teacher activities that elicit favourable perceptions from students, in order to actively improve and refine these activities.

Prior knowledge of a calculus course: The impact of prior knowledge on students’ errors

We conducted a descriptive study among first-year engineering students at the Anton de Kom University of Suriname. We analyzed students’ errors regarding necessary prior knowledge in a calculus A exam. We found that the stage of the solution in which prior knowledge is required impacts the importance of prior knowledge. We also found that many errors concerned basic algebra and trigonometry concepts and skills. We concluded that even though the required prior knowledge concerns basic algebra and trigonometry, the stage of the solution in which prior knowledge is needed is of great importance.

Technology Integration in Engineering Education: Assessing Google Classroom's Effectiveness in Communication Skills Courses

This study delves into the effectiveness of Google Classroom in enhancing academic performance among first-year engineering students in a communication skills course. Rooted in the Technological Pedagogical Content Knowledge (TPACK) model and the Diffusion of Innovations theory, the research tests two hypotheses regarding the impacts of technology use and the instructor factor on student outcomes. With a sample of 356 students, the analysis employs t-tests and regression analysis to compare performance between students using Google Classroom and traditional teaching methods. The results reveal no significant difference in performance between the two groups, suggesting that integrating Google Classroom does not inherently enhance academic outcomes. However, marginal effects of instructor involvement were observed, underscoring the intricate interplay of human and technological factors in educational settings. The implications of these findings are significant, as they provide a nuanced understanding of the role of technology in education and the importance of effective instructor engagement. Future research should examine technology's role across diverse disciplines and the dynamics of instructor-student interactions within technology-enhanced environments.

Comparing First-Year Engineering Student Conceptions of Ethical Decision-Making to Performance on Standardized Assessments of Ethical Reasoning

The Defining Issues Test 2 (DIT-2) and Engineering Ethical Reasoning Instrument (EERI) are designed to measure ethical reasoning of general (DIT-2) and engineering-student (EERI) populations. These tools—and the DIT-2 especially—have gained wide usage for assessing the ethical reasoning of undergraduate students. This paper reports on a research study in which the ethical reasoning of first-year undergraduate engineering students at multiple universities was assessed with both of these tools. In addition to these two instruments, students were also asked to create personal concept maps of the phrase “ethical decision-making.” It was hypothesized that students whose instrument scores reflected more postconventional levels of moral development and more sophisticated ethical reasoning skills would likewise have richer, more detailed concept maps of ethical decision-making, reflecting their deeper levels of understanding of this topic and the complex of related concepts. In fact, there was no significant correlation between the instrument scores and concept map scoring, suggesting that the way first-year students conceptualize ethical decision making does not predict the way they behave when performing scenario-based ethical reasoning (perhaps more situated). This disparity indicates a need to more precisely quantify engineering ethical reasoning and decision making, if we wish to inform assessment outcomes using the results of such quantitative analyses.

Engineering students’ perceptions of problem and project-based learning (PBL) in an online learning environment

ABSTRACT Modern engineering curricula often rely on approaches such as problem and project-based learning (PBL) as a core teaching and learning strategy. With a growing need to move these student-centred active learning curricula to online and blended learning environments, it is essential that practitioners understand the impact that these different modes of delivery may have on student collaboration. This paper aims to identify factors that affect students’ perceptions of PBL in an online learning environment. This case study was carried out in an Irish university over a seven-week period with first-year engineering students during the COVID-19 pandemic. The study utilised a questionnaire (n = 94) and semi-structured interviews (n = 7) to collect participant data. Qualitative data were analysed using Braun and Clark’s thematic analysis. The analysis identified 6 themes and 18 sub-themes that are linked to students’ perceptions of problem and project-based learning (PBL) in an online environment. The identified themes and sub-themes in this study are uniquely reported findings within the context of online PBL in engineering education.

A framework for integrating additive manufacturing into engineering education: perspectives of students and educators

ABSTRACT Additive manufacturing (AM) and 3D printing (3DP) offer unique opportunities for experiential learning and practical application in engineering education. In developed countries, AM is integrated into engineering education to train mechanical engineers. However, existing research has not investigated the integration of AM and 3DP into higher education in developing countries. Semi-structured interviews were conducted with students and educators from mechanical engineering programmes in Vietnam to examine AM usage in engineering education. Our study revealed that no curricula or policies to integrate AM into classrooms exist in the participating institutions. Engineering schools are attempting to introduce 3DP to students through short courses, but educators have inadequate training. The lack of consistent communication among institutions has hindered the growth of 3DP education. Therefore, to meet the standards of Industry 4.0, it is crucial to have policies and funding in place to promote AM growth among first-year engineering students.

Emotional Intelligence of Russia’s Potential Scientific and Technical Elite

A highly intellectual environment involves intense mental activity, rapid acquisition of new material, creativity, competition, and rivalry. All these aspects may cause a long-time neuropsychic stress. Students of leading technical universities need to be able to overcome such difficult situations. The authors reviewed theoretical approaches to emotional intelligence. They designed a psychological model of scientific and technical elite of modern Russia. The model included emotional-volitional, demand-motivational, value-meaning, socio-psychological, and cognitive-activity components. This paper focuses on the empirical study and confirmation of the emotionalvolitional component in potential engineering, scientific, and technical elite, i.e., junior students of Russia’s leading technical universities. The research revealed some psycho-logical peculiarities in their emotional intelligence and coping-strategies. The sample consisted of first-year engineering and technical students of the National Research Nuclear University MEPHI (n = 111). The psychodiagnostic tools included the coping test developed by R. Lazarus and S. Folkman and adapted by T. L. Kryukova, E. V. Kuftyak, and M. S. Zamyshlyaeva; D. V. Lyusin’s test of emotional intelligence. The data analysis relied on IBM SPSS Statistics V.22.0 and the Kruskal-Wallis H-test method of mathematical statistics. The students proved able to consciously analyze difficult situations, work out solutions, plan and predict the outcomes of their behavior, as well as to resort to past experience and available resources. In general, these overcoming models had a constructive effect on the development of an engineer’s personality. However, the underdevelopment of the emotional sphere and poor expression of feelings affected interpersonal and intragroup relationships. Students of nuclear engineering should develop their emotional sphere and expand the range of coping strategies in stressful situations.

First-year engineering students’ attitudes and learning goals in calculus: A ten-year follow-up study


 
 
 This study sets out to examine engineering students’ attitudes and learning goals in a first-year mandatory calculus course. We explored how, and the extent to which, course specific goals and attitudes changed over the course of one semester. A study of learning goals and attitudes was conducted among first-year engineering students at the Norwegian University of Science and Technology in 2007, and “educationally unwelcome” trends were observed. The current follow-up study (2017) was motivated by comprehensive course revisions from 2013 through 2015, including the use of digi- tal learning resources, improved tutoring sessions and the introduction of active learning methods. Contrary to expectations, this follow-up study brings no evidence of positive impacts of the course revisions at the mean level. Some students had stable attitudes and goal orientations, while others switched to undesired territories throughout the semester in the same way as observed ten years earlier. Better integration between foundational and applied courses, and consideration of the entire teaching and learning environment, may yield more of desired attitudes and goal orientations in the first year of study.
 
 

How Do First-Year Engineering Students’ Emotions Change while Working on Programming Problems?

Emotions are a complex multi-faceted phenomenon. To assess the complexity of emotions from different facets, multi-modal approaches are necessary. However, multi-modal approaches are rarely used for assessing emotions, especially in the context of computer programming. This study adopts a multi-modal approach to understand the changes in students’ perception of emotions before and after working on programming problems. Understanding these changes in students’ perceptions may enable educators to devise interventions that help students adjust their perceptions and regulate their emotions as per their skills. We conducted a one-on-one programming session and retrospective think-aloud interview with 17 students from an introductory programming course. During the programming session, students filled surveys and performed four programming tasks. While working on these tasks, students’ eye gaze, video of face and screen, and electrodermal activity data were also collected using a non-invasive device. The data collection for this study was multi-modal, with a mix of both qualitative and quantitative data collection methods. Data analysis was primarily qualitative, with additional triangulation of qualitative and biometric data for select exemplars. The findings of this study suggest that students experience changes in emotions because of many reasons, for instance, they encountered repeated errors, they set high standards for their performance, or they could not manage time. For some students, negative emotions changed to positive emotions when they solved errors without any external help or achieved more than what they expected going into the task. Moreover, the triangulation of qualitative and biometric data of two participants provides a fine-grained analysis of their emotions and behaviors and confirmed the change in the perception of their emotions while performing the programming tasks.