general, a broader research base on SBPs is likely to be useful inmeeting program goals.AcknowledgementsThis work is supported by the National Science Foundation under award #2119930. Anyopinions, findings, and conclusions or recommendations expressed in this material are those ofthe author and do not necessarily reflect the views of the National Science Foundation.References [1] What Works Clearinghouse Summer Bridge Programs. 2016; https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=WWCIRPS661, Publisher: National Center for Education Statistics. [2] Yoder, B. L. Going the distance: Best practices and strategies for retaining engineering, engineering technology and computing students. American Society for Engineering Education. 2012
three themes related to advisor-advisee communication: Mutual Trust, ClearExpectations, and Delivery of Feedback.Mutual TrustWhen asked if they would share information about their neurodiversity-related experiences,strengths, and challenges with their advisor, most participants expressed some hesitation aboutdoing so, suggesting that students may not have the necessary trust in their advisor-adviseerelationship to facilitate these types of discussions. Wendy, who later on in her programdeveloped open communication with her advisor about neurodiversity, reflected on her earlyperception that she was not safe discussing her experiences with ADHD, saying: I think it would be something that might be helpful to share with my advisor
influenceparticipants' responses. Third, the study included a mix of closed-ended and open-endedquestions, allowing participants to express their thoughts and experiences in their own words.However, despite these efforts, the possibility of response bias cannot be entirely eliminated,and the results should be interpreted with this limitation in mind.Finally, the rapidly evolving nature of AI technology presents another challenge. The study'sfindings are reflective of the current state of AI and may not remain relevant as newadvancements and shifts in the industry emerge.6.2 Future WorkTo build upon the findings of this study and address its limitations, future research couldexpand the scope to include a more diverse range of participants from various
student-to-instructor interaction has a significantimpact on students’ learning and engagement [31]. Similarly, studies also show that student-to-instructor interactions help the student create a sense of belongingness in the online courses [32].Limitations, Implications, and Future WorkSimilar to other research studies, this study also comes with limitations. The sample recruited forthis study includes participants from one university at undergraduate level and is not representativeof the broader online engineering programs/community. Additionally, the undergraduate studentsrecruited were from only three engineering majors: information technology, software engineering,and graphic information technology, which does not reflect the experiences of
who changemajors, and students who are veterans (e.g., [7], [27]). Other work has indicated the importanceof factors such as motivation and belongingness [5], [28]. While those factors are not connectedto a students’ academic record, they are an important reminder of what academic records can andcannot reflect about students. MIDFIELD leaders point to the value of qualitative research tofurther explore the quantitative findings [9]. Similarly, this paper represents the early quantitativestrand of a larger mixed-method project seeking to identify opportunities to support ECEstudents.The past few years have seen the engineering education research community grapple with thepotential contributions of educational data mining students’ academic
Mean St. Dev Mean St. Dev Non-Traditionally Underrepresented Students 3.510 0.426 29.30 3.797 Traditionally Underrepresented Students 3.236** 0.717 28.20 5.448 PMP-Eligible Students 3.161** 0.813 28.02 5.255 PMP Participants 3.343 0.546 28.46 5.782Significance reflects results of an independent samples t-test between non-TU students and TU studentsubpopulations. * p ≤ 0.05, ** p < .01, *** p < .005.Since RQ2 seeks to understand the relationship between participation in the PMP and studentacademic
, the simplicity of the project naturally yields the project to be used in awide variety of learning environments and student learners. When implementation does occur, the generatedresults would need to be studied and further modifications would be made to the teaching approach.Eventually, the module and learning materials along with the project will be made highly accessible toeducators through a centralized soft robotic teaching website being developed at Rowan University.AcknowledgementsThis material is based upon work partially supported by the National Science Foundation under Grant No.2235647. Any opinions, findings, conclusions, and recommendations expressed in this material are thoseof the authors(s) and do not necessarily reflect the
could be’, 2019, doi: 10.1007/s11186-019-09345-5.[26] S. Hunziker and M. Blankenagel, ‘Single Case Research Design’, Research Design in Business and Management, pp. 141–170, 2021, doi: 10.1007/978-3-658-34357-6_8.[27] R. H. Horner and J. Ferron, ‘Advancing the Application and Use of Single-Case Research Designs: Reflections on Articles from the Special Issue’, Perspectives on Behavior Science , vol. 45, pp. 5–12, 2021, doi: 10.1007/s40614-021-00322-x.[28] V. S. Athota and A. Malik, ‘Within-Case Qualitative Analysis’, Managing Employee Well-being and Resilience for Innovation, pp. 95–174, 2019, doi: 10.1007/978-3-030- 06188-3_5.[29] I. Halevi Hochwald, G. Green, Y. Sela, Z. Radomyslsky, R. Nissanholtz-Gannot, and O
lecture series program Q7. How did the [component] Mean 3.875 3.333 affect your sense of belonging in the research group? Std. dev. 0.696 0.471PALS surveyThe Patterns of Adaptive Learning Scales (PALS) survey is demonstrated in the literature toaccurately predict the motivation and persistence among students that engage in researchexperiences [15 ,11][19 ,18]. This instrument can assess the perceptions of student’s goals,which include orientations that are classified as mastery (or task), performance-approach, andperformance-avoidance. The revised scales were used in this study to reflect the adaptation of thePALS survey to measure goal
supported by the National Science Foundation under GrantNumbers 2346868 and 2144698. Any opinions, findings, and conclusions or recommendationsexpressed in this material are those of the author(s) and do not necessarily reflect the views ofthe National Science Foundation. We would like to express gratitude to Team Y for participatingin this study and for their willingness to open their meetings to us and provide feedback on theinitial drafts of this paper. We would also like to thank Dr. Nicola Sochacka for her insightfulfeedback and discussions as we analyzed our initial data. Finally, we would like to thank themembers of the ENLITE research team who gave feedback to the drafts of this paper.References[1] M. Borrego and L. K. Newswander
guest speakers from academia andindustry, individual homework assignments where students reflected on what they learned fromthe speakers, and a group project to design a sustainable human habitat on the planet Mars. InFall 2023, a new instructional team (1 lead professor, 2 undergraduate and 1 graduate courseassistants, and 1 education specialist) was mentored by an instructional team in the Chemical andBiological Engineering Department to redesign the course. The course redesign features twogroup socio-technical design challenges and weekly individual homework for students toresearch disciplinary sub-specialties and career opportunities. During the first month ofinstruction, students are oriented to campus, the major, resources within the
NationalScience Foundation research. Any opinions, findings, and conclusions or recommendationsexpressed in this material are those of the author and do not necessarily reflect the views of theOffice of Naval Research or the National Science Foundation.References[1] B. K. Townsend and K. Wilson, “A hand to hold for a little bit: Factors facilitating thesuccess of community college transfer students to a large research university,” Journal ofCollege Student Development, vol. 47, no. 4, pp. 439-456, 2006. [Online]. Available:https://doi.org/10.1353/csd.2006.0052.[2] D. D. Buie, “Beyond a deficit view: Understanding the experiences of first-generationstudents who participate in college access and success community-based organizations,” Ed.D.dissertation
has been known to significantly increase success, retention, and graduationrates. We noticed the differences in the level of preparedness and its influence on the student’sperception of their journey. We also explored the influence of soft skills, outlook, scholarlyattributes, and support on the perception of the journey through the program. Although ourparticipants have reported that they did not perceive any overt sexism or racism, we present thefindings correlated with gender and race/ethnicity.Our future work will include fine-tuning the protocol to explore intersectionality and reflect uponthe situations where the students might feel minoritized. Additionally, the students in the futurestudy will be purposefully selected to examine
CS.Next, the theme of collaboration was also found to be beneficial for students’ formation of bondsin CS. This result is reflected in prior work whose results suggest that the long-term impacts ofproject-based learning in STEM transcend traditional learning outcomes to also includeprofessional advancement and friendships [60]. Further, authors demonstrate that students’exposure to collaborative assignments are a significant, positive predictor of their persistence inCS [26]. Interestingly, however, the more recent work of Lehman et al. [32] found that students’exposure to collaborative pedagogy in introductory CS courses was a significant, negativepredictor for persistence. In their discussion, they suggest that the surprising result may
betelling of how students approach learning with the affective domain [14]. Also, returning to theidea that the domains are connected is reflected in the fact that many of studies found focus on twodomains at a time instead of only one domain at a time [4-7], [14-19]. Several studies exist thatresearch the domains, but they focus on testing a specific class within engineering or non-engineering majors [4-6], [9], [14-16], [18], [20]. Similarly, the studies that focus on math orchemistry classes may not have tested solely engineering students, which could still distort or skewresults towards conclusions that may not apply to engineering students overall [4-5], [21]. Theproblem with these studies is that their findings cannot be generalized for all
analyses at subsequent time points. For instance, if X students drop out orgraduate by the end of a semester, they will be removed from subsequent analyses, ensuring thatthe remaining students constitute the entire study cohort for subsequent persistence analyses.The study will acknowledge the dynamic nature of student enrollment, and robust measures willbe employed to handle attrition. The removal of students who exit the program will ensure thatanalyses reflect the evolving composition of the sample, contributing to the accuracy andrelevance of the findings.ConclusionIn conclusion, this study undertakes comprehensive exploration of the factors influencingengineering student persistence, with a particular focus on the impact of Calculus I. By
avariety of digital tools. Their choices reflect their degree of awareness and understanding ofavailable tools, showcasing whether they are acquainted with a diverse range of technologiesrelevant to the construction industry. On the other hand, assessing students' comfort levels inusing a specific digital tool provides insights into their confidence and self-perceivedcompetence. This subjective measure complements the objective evaluation of their toolselection, offering a holistic view of their digital skill awareness, confidence, and readiness toapply their knowledge.These scenarios were crafted to assess participants' knowledge of digital technologies and theirreadiness to apply them in practical construction scenarios. By presenting authentic
commitment to RT transformed into effective RT for communities 5 1.5 RT is not supported nor 2.5 Academic advisors can help students required by academic institutions circumvent institutional barriers to RTRT in Academic Research Program: Student Case Studies in HES @ MinesAs reported in our ASEE 2022 paper [1], graduate students’ journey to RT begins with an in-depth process of formation which includes a self-reflection of their perspectives as historical andsocial agents, extensive critical readings of the history of engineering, development, and the roleof engineers in development. Once they
efforts indiversity, equity, and inclusion were out of his scope. Initially, the researchers felt Omar’sresponses could have fit in broader systemic issues such as greenwashing or performativeallyship [34], [35], but in reflection following the interview process, the researchers felt Omarmight have been uncomfortable, or felt he was being assessed, leading him to look for the “right”answer. However, Omar perceived his work as separate from efforts in diversity or equity, the“science side of things.” Later in the interview, Omar also mentioned that he did not have a lot ofinvolvement with the Center outside of his lab, lab work, and advisor. Omar may not have beenexposed to the importance of inclusive or equitable practices in the way Zenith was
completed the survey near the end of each school term, with the Winter termsurveys completed in March 2023, and the Spring term surveys completed in June 2023. TheMECH-431 courses were complete by the time the survey was taken by enrolled students, so theywere able to reflect on the course as a whole at the time of completing the surveys.4.1 HypothesisResults are determined in this study by inductive reasoning. Based on the results of the literaturereview, it is clear that some dynamics systems and controls undergraduate laboratory courses atother institutions have effectively employed hands-on laboratory exercises at low cost. Therefore,a reasonable resulting hypothesis is that low cost physical laboratory experiments can beemployed effectively in
–student interaction data, where the frequency of online interactions proved to betterindicate student persistence and success than did the length of interactions. And the study by Aguiaret al. (2014) [14] predicted persistence using first‐year engineering students' electronic portfolios,extracting information about their course engagement through their reflections about engineeringadvising, project updates, and engineering exploration throughout the course. Using attributesrelated to student activities such as assignment skips, assessment performance, and video skips andlags to predict student dropout in online courses, while the study by Halawa et al. (2014) [15] wasable to successfully flag 40%–50% of students who dropped out of the course
scholarly pursuits, Ayodeji demonstrates a keen interest in engineering education. He has made significant contributions to his field through a prolific publication record and active participation in academic conferences. Possessing a diverse skill set, including strong communication abilities and analytical proficiency, Ayodeji is also an avid reader and enjoys nature. His trajectory reflects a commitment to continuous growth and making a meaningful impact within engineering and beyond.Dr. Emmanuel Okafor, King Fahd University of Petroleum and Minerals, Saudi Arabia Emmanuel Okafor holds a Ph.D. in Artificial Intelligence from the University of Groningen, Netherlands, specializing in computer vision, machine learning, and
) • Connectivity Problems (17 Voices) • Challenges and Obstacles of Virtuality (15 Voices) • Difficulties with Specific Content (9 Voices) • Personal Factors (6 Voices)Student statements about obstacles to learning during the course reflect an uneven adaptation tovirtual teaching. Challenges are associated with connectivity and understanding specific topics such asmathematics and circuit laws.3) What changes to the course could improve your learning? When analyzing the answers to thisquestion, the following emerging constructs can be seen (71 student voices) • Suggestions to Improve interaction (43 voices) • Request for More Practices and Activities (37 Voices) • Recommendations to Improve Communication (20 Voices)Below is a
questionnaire refers to emotions you may experience as part of this class (EGR 210 - Electric Circuits). It is divided into three sections: (a) your emotions related specifically to testing in this course, (b) your emotions related to Circuits class in general, and (c) your experience as part of the larger Engineering program. Please reflect on your experiences during this semester as you answer the questions below.* Required Unique Identifier 1. Copy and paste the unique identifier you received in your email: *Emotions during Electric Circuits testing and examsAttending college classes can create different feelings. This part of the questionnaire refers specifically to emotionsyou may experience during exams in EGR 210 - Electric Circuits. Before
limitation is mostlikely due to the FPGA’s ability to connect two ALMs during the routing process, where a wirewith a width larger than 1120 cannot be connected between two ALMs. The data we report onlygoes up to a maximum bit-width of 1024, so this limitation is not reflected in our graphs. Also,the Goldschmidt divider has a smaller range than the other dividers because it was not able tosynthesize above a width of 244. This is due to the limited number of DSP blocks.4.1 AreaThe FPGA used in these tests is the 5CGXFC9E7F35C8 from the Cyclone V line. This FPGA ischosen due to its large amount of available ALMs and DSP blocks. The maximum ALMs that ourFPGA has in this study is 113,560. Very few dividers in this study approached this maximumnumber of
standard deviation and the number of participants for each semester. The Likert-scale used in the surveyconcepts across various ranged from "Excellent" (5) to "Poor" (1), enabling participants to rateinstructional delivery formats. The their perceptions regarding the effectiveness of the take-home kits ormodules' effectiveness is widely desk-scale modules in aiding their understanding of theoretical concepts underlying physicochemical phenomena and unit operations.acknowledged among students,reflected in small standarddeviations. Emphasizing the importance of face-to-face components in blended learning, thesemodules received high
results from the preceding analysis,including further interpretation of the results, and propose some possible explanations.Beginning with demographic variables, Asian students reported stronger beliefs in the value ofcollaborative learning compared to white students. This may reflect cultural differences inlearning styles, or the value placed on group harmony and collective effort. Additionally,Mechanical Engineering (ME) and Industrial Engineering (IE) students showed lowercollaborative learning beliefs compared to their counterparts in Electrical and ComputerEngineering (ECE). These findings suggest that there may be disciplinary differences in thevalue and integration of collaborative learning in different degree programs.Turning to other
gender choice of “Other”was excluded due to the limited number of degrees awarded, reported only for 2019. Our“Native” category reflects combining the racial reporting options of “American Indian/AlaskaNative” and “Native Hawaiian/Other Pacific Islander.” Similarly, our “Multi” category reflectscombining “Foreign,” “Multiracial,” and “Unknown.” Other racial categories are used asreported by ASEE (e.g., “Asian,” “Black,” “Hispanic,” and “White”). Procedurally, the data was first downloaded into a CSV file. A self-generated Jupyter filewas created to clean the data and create the tidy format [21] XLSX files needed by Tableau forcreating the infographics [11]. Once the charts were styled with shapes, colors, and categorieschosen for visual