Engineering Course Research Articles

Alternating Donor-Acceptor Ladder-Type Heteroarene for Efficient Photothermal Conversion via Boosting Non-Radiative Decay.

The development of novel ladder-type conjugated molecules is crucial for advancing supramolecular chemistry and material science. In this study, we report a straightforward synthesis of new alternating donor-acceptor (D-A) ladder-type heteroarene, FCDTDPP, and demonstrate its application as photothermal agent for imaging and cancer therapy. FCDTDPP is constructed by vinylene bridge between cyclopentadithiophene (D) and diketopyrrolopyrrole (A) through intramolecular Friedel-Crafts type reaction. FCDTDPP exhibits unique combination of good molecular planarity, efficient intra/inter-molecular mixed D-A interactions, and local aromaticity. These features collectively contribute to its broad and intense absorptions with narrow bandgap in red band of the spectra, coupled with multiple vibrational absorption feature, thereby enhancing non-radiative decay process and resulting in efficient photothermal conversion property. FCDTDPP and its nanoparticles (NPs) exhibit superior photothermal conversion performance and stability under 660 nm laser irradiation. Moreover, in vitro studies reveal that FCDTDPP NPs possess excellent biocompatibility, low cytotoxicity, and robust photothermal therapeutic efficacy, a finding further corroborated by preliminary in vivo experiments in tumor-bearing mice. This work charts a novel course for the molecular engineering of organic photothermal conversion systems, propelling relevant research forward.

Alternating Donor‐Acceptor Ladder‐Type Heteroarene for Efficient Photothermal Conversion via Boosting Non‐Radiative Decay

The development of novel ladder‐type conjugated molecules is crucial for advancing supramolecular chemistry and material science. In this study, we report a straightforward synthesis of new alternating donor‐acceptor (D‐A) ladder‐type heteroarene, FCDTDPP, and demonstrate its application as photothermal agent for imaging and cancer therapy. FCDTDPP is constructed by vinylene bridge between cyclopentadithiophene (D) and diketopyrrolopyrrole (A) through intramolecular Friedel‐Crafts type reaction. FCDTDPP exhibits unique combination of good molecular planarity, efficient intra/inter‐molecular mixed D‐A interactions, and local aromaticity. These features collectively contribute to its broad and intense absorptions with narrow bandgap in red band of the spectra, coupled with multiple vibrational absorption feature, thereby enhancing non‐radiative decay process and resulting in efficient photothermal conversion property. FCDTDPP and its nanoparticles (NPs) exhibit superior photothermal conversion performance and stability under 660 nm laser irradiation. Moreover, in vitro studies reveal that FCDTDPP NPs possess excellent biocompatibility, low cytotoxicity, and robust photothermal therapeutic efficacy, a finding further corroborated by preliminary in vivo experiments in tumor‐bearing mice. This work charts a novel course for the molecular engineering of organic photothermal conversion systems, propelling relevant research forward.

Probabilistic Linguistic TODIM Method with Probabilistic Linguistic Entropy Weight and Hamming Distance for Teaching Reform Plan Evaluation

In the context of the construction of new liberal arts, the integration and intersection of disciplines have become a new trend in the development of higher education. How to promote the teaching reform of big data technology and application courses in the new liberal arts construction scenario has become an important issue in enhancing students’ digital talent literacy and social adaptability. In this study, an extended probabilistic linguistic TODIM (an acronym in Portuguese for interactive multi-criteria decision making) with probabilistic linguistic entropy weight and Hamming distance is presented for teaching reform plan evaluation for the core course “big data technology and applications” in the digital economy major. Firstly, probabilistic linguistic entropy weight, based on the entropy of the additive linguistic term set, is applied to generate weight information. Secondly, parameter sensitivity analysis is carried out to prove the stabilization and effectiveness of the extended TODIM approach. Thirdly, this extended approach can integrate the psychological factors and cognitive behaviors of decision-makers for effectively responding to education management in the new liberal arts construction scenario. Finally, a case study on teaching reform plan evaluation is carried out, and a comparative analysis with different criteria weights and different methods is conducted to verify the extended approach. The results indicate that the extended approach can provide an effective technical tool for scientific decision-making, especially in the teaching reform plan evaluation scenario in order to promote high-quality development of education.

Enhancing academic outcomes through industry collaboration: our experience with integrating real-world projects into engineering courses

This research investigates the integration of industry projects and mentorship into academic curricula, aiming to enhance student learning and professional readiness. By incorporating real-world projects and pairing students with industry mentors, this approach seeks to provide a unique blend of theoretical knowledge and practical application. Utilizing a mixed-methods research design, the study captures both quantitative and qualitative data to assess the educational outcomes of this innovative model. Quantitative metrics include final grades, attendance rates, participation rates, placement rates, project grades, and professional skills ratings, while qualitative feedback is gathered from students, mentors, and faculty. The study is set against the backdrop of two courses that have been redesigned to include elements of industry collaboration. The findings are expected to shed light on the effectiveness of this approach in preparing students for the demands of the modern workforce, offering insights into how industry mentorship and project-based learning can enhance academic curricula and better equip students for their future careers.

Enhancing Automated Peer Code Reviews in Software Engineering Education with Context-Aware Generative AI

This study investigates the enhancement of peer code reviews in software engineering education through the integration of Generative Artificial Intelligence (GenAI) with contextual awareness. Previous implementations of GenAI, such as ChatGPT, lacked detailed context about the educational content and assessment goals, limiting their effectiveness. Our work-in-progress research addresses this gap by providing GenAI with additional static and dynamic contextual information, including project overviews, pull-request descriptions, and comments. In a controlled study involving 26 students from a 12-week software engineering course, we compared the efficacy of the original GenAI system with a context-enhanced version. Results demonstrated that the context-aware GenAI provided more accurate and useful feedback, as perceived by the students. These findings suggest that incorporating contextual information improves the quality of automated peer reviews, offering a promising tool for educators to enhance student learning and engagement in code review activities.

Examining the Support of Students in e-Learning Context: e-Tutors’ Perspectives

Student support received some attention from e-learning institutions but with some caution in the extent of empirical studies where -tutors’ perceptions were explored. The premise of this research paper is to contribute to an understanding of how support is understood from the e-tutors’ perspectives. It also aims to suggest new and alternative support mechanisms for the e-tutors. Six e-tutors were participants in the Design Thinking and Technology course modules for honours students at a distance learning institution. A quantitative approach and web questionnaires were used to collect the data and were analyzed and visualized through pie charts to represent the data. The findings reveal a significant gap in the e-tutors' ability to effectively support students based on the constructs that were developed. This highlights a critical area for improvement in the training and resources provided to e-tutors to enhance the efficacy of online education.

Discussion on the Teaching Reform and Practice of “Civil Engineering Materials” under the Background of “New Engineering”

As a fundamental course in civil engineering, the reform and practice of “Civil Engineering Materials” are crucial for the development of the civil engineering discipline. This paper addresses previous teaching shortcomings and integrates the new requirements of “New Engineering” construction. It explores the reform of teaching methods for “Civil Engineering Materials” in five areas: optimization and integration of teaching content, adjustment of experimental content, application of online learning platforms, cultivation of students’ innovative abilities, and optimization of assessment methods. The paper offers constructive suggestions for the future development and practice of the course.

Exploring Online Teaching's Impact on Instructors in Core Engineering Courses: Insights, Challenges, and Future Directions

ABSTRACTThis study examines the impact of online teaching on instructors of fundamental engineering courses, focusing on insights, challenges, and future pathways. By analyzing the instructors' perspectives, the research examines various aspects of online teaching, including mode of delivery, student engagement strategies, assessment preferences, and future directions. Insights are drawn from a comprehensive survey of instructors, shedding light on their experiences, challenges, and preferences in the online teaching landscape. The findings highlight a preference for synchronous sessions, the utilization of diverse engagement techniques, and the significance of maintaining academic integrity in assessments. Instructors' preference for face‐to‐face interaction for improved academic performance and openness to hybrid teaching modes are evident. This study not only provides valuable insights into the dynamics of online teaching but also paves the way for future advancements in pedagogical strategies and educational technology integration. The research identifies potential areas for future work, ranging from refining hybrid teaching models to exploring emerging technologies and fostering instructor training.

Empowering student entrepreneurship skills: A software engineering course for innovation and real-world impact

Empowering student entrepreneurship skills: A software engineering course for innovation and real-world impact

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.

Antecedents and consequences of academic help-seeking in online STEM learning

IntroductionCollege students often encounter challenges or ambiguity in online learning, which they cannot overcome independently, and therefore, require help. However, relatively little is known about how academic help-seeking can be supported in online contexts and about its potential benefits. The present study investigated the role of academic help-seeking in online STEM learning and its contextual antecedents.MethodsA total of 213 college students, enrolled in an introductory Engineering course, completed an online survey. Their survey responses and academic record data were analyzed.ResultsResults of path analysis indicated that adaptive help-seeking was positively related to retention intention, whereas expedient help-seeking was negatively related to the choice of future courses. In addition, avoidant help-seeking was negatively related to retention intention and major declaration status and positively to disorganized studying. Results also showed that sense of belonging and environmental fixed mindset served as significant predictors of academic help-seeking.DiscussionFindings indicate that academic help-seeking is related to successful online STEM learning. Therefore, fostering online learning contexts in which students perceive more sense of belonging and less environmental fixed mindset is crucial.

Design Thinking in Online Spaces: How Students Develop Their Engineering Identities

Engineering identity plays a key role in the educational experiences of undergraduates majoring in engineering fields. Design thinking pedagogy can enhance engineering identity. However, little is known about how design-thinking pedagogy influences engineering identity development within an online environment, and specifically how this looked during the COVID-19 pandemic. The purpose of this qualitative study was to understand how a design thinking-oriented engineering course delivered online supports undergraduate students’ engineering identity development during the COVID-19 pandemic. Researchers collected 63 observations, totaling approximately 79 hours of observation of an embedded systems engineering course. Findings revealed the importance of language and framing in shaping engineering identity in online learning spaces. In addition, online student-faculty interactions were seen as an area of growth. Finally, the study found that online spaces can complicate opportunities for engineering identity performance. This study has implications regarding intentionality and online learning. To enhance engineering identity, faculty and administrators should consider how they use language to frame their courses and create meaningful student-faculty interactions.

Integrating an Annotation Project in a Senior-Level Biomedical Engineering Course to Develop Primary Literature Analysis and Science Communication Skills

Abstract Purpose This paper describes a senior-level biomedical engineering course designed to educate students on primary literature analysis and effective scientific communication. The course integrates elements from both disciplines through in-class discussions of primary research articles and an innovative annotation project utilizing the Science in the Classroom (SitC) program. Methods The course incorporates weekly discussions of seminal research articles led by the instructor in the field of biomedical microdevices, bi-weekly quizzes to assess comprehension, and a novel final project where student groups collaborate to annotate a high-impact scientific article through the SitC program. The annotations aim to make the article accessible to a broader audience while training the students in primary literature analysis and effective scientific communication. Results The course effectively enhances student understanding of primary literature, as evidenced by the significant improvement in quiz scores following in-class discussions. Additionally, student participation in the annotation project contributes valuable educational resources to the SitC program, promoting the dissemination of scientific knowledge to a wider audience. Conclusions The novel aspects of the course, specifically the annotation project, offer a unique learning experience by equipping students with the necessary skills to navigate and critically analyze primary research articles. The course also fosters effective scientific communication, transforming students into active contributors to the scientific community. Recommendations are included for instructors interested in adopting this novel approach to teaching primary literature analysis and scientific communication.

The Influence of Artificial Intelligence Tools on Student Performance in e-Learning Environments: Case Study

This study investigated the impact of AI-powered personalized learning tools on the academic performance and perceptions of pre-service student teachers enrolled in the Educational Technology course, a compulsory component of the Professional Postgraduate Diploma in Teaching program at Ajman University. A quasi-experimental design was employed with 55 students in the experimental group and 55 in the control group. The experimental group utilized AI-powered tools within the Moodle platform, while the control group received traditional instruction. Pre- and post-tests, along with a rubric-based assessment and a questionnaire, were administered to assess performance, knowledge retention, critical thinking, motivation, and engagement. Statistical analysis revealed significant differences between the groups, favoring the experimental group in terms of academic performance and knowledge retention. Additionally, students in the experimental group demonstrated higher levels of critical thinking, motivation, and engagement. These findings underscore the transformative potential of AI-powered personalized learning tools in teacher education. By integrating AI into educational practices, institutions can revolutionize e-learning by providing personalized instruction, intelligent tutoring, automated grading, and adaptive learning experiences. This can enhance student engagement, improve learning outcomes, and reduce the workload of educators. Ultimately, AI empowers institutions to create more effective and inclusive learning environments that cater to the diverse needs of students and prepare them for the future.

Comparison and AI-based prediction of graph comprehension skills based on the visual strategies of first-year physics and medicine students

Graphical representations of data are common in many disciplines. Previous research has found that physics students appear to have better graph comprehension skills than students from social science disciplines, regardless of the task context. However, the graph comprehension skills of physics students have not yet been compared with (veterinary) medicine students, both of which are disciplines that require multiple science, technology, engineering, and mathematics (STEM) courses. This study extends previous research on this subject by exploring whether physics majors possess superior graph comprehension skills due to their study discipline. Here, participants solved 24 graph comprehension tasks across various subjects, including mathematics, physics, and medicine; these tests were conducted at the beginning and end of their first semester. Graph comprehension gain was calculated based on the percentage of correct and incorrect answers in the pretest and the post-test. In addition to these comparisons, we replicated previous research that successfully distinguished correct and incorrect solvers based on their visual behavior by using a novel machine-learning method tailored to small datasets. Through this replication of statistical analyses, we aim to ensure the reliability of adaptive learning systems in the future, regardless of data size, using the same machine-learning method. Physics and medical students were found to exhibit relatively similar graph comprehension gain; this is in contrast to previous research comparing physics and non-STEM students. Our results also revealed that both physics and medical students use similar visual strategies to solve these tasks. However, correct and incorrect solvers could be distinguished via machine-learning methods regardless of their discipline. Our research suggests that visual behavior is a good predictor of graph comprehension skills. Published by the American Physical Society 2024

The Role of AI Technology in Digital Media Technology Course Teaching

With the rapid development of Internet technology and the widespread use of smart terminals, we have entered the Internet era. The continuous innovation of artificial intelligence (AI) technology has enriched people's work and life and has changed how people receive information. Unlike traditional media such as newspapers, magazines, and television, digital media provides a more efficient way to access information. In the 21st-century knowledge economy, digital media has become a core industry. Under such circumstances, universities across the country have successively introduced related courses, with the Digital Media Technology program being one of the most representative. Due to the diverse fields and wide application range of digital media technology, its social functions have been fully demonstrated during its development. Therefore, integrating AI technology into the teaching of digital media technology courses can help adjust teaching goals, optimize teaching methods, and gradually enhance students' initiative. This paper aims to explore the specific application of AI technology in digital media technology course teaching to provide useful references for educators.

Integrating Art into Engineering: An Educational Gaps and Solutions

This paper explores the deficiencies in art education within engineering schools in Hebei and proposes strategies for integrating art to enhance creativity and innovation. The paper identifies key gaps in the current curriculum, including a lack of interdisciplinary courses and insufficient institutional support for creativity-driven initiatives. Drawing on existing literature and successful case studies, the proposed solutions include integrating art into engineering courses, fostering professional development, and enhancing collaboration between disciplines. The long-term benefits of this integration include improved problem-solving skills, enhanced creativity, and broader professional competencies. By examining Hebei’s educational landscape, this paper presents a model that could inspire similar reforms in engineering education globally.

Investigative and collaborative experimental activities using simple purification of curcuminoids by column chromatography

This work describes the use of turmeric in the teaching concepts and laboratory techniques of organic chemistry to students in introductory classes of licentiate, bachelor’s and industrial chemistry courses, as well as to pharmacy and chemical engineering students at Universidade Federal Fluminense, in Niterói/RJ/Brazil. Considering investigative and collaborative activities and Vygotsky theory, the discussed concepts were everyday natural products, green chemistry, purification and separation of organic substances, molecular interactions, organic compound extraction techniques, and thin-layer and column chromatography. The activities were applied for four 3-hour classes for 31 students in 7 introductory organic chemistry laboratory classes for Chemistry and for 43 students in 4 experimental organic chemistry classes for Pharmacy and Chemical Engineering courses, in the years 2022–23. The teaching-learning process methodology involved 4 moments/classes: a) discussions about organic chemistry; b) discontinuous extraction of turmeric and thin-layer chromatography; c) column chromatography; and d) discussions about results and the learning process. After the sequence of classes, it was possible to observe the students’ motivation with the ease of separating curcuminoids and the understanding of the relationship between theoretical concepts and practice, as well as the understanding of the importance of low waste production.

Study on the Teaching Reform of Translation Technology in the Context of New Liberal Arts

At present, the world is in a period of great change and development. Driven by emerging technologies such as artificial intelligence, big data, and the Internet of Things, the translation technology requirements for translation talents are higher. The study of translation technology has become the core curriculum of translation major, which has a profound impact on translation education under the background of the construction of new liberal arts. Guided by the new requirements of the development of language service industry, this paper discusses in detail the teaching mode of the core course of translation technology under the background of the new liberal arts from the aspects of the dilemma of translation curriculum, the principles of the design of translation technology curriculum, course content, teaching methods and course assessment. This paper explores how to reform the translation technology curriculum and realize the innovative development of education and teaching.

Synergizing Systems Thinking and Technology-Enhanced Learning for Sustainable Education Using the Flow Theory Framework

In an era where digital technologies are integral to daily life and sustainable education is increasingly critical, developing higher-order thinking skills with appropriate information and communication technology (ICT) support is crucial for achieving Sustainable Development Goals (SDGs). The purpose of this study was to examine synergies of systems thinking and technology-enhanced learning from the perspective of flow theory within the context of sustainable education. We surveyed more than 65 pre-service preschool teachers engaged in a design, technology, and engineering (DTE) course at the University of Ljubljana. Mapping of systems thinking revealed that pre-service preschool teachers needed support regarding feedback and understanding the interrelationship dimension of systems thinking—essential components of sustainable education. Predictive and mediation analyses yielded noteworthy results. Participants in the ICT-enhanced DTE course rated their cognitive and social engagement above the mid-point of the scale, with this higher engagement correlating with higher systems thinking crucial for sustainable education. In contrast, their aesthetic engagement was below the mid-point of the scale. Experiencing a flow state during ICT activities positively influenced systems thinking, particularly in terms of clear goals and autotelic experiences. Flow theory thus emerges as a solid and appropriate framework to use for studying synergies in technology-enhanced systems thinking for sustainable education. These findings underscore the importance of integrating systems thinking into curricula to enhance learning outcomes and prepare students for future challenges, thereby contributing to the achievement of SDGs through sustainable education.