Factor (EF) is primarily linked toCovid-19 (EF2) as the impact of other factors is more variable across participants. In addition tofurther illumination of the responses for the activity codes, examination of the subcode data revealedan interesting pattern where several individual overall program codes have negative response patterns– matriculation (bureaucratic & academic issues before first class) (OP2), fellowship requirements(OP3), and bureaucratic and administrative issues after first class (OP4) - even though the aggregatevalue of the response code for Overall Program (OP) is (slightly) positive as shown in Figure 2. Ascan be seen by the subcode names, all of these reflect activities that participants viewed as eitherbureaucratic or
peers.Multiple Apprenticeship Model (Walker et al., 2008) Each of these features should shape the relationship between the scholar and their mentors. Faculty with scholarly and professional expertise help students self-reflect upon the Intentionality process of creating scholarly ideas and communicating them to others in their field. Multiple Students engage with numerous intellectual mentors. Relationships Collective All parties share responsibility for the development of students’ learning. Responsibility Allow individuals to learn mentoring techniques and be recognized and rewarded for Recognition demonstrating
Foundation Awards#1937950, 1939105; USDA/NIFA Award#2021-67021-35329. Any opinions, findings, conclusions, or recommendations expressed in this Aditya Johri johri@gmu.edu material are those of the authors and do not necessarily reflect the views of the funding agencies. The research study has been approved by the George Mason University Institutional Review Board at George Mason University. bit.ly/mason-tech-ethicsThis talk is about a research
a complementary access point and reinforcing the commitment to providecomprehensive educational resources.Course WebsiteIn the realm of open educational resources (OER), the accessibility and relevance ofmaterials are crucial. To address this, a dedicated website (https://sites.google.com/georgiasouthern.edu/digitaldesign) was developed using Google Sites,serving as a central hub for disseminating the OER materials related to the Digital Designcourse both to students and the broader OER community. This website is actively managedand regularly updated by the development team, ensuring that the content remains current,reflecting the latest advancements in software and hardware. Additionally, it allows fordynamic adaptation to align with the
disclosed in the application. The final participation pool was from four different engineering departments, representedmultiple gender and sexual identities, disability statuses, and racial identities. Additionally, manyof the students in the program were international students. Exact identities and participationdemographic statistics have been withheld to protect participant anonymity.Program Facilitation The program itself was based on the success of other first year mentorship programs at theuniversity [11]. The mentorship program officially began in January of 2024. The mentors werefirst invited to attend a one-hour onboarding and mentorship training, in which they were providedwith program specifics, and we reflected on
]. With the increase in research publications, the focus on impact indicators has broadened,with citation counts remaining a widely accepted measure. Yet, they are not direct measures ofquality [7]. Despite controversies around these metrics, they continue to be used in academicdecision making. An additional metric that is being used more for evaluating scholarship are downloadcounts [8, 9]. Using downloads reflects a broader view of research impact, considering the actualusage and dissemination of scholarly works. While there is a correlation between downloadmetrics and citations [10], there are situations where this is not the case. For example, papers withfewer citations might be extensively downloaded and used by practitioners
Biotechnology in the Division of Science and Technology at the United International College (UIC) in Zhuhai China. She has trained with ASCE’s Excellence in Civil Engineering Education (ExCEEd) initiative, been exploring and applying evidence-based strategies for instruction, and is a proponent of Learning Assistants (LAs). Her scholarship of teaching and learning interests are in motivation and mindset, teamwork and collaboration, and learning through failure and reflection. Her bioengineering research interests and collaborations are in the areas of biomaterials, cellular microenvironments, and tissue engineering and regenerative medicine. She serves on leadership teams for the Whitaker Center of STEM Education and the
development. These business achievements are reflected in his academic activities through the designing of lectures and mobility programs with practical implementation perspectives. Ishizaki has been actively presenting and publishing his academic achievements at international conferences in the Asia Pacific region and North America such as APAIE, WERA, and NAFSA. He earned a Master of Business Administration majoring in international business at the University of Southern California in the United States of America, and a Bachelor in Law at Hitotsubashi University in Japan.Dr. Maria Anityasari, Sepuluh Nopember Institute of Technology Maria Anityasari is the Director of ITS Global Engagement. Institut Teknologi Sepuluh
, enhanced teamwork and sustainedprofessional development.The professional identity of doctoral students is defined by their acknowledgment andrecognition of their major through rigorous study, research, and practical applicationof their academic disciplines. Furthermore, it reflects their eagerness to proactivelyadhere to professional and occupational norms, and to pursue this career as a personallifelong goal.[11,12] Identity in the field of engineering education also focuses on theoverall process of an individual's transformation from an "outsider" to a community inthe field of engineering, such as awareness and perception of the content ofspecialized knowledge in engineering, the significance of the profession, thecharacteristics of the
ConclusionsA. Student metacognitionMetacognition involves a person critically analyzing their own understanding. Within engineeringeducation, this reflective practice by the student enhances learning and problem solving. Thereare numerous classroom structures or techniques we can use to build these skills. ChatGPTprovides interesting ways for a student to engage with material, and may further a student’sunderstanding of their own learning processes, problem-solving strategies, and perhaps identifyknowledge gaps.The process of initially re-engaging with the test question without the assistance of AI, provided ameans to both reflect on their own work, as well as explore more traditional means of correctingor expanding their original code outside the
suffer from high attrition rates[2] [4] [5]. If factors that improve the chances of student success in this type of course could beidentified, they could be used to reduce attrition rates and improve educational outcomes in amore scalable fashion.The purpose of this research is to understand if identified student attributes and behaviors arerelated to higher levels of success in a free, online, voluntary, noncredit, introductory Pythonprogramming course. The course was developed by the authors and provided to over 900students in several cohorts, with the same general curriculum delivered online via GoogleClassroom over a period of 18 months. Students in these courses were evaluated using multiple-choice quizzes, participation in reflection
proved to be daunting, for both participants and organizers.For best possible participant availability the workshop was held during an academicbreak on consecutive days. However, the short calendar span was not conducive toin-depth reflection or detailed course planning, and there was definitely no time forimplementation and testing. Although enthusiasm was high after the workshop, thebeginning of the spring academic semester quickly pushed planned activities to theback burner, and momentum fizzled. Course assignment changes and changes infaculty positions further complicated implementation of the course changes plannedduring the workshop. In addition, the planning and presentation of the workshop contentwas up to the organizers, and this
methods to diverse learning needs, as reflected in varying ratiosof correctness in pre-/post-lecture tests [15]. Collectively, these studies underscore the importanceof recognizing each class as a unique entity, catering to the diverse learning styles and backgroundsof students.In this research, we aim to broaden the application of pre-post lecture assessments, elevating themfrom feedback tools to more refined instruments that measure learning at different cognitive levels,as defined by Bloom's Taxonomy (Figure 1b). Our strategy involves aligning key lecture learningoutcomes with pre/post assessment questions, crafted to probe varying cognitive depths. Thismethod will provide instructors with a more nuanced understanding of student
collection of additional information,consideration of external constraints, and thoughtful reflection on the solution process. Theseskills are recognized as crucial for future engineers in their daily professional lives. However,there are concerns from employers and researchers that undergraduate students may not beadequately prepared to address such problems upon graduation [1‒3]. To make things worse,courses in thermofluids require a robust understanding of mathematics and extensively utilizephysics to explain physical systems. Heat transfer, in particular, introduces complex subjects thatmay appear even more difficult for students studying engineering technology.There have been some attempts at addressing the students’ problem-solving abilities
duties or roles, where teaching faculty alternate in delivering classes or dividethe course credit load based on specific weeks or assignments [4]. This method does notmaximize the potential of coteaching, which should enable instructors to interact with each otherin class be used to leveraging the collective knowledge and expertise of multiple teachers withinthe same classroom to enhance student learning outcomes [1], [5]. This collaborative teachingmodel fosters a dynamic learning environment, addresses the varied learning needs of students,promotes active engagement, and provides differentiated instruction. Furthermore, co-teachingencourages shared responsibility, reflection, and professional growth among teachers, ultimatelyenhancing the
was a teachingphilosophy that students learn by doing and that should apply to project management. Bydefault, project management is an active learning exercise that involves a diverse group ofindividuals. The literature in project management education supports this underlying personalbelief. “Preparing students for professional practice is enhanced by the use of ‘authentic’ tasksand assessments that reflect the practices and outputs encountered in the profession” [1]. Inorder to be authentic, it needs to be a real executable project. The literature also speaks about thedisappointment with practitioners on the skills of students and that has been confirmed withadvisory boards in our college.In addition, students who took the previous version
, our research delves into the realm of student-teacher dynamicsthrough the lens of learning styles, as evaluated by the Silverman-Felder Index of Learning Styles(ILS). This study aims to contribute to the discourse within engineering education by examining thecorrelation between the alignment of student and instructor learning styles and its impact onstudent academic performance. The Silverman-Felder ILS, a well-established tool, delineateslearning styles across four dimensions: active/reflective, verbal/visual, sensing/intuitive, andsequential/global. We operationalize alignment as the proximity in four-dimensional space betweena student's ILS score and that of their instructor. Initial findings based on a cohort of 300 Cadets atthe United
participation in learning [9]. Developing teamwork skillsbenefits students academically and has long-term implications for personal and professionaldevelopment. It develops leadership skills, enhances problem-solving abilities, and developsdecision-making skills, all contributing to students' overall growth and readiness for futureefforts [2], [10], [11], [12]. Teamwork skills gained through academic settings are crucial forstudents' future careers as employers highly value them [13]. It also enhances empathy, socialawareness, and improved decision-making abilities, which are essential for navigating diversework environments and making informed choices [14], [15]. Effective time management skillsand self-reflection abilities in students are being
among engineering students isalso worth noting, as different types of strengths and supports are commonly associated withthese conditions.Fairly large numbers of engineering students self-identified as maybe neurodivergent, whichlikely reflects a lack of clarity on what conditions “count” as ND (using a medical model),variability in formal diagnosis, and/or lack of general familiarity with the term. The write-inresponses reflect this range of framing. Some of the conditions listed are not traditionallyconsidered forms of neurodivergence under a medical model (e.g., anxiety) but are moreclassically considered mental disorders or internalizing disorders (Andrews et al., 2008). Thehigher percentage of female compared to male students identifying
a corporate environment. Therefore, accurately reflecting the true opinionsof apprentices to partner companies is crucial to ensuring these apprentices are set-up for longterm success at those companies, given the companies' investment into those students during theapprenticeship program.In the following paper, the authors will explore the preparation and application stages, as well asthe technical and social elements involved in apprenticeships within partner companies. Thepaper will also include apprentices' perspectives on each of these aspects.Apprenticeship Preparation and Application ProcessThe development of the apprenticeship program in partnership with the college has also involvedthe creation of a career development pipeline to
the following: Ability to determine the domain of differentiability of a function. Ability to determine the differentiability domain of a composition function. Ability to apply the chain rule correctly. Ability to determine the domain on which the chain rule is applied.APOS theory is briefly explained in [10] as follows: An action is a transformation of objects perceived as essentially external and as requiring, either explicitly or from memory, step-by-step instructions on how to perform the operation. When an action is repeated and the individual reflects upon it, the individual can make an internal mental construction called a process which the individual can think of as performing the same
al. [3]. Transformational resistance is defined as an action that reflects a critique of thesocial oppression at hand, rather than conformist resistance that does not challenge the structure athand. The structure of a panel puts graduate students in the seat of authority and allows them todirectly relay their experiences to the attendees. This challenges the structure by empoweringoverlapping disempowered groups, graduate students, and LGBTQ people. Members of the panelincluded both cis and trans people, individuals who are nonbinary, individuals who are gay orlesbian, and students on the neurodivergent and asexual spectrum. When creating the panel, it wasessential to ensure that a broad swath of identities were represented. There will
terms in consultation with the engineeringlibrarian, and the finalized search string is shown in Figure 3. We are currently further refining thesearch string by taking a more systematic approach to identify terms related to the sense ofbelonging, based on the previous suggestions by Phillips et al.’s (2017) reflection on a systematicliterature review. (belonging OR belongingness OR connectedness OR relatedness OR “sense of inclusion” OR “sense of school membership” OR “sense of social fit”) AND (“engineer* educat*” OR “STEM educat*” OR “biology educat*” OR “chemistry educat*” OR “math educat*” OR “physics educat*” OR “geoscience educat*” OR “computer science educat*” OR “engineering student*” OR “STEM student*” OR “biology student*” OR
taken [2]. The research ofEdmondson noticed that certain teams within the same hospital produced very differentoutcomes for the patients they oversaw. As she observed more closely why certain teams couldbecome a learning organization, she noticed that the teams did seven things positively. From theseven items she created a survey that a team could use to guide a reflection on where they are intheir growth towards becoming a learning organization.The seven survey items that Edmonson created are included in the appendix of this paper, butcan be summarized into the following categories of scenarios commonly encountered in teams:making mistakes, asking for help, taking small risks, discussing tough issues, respecting thecontribution of others
century engineering workforce. Angie received an NSF CAREER award in 2021 for her work with student veterans and service members in engineering.Mr. Talha Naqash, Utah State University Mr.Talha Naqash is currently pursuing his doctoral studies in Engineering Education at Utah State University. With a profound educational background spanning multiple disciplines, he holds an MS in Telecommunication and networking. His extensive research contributions are reflected in numerous publications and presentations at prestigious IEEE & ASEE conferences, Wiley’s, and Springer Journals. His research primarily revolves around understanding Cognitive Engagement Analysis, Assessing Methods in Engineering Education, and
, we acknowledge that as a team primarilycomprising white women and nonbinary people, we come from a place of privilege in society.We continuously work to critically reflect on our intersectional identities and leverage ourprivilege to work towards greater justice, as well as create an inclusive community. In telling thestory of our design, we share ways we have embodied this value.In this design case, we first describe the context in which we designed the GATHER CoT,including some early ideas that shaped our focal narrative, which illustrates key decisions wemade in the process of designing an arts-based kickoff event that we hoped would begin formingtrust and community, the bedrock of GATHER. While we made many design decisions, in thiscase
students are not in the field and possessing expertise or specific working knowledge? 14 -Does the design reflect creativity and imagination on the student’s or team’s part?Overall Is the design well written? 5quality of Does the report effectively present the design solution? 3the designpackage Does the report follow the required format and reference citation requirement? 3Total points 115The course structure was not changed significantly when the ACRP University DesignCompetition was first
data training set that was used, thisis reflected in the results or writing created by it. “ChatGPT is known to perpetuate stereotypessuch as nurses being female and doctors being male…” [2], many of these biases are included inhuman writing which is then reflected by the program however the identifiable source of thesebiases are lost when in this form making it harder to identify. While many of the other problemscan be solved through increasing the data set of the AI model, this problem will have to becarefully considered by the AI companies if it can be solved at all.False Information‘Hallucination’ or falsely presenting information can be an issue. While the software excels at thegeneration of documents it is prone to falsely presenting
. DiscussionThis research aims to examine students’ in situ demonstration of the cognitive and behavioralskills associated with algorithmic thinking in an introductory computing course in engineering.Our findings indicate that while students are frequently able to produce working code that solvesa wide array of computing problems, their submissions do not always reflect the cognitive skills,such as algorithmic thinking, that are central learning goals in introductory CS education. Thesefindings lead us to question the utility and appropriateness of autograders for assessing andevaluating student learning, particularly as it relates to complex cognitive skills in CS education.Existing research suggests instructor feedback supports students’ learning beyond
to reflect on accessibility within this setting. Each timeco-researchers mentioned negative experiences related to their disability(s) or accessibility, theywere asked to consider what supports or changes could have improved their experience.Data Analysis and Trustworthiness Transcripts were de-identified before beginning any analysis to maintain co-researcherconfidentiality. After de-identification, transcripts were uploaded to Dedoose (2021) to code andanalyze the interview data. Data analysis was conducted in two rounds using thematic analysis(Braun & Clarke, 2006) through a critical lens. Salient themes were identified using aconstant-comparative, open coding process (Saldaña, 2016). Open coding was used in the firstround to