VTechWorks staff will be away for the winter holidays starting Tuesday, December 24, 2024, through Wednesday, January 1, 2025, and will not be replying to requests during this time. Thank you for your patience, and happy holidays!

Scholarly Works, Engineering Education

Permanent URI for this collection

https://hdl.handle.net/10919/24289
Research articles, presentations, and other scholarship

Browse

Browsing Scholarly Works, Engineering Education by Author "Bairaktarova, Diana"

Now showing 1 - 7 of 7
  • Thumbnail Image
    Engineering Student's Ethical Awareness and Behavior: A New Motivational Model
    Bairaktarova, Diana; Woodcock, Anna (2017-08)
    Professional communities are experiencing scandals involving unethical and illegal practices daily. Yet it should not take a national major structure failure to highlight the importance of ethical awareness and behavior, or the need for the development and practice of ethical behavior in engineering students. Development of ethical behavior skills in future engineers is a key competency for engineering schools as ethical behavior is a part of the professional identity and practice of engineers. While engineering educators have somewhat established instructional methods to teach engineering ethics, they still rely heavily on teaching ethical awareness, and pay little attention to how well ethical awareness predicts ethical behavior. However the ability to exercise ethical judgement does not mean that students are ethically educated or likely to behave in an ethical manner. This paper argues measuring ethical judgment is insufficient for evaluating the teaching of engineering ethics, because ethical awareness has not been demonstrated to translate into ethical behavior. The focus of this paper is to propose a model that correlates with both, ethical awareness and ethical behavior. This model integrates the theory of planned behavior, person and thing orientation, and spheres of control. Applying this model will allow educators to build confidence and trust in their students' ability to build a professional identity and be prepared for the engineering profession and practice.
  • Thumbnail Image
    Exploring Students’ Experiences with Mindfulness Meditations in a First-Year General Engineering Course
    Martini, Larkin; Huerta, Mark Vincent; Jurkiewicz, Jazmin; Chan, Brian; Bairaktarova, Diana (MDPI, 2024-05-29)
    With growing mental health concerns among college students, they need to effectively develop skills to alleviate stress amidst the demands of university life. Teaching mindfulness skills to engineering students early in their programs, such as during introductory courses, may provide students with the tools they need to effectively cope with academic stressors, support well-being, and mitigate mental health concerns. This study aimed to understand the variation in experiences of engineering students who participated in weekly mindfulness meditation during a first-year cornerstone engineering course. This study used a thematic analysis approach to analyze students’ in-class, weekly reflections from eight meditation exercises across two course sections. The frequency of codes and themes were then analyzed across meditation types to identify trends in student experiences. Our results show that the most common student experience from engaging in mindfulness meditation was feeling less stressed, calmer, and more relaxed. Other positive experiences include feeling more energized and focused. Some students, however, did report some negative experiences, such as distress and tiredness. The Dynamic Breathing exercise, in particular, showed higher rates of negative experiences than other meditation types. The results also demonstrate that different types of meditations produce different student experiences. Meditation exercises with open monitoring components showed higher rates of insight/awareness and difficulty focusing attention than focused attention meditations. These findings indicate that utilizing weekly mindfulness exercises in introductory engineering courses can benefit students’ overall mental health and well-being when adequately implemented.
  • Thumbnail Image
    Mixed reality based environment for learning sensing technology applications in construction
    Ogunseiju, Omobolanle O.; Akanmu, Abiola A.; Bairaktarova, Diana (2021-11)
    With the growing rate of adoption of sensing technologies in the construction industry, there is an increased need for technically skilled workforce to successfully deploy these technologies on construction projects. Inspired by opportunities offered by mixed reality, this paper presents the development and evaluation of a holographic learning environment that can afford learners an experiential opportunity to acquire competencies for implementing sensing systems on construction projects. To develop the content of the learning environment, construction industry practitioners and instructors were surveyed, and construction industry case studies on the applications of sensing technologies were explored. Findings of the surveys revealed sensing technologies domain-specific skill gap in the construction industry. Further, the findings informed the requirements of the learning environment. Based on these requirements, key characteristics of the learning environment are identified and employed in designing the environment. Still, a formative evaluation is important for developing an effective mixed reality learning environment for teaching domain-specific competencies. Thus, it is imperative to understand the quality, appropriateness, and representativeness of the content of the learning environment. This paper also presents a learnability assessment of the developed mixed reality learning environment. The assessment was conducted utilizing a focus group discussion with construction industry practitioners. Feedback was sought from the participants regarding the reflectiveness of the layout of the virtual environment of an actual construction site and the appropriateness of the represented construction applications. This study contributes to the definition of the type of domain-specific skills required of the future workforce for implementing sensing technologies in the construction industry and how such skills can be developed and enhanced within a mixed reality learning environment.
  • Thumbnail Image
    Person or thing oriented: A comparative study of individual differences of first-year engineering students and practitioners
    Bairaktarova, Diana; Pilotte, Mary K. (2020-02-07)
    Background: Engineering practice is meant to advance the human condition, yet curricula do not appear to fully promote the human-centered philosophy of engineering in implementation. The educational system may inadvertently signal to students that engineering is a career choice better suited for those preferring to work with things rather than people. This framing of the profession prompts questions regarding student interests when compared to those of practicing engineers and how such interests become concrete through education and introduction into the profession. Purpose/Hypothesis: We compare engineering students' and practitioners' interest in working with people or things in their environment. We examine gender differences for each sample. Design/Methods: Multiple analysis of variance was used to examine the samples of practicing engineers (n = 339) and first-year engineering students (n = 383). A multiple-group confirmatory factor analysis provides evidence of measurement invariance and justifies the use of the person-thing orientation (PO-TO) scale structure for both samples. Results: Detailed PO values reveal that students' PO scores (n = 383, M = 3.313) are more than one and a half points lower than practicing engineer counterparts examined (n = 339, M = 4.836). However, no significant difference between practicing engineers and students was found for TO. Further, statistically significant differences in PO and TO were found between male and female participants within both samples, students and practicing engineers. Conclusions: Differences detected in PO and TO across the samples suggest possible environmental factors influencing student perspectives of the engineering profession. This condition may inadvertently discourage more diverse students from pursuing engineering.
  • Thumbnail Image
    Predicting Spatial Visualization Problems’ Difficulty Level from Eye-Tracking Data
    Li, Xiang; Younes, Rabih; Bairaktarova, Diana; Guo, Qi (MDPI, 2020-03-31)
    The difficulty level of learning tasks is a concern that often needs to be considered in the teaching process. Teachers usually dynamically adjust the difficulty of exercises according to the prior knowledge and abilities of students to achieve better teaching results. In e-learning, because there is no teacher involvement, it often happens that the difficulty of the tasks is beyond the ability of the students. In attempts to solve this problem, several researchers investigated the problem-solving process by using eye-tracking data. However, although most e-learning exercises use the form of filling in blanks and choosing questions, in previous works, research focused on building cognitive models from eye-tracking data collected from flexible problem forms, which may lead to impractical results. In this paper, we build models to predict the difficulty level of spatial visualization problems from eye-tracking data collected from multiple-choice questions. We use eye-tracking and machine learning to investigate (1) the difference of eye movement among questions from different difficulty levels and (2) the possibility of predicting the difficulty level of problems from eye-tracking data. Our models resulted in an average accuracy of 87.60% on eye-tracking data of questions that the classifier has seen before and an average of 72.87% on questions that the classifier has not yet seen. The results confirmed that eye movement, especially fixation duration, contains essential information on the difficulty of the questions and it is sufficient to build machine-learning-based models to predict difficulty level.
  • Thumbnail Image
    Using eye gaze to reveal cognitive processes and strategies of engineering students when solving spatial rotation and mental cutting tasks
    Hsing, Hsiang-Wen; Bairaktarova, Diana; Lau, Nathan (American Society for Engineering Education, 2023-01)
    Background: Spatial problem-solving is an essential skill for success in many engineering disciplines; thus, understanding the cognitive processes involved could help inform the design of training interventions for students trying to improve this skill. Prior research has yet to investigate the differences in cognitive processes between spatial tasks in problem-solving to offer learners timely feedback. Purpose/Hypothesis: In this study, we investigated how different spatial tasks change the cognitive processes and problem-solving strategies used by engineering students with low spatial ability. Design/Method: Study participants completed mental rotation and mental cutting tasks of high and low difficulty. Eye-tracking data were collected and categorized as encoding, transformation, and confirmation cognitive processes. The adoption of either a holistic or piecemeal strategy and response accuracy were also measured. Results: Mental rotation was found to have a higher number of fixations for each cognitive process than the mental cutting task. The holistic strategy was used in both difficulty levels of the mental cutting task, while the piecemeal strategy was adopted for the mental rotation task at a high difficulty level. Only encoding fixations were significantly correlated with accuracy and most strongly correlated with strategy. Conclusion: Encoding is an important cognitive process that could affect subsequent cognitive processes and strategies and could, thus, play an important role in performance. Future development in spatial training should consider how to enhance encoding to aid students with low spatial ability. Educators can utilize gaze metrics and empirical research to provide tailored and timely feedback to learners.
  • Thumbnail Image
    ViTA: A flexible CAD-tool-independent automatic grading platform for two-dimensional CAD drawings
    Younes, Rabih; Bairaktarova, Diana (SAGE, 2022-01-01)
    Grading engineering drawings takes a significant amount of an instructor’s time, especially in large classrooms. In many cases, teaching assistants help with grading, adding levels of inconsistency and unfairness. To help in grading automation of CAD drawings, this paper introduces a novel tool that can completely automate the grading process after students submit their work. The introduced tool, called Virtual Teaching Assistant (ViTA), is a CAD-tool-independent platform that can work with exported drawings originating from different CAD software having different export settings. Using computer vision techniques applied to exported images of the drawings, ViTA can not only recognize whether or not a two-dimensional (2 D) drawing is correct, but also offers the detection of many important orthographic and sectional view mistakes such as mistakes in structural features, outline, hatching, orientation, scale, line thickness, colors, and views. We show ViTA’s accuracy and its relevance in the automated grading of 2 D CAD drawings by evaluating it using 500 student drawings created with three different CAD software.