,” 2020.[12] E. Dorn, B. Hancock, J. Sarakatsannis, and E. Viruleg, “Covid-19 and learning loss - dispar- ities grow and students need help,” 2020.[13] M. Kuhfeld, J. Soland, B. Tarasawa, A. Johnson, E. Ruzek, and J. Liu, “Projecting the poten- tial impact of covid-19 school closures on academic achievement,” Educational Researcher, vol. 49, no. 8, pp. 549–565, 2020.McGill, Thompson, et al ASEE 2022[14] O. M. Oyinloye, “Possible impact of covid-19 on senior secondary school students’ perfor- mance in science education in nigeria,” Journal of Pedagogical Sociology and Psychology, vol. 2, no. 2, pp. 80–85, 2020.[15] E. J. Sintema, “Effect of covid-19 on the performance
]. However, performance on an assignmentmight not necessarily reflect a student’s understanding of the specified topic or their participationin class. Traditionally, homework assignments have taken on many forms: projects, readingprompts (in selected articles or chapters from a textbook), or responses to question from a givensource [3]. In recent years, however, many qualities of the homework format have been altered.These aspects include digital submissions or digital assignments entirely. Students have reportedhigher scores from these digital methods, but previous data analysis suggests there are nodifferences between this and the physical forms of homework [32]. Furthermore, these studiescritique the simplicity of these digital characteristics
engineering courses and enjoys working with his students on bridge related research projects and the ASCE student chapter.Benjamin Z. Dymond (Associate Professor)David A Saftner (Associate Professor) Dr. David Saftner is an Associate Professor in the Department of Civil Engineering. He earned a BS from the United States Military Academy and an MS and PhD from the University of Michigan. Prior to pursuing a career in academics, Dr. Saftner spent five years as an engineer officer in the US Army and serving in Missouri, Colorado, Kuwait, and Iraq. His areas of research include beneficial reuse of waste soil material, geotechnical site investigation and characterization, and teaching and learning in engineering education. He
. Some studies suggest that students who are membersof racial/ethnic minority groups underrepresented in engineering will have more awareness ofsocial problems [55], [56]. However, a study by Bielefeldt applying the PSRDM failed to findsignificant differences among engineering students of different racial/ethnic groups [52]. Thus,we do not have clear expectations regarding the relationship between the race/ethnicity ofcomputing students and social responsibility attitudes, although we include these variables in ouranalysis.3. Data and methods3.1 Survey methodsThis study, which is part of a larger research project, draws on data from a survey instrumentcompleted by five cohorts of students at or near graduation from the Georgia Institute
in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.Citations[1] R. A. Cheville and J. Heywood, “The Philosophical Foundations of Technological and Engineering Literacy,” in American Society for Engineering Education, 2017, p. 19530.[2] “Charles Sturt University - Our Ethos.” [Online]. Available: Our ethos.[3] J. H. Newman, The Idea of a University Defined and Illustrated: In Nine Discourses Delivered to the Catholics of Dublin. Project Gutenberg, 1852.[4] P. Dias, “The Engineer’s Identity Crisis: Homo Faber or Homo Sapiens?,” in Philosophy and Engineering: Re ections on Practice, Principles and Process, D. P. Michelfelder, N. McCarthy, and
qualitative case study research project sought tounderstand the nature and quality of STEM doctoral mentorships at an HBCU. The analysis onthe HBCU subcase asked, how are STEM doctoral mentorships understood by Black STEMdoctoral students at HBCUs? Black STEM HBCU students were interviewed and completed amentoring competency assessment survey. In addition STEM doctoral students from threeuniversities also completed the survey. The qualitative data was analyzed using narrativeanalysis and the survey data was analyzed using descriptive and inferential statistics. This projectis part of a larger NSF AGEP sponsored research study.Research findings: The findings from this study expose that Black STEM doctoral students atHBCUs have not reached the
Graduate Research Fellowship (GRFP). Mariah is an openly disabled scientist and has a passion for creating equitable access to education for everyone. During her undergraduate studies, she developed an interest in studying mentorship of disabled individuals and initiated an ongoing research project with Dr. Halpern. In addition to her mentorship research, Mariah enjoys advocating for the disability community. © American Society for Engineering Education, 2022 Powered by www.slayte.com10 Tips to Make Your Course More Accessible and Inclusive to Disabled StudentsMariah L. Arral, Carnegie Mellon UniversityAbstractAbleism is a barrier to accessible engineering education
such assenior design. At the University of Toronto, Rottmann and Reeve [50] have developed a three-hour ethics workshop that introduces students to five different ethical frameworks and fourdifferent equity concepts. In an ongoing effort, Riley et al. [49] are studying the lessons learnedfrom social movements to bring about equity-oriented changes in engineering education andhave collected teaching resources at engineersshowup.com. The Partnership for Equity (P4E)project has sought to incorporate diversity, equity, and inclusion lessons in requiredundergraduate engineering and computer science courses on four different campuses bycollaborating with engineering and computer science faculty [13]. Many of the P4E activitieshave primarily focused
teaching effectiveness is inherently problematic for a number of reasons, includinginability to disaggregate increases and decreases in performance in different areas, year-to-yearvariation in what the students enter with, difficulty insuring exams test the same thing and at thesame level each year, and possible instructor bias that leads to grade inflation. The absence ofstandards at the university level is unfortunate, as they have substantially enhanced formativeassessment and descriptive feedback in K-6 education [1].Since the present study was not (at the outset) intended as a formal educational research project,many of the methods used by educational researchers to document teaching effectiveness, suchas tracking individual student
-conceptual, or execution errors. Recommendations areprovided for instructors to address these common errors during future delivery of the coursematerial. Some of the errors identified suggest misconceptions; a future research project will bedesigned to help identify why some misconceptions may exist.INTRODUCTION AND BACKGROUNDEngineering mechanics provides foundational concepts that students apply in advancedengineering courses. For example, structural analysis requires a strong knowledge of staticequilibrium. Confidence calculating flexural stress and strain through the depth of a cross-sectionis critical when learning structural steel and reinforced concrete design. Ideally, prerequisiteengineering mechanics concepts are mastered and retained as
, and equitable workloads to increase efficiency and effectiveness (c) Solicit and incorporate feedback from, and provide constructive feedback to, team members and other stakeholders (d) Evaluate and select technological tools that can be used to collaborate on a project 3. Recognizing and Defining Computational Problems (a) Identify complex, interdisciplinary, real-word problems that can be solved com- putationally (b) Decompose complex real-world problems into manageable sub-problems that could integrate existing solutions or procedures (c) Evaluate whether it is appropriate and feasible to solve a problem computationally 4. Developing and Using Abstractions (a) Extract
vignette video: “Names and history are almost non-existent inour engineering courses, and numbers and equations are actually what we deal with….” Thus,the participant focuses on using engineering for new innovations and acknowledges that ahistorical lens is not used in the engineering curriculum at the institution he attends. Participant 65 mentions his experiences with HC. He notes that in his senior design class,the “…instructor specified that the senior project leaders could not be White males. . .which wasprobably the biggest show of racism I have seen on campus.” Additionally, the participantdescribes that his “biggest personal obstacle has been being a father during undergraduate andgraduate work,” and “it can sometimes be frustrating
in an existing system are easily understood as therules are assembled by the system developer. Furthermore, such an approach does not require thelarge training corpus of responses employed in state-of-the-art machine learning approaches tosemantic analysis [12]. Two potential drawbacks of the rule-based approach are that a domainexpert is needed to create the rules that govern the analysis of text, and the rules generated for oneproblem will not necessarily apply to other problems. As the overarching idea of the web-basedwriting exercise project is to create a template that instructors are able to use to construct their ownwriting exercises, these are not considered serious drawbacks. Naturally, as the amount of data inthe form of student
Paper ID #38724Analysis of Learning Assistants’ Beliefs of Status and Their Role asStatus InterventionistsHarpreet Auby, Tufts University Harpreet is a graduate student in Chemical Engineering and STEM Education. He works with Dr. Milo Koretsky and helps study the role of learning assistants in the classroom as well as machine learning applications within educational research and evaluation. He is also involved in projects studying the uptake of the Concept Warehouse. His research interests include chemical engineering education, learning sciences, and social justice.Dr. Milo Koretsky, Tufts University Milo Koretsky is
Paper ID #38909Motivation and Evidence for Screen Reader Accessible Website as anEffective and Inclusive Delivery Method for Course Content in HigherEducationDr. Vijesh J. Bhute, Imperial College London Dr. Vijesh Bhute currently leads 1st and 2nd year modules on Mathematics in the Chemical Engineering Department at Imperial College London. He leverages technology to enhance delivery of abstract con- cepts and also uses math-aware assessment platforms to improve student learning. He collaborates with students on various projects and has also contributed to development of innovative hybrid experiential learning approaches
notrestricted to computing students. While non-computing STEM majors suffer from the same lackof representation, it is important for researchers in computing to understand discipline-specificperceptions and experiences. Finally, the study did not account for other student identitiesoutside of race and gender. This excludes more nuanced analysis of results, based on multipleforms of oppression that students may (not) experience [21]. In addition, the computingcommunity lacks significant data collection efforts related to students with disabilities,highlighting the need to account for this important (and often overlooked) identity [22].This work-in-progress paper is situated within a broader ongoing project that seeks to answertwo research questions
had completed comprehensive safety training experiences were 49% lesslikely to have had an accident occur in their courses [5]. However, of greater concern are thebroader impacts of safety deficiencies modeled for students in P-12 since research suggests thatstudents often implement these safety habits in post-secondary programs and the workplace.Utilizing data from a national safety research project involving 718 P-12 educators from 42states in the U.S. [3], this study examined results from a subsample of 381 educators whospecifically reported teaching pre-engineering or engineering design (PE/ED) focused courses.The goals of this study were to examine how PE/ED courses differed in terms of accidentoccurrences in comparison to other P-12
. AcknowledgementsThe authors would like to thank Dr. Sanjay Rebello, Dr. Carina Rebello and Mr. Amir Bralin fortheir support with the design of the learning materials and the project logistics. This work waspartially funded by the National Science Foundation under Grant No. DUE 2021389. Anyopinions, findings, and conclusions or recommendations expressed in this material are those ofthe author(s) and do not necessarily reflect the views of the National Science Foundation. References[1] S. Papert, Mindstorms. Children, computers and powerful ideas. New York, NY: Basic Books, 1980.[2] J. M. Wing, “Computational thinking,” Commun. ACM, vol. 49, no. 3, pp. 33–35, 2006, doi: 10.1145/1118178.1118215.[3] A. Çiftçi and
, FFChopes to create enough fidelity in the systems that, when it puts them all together, the overalleffect will be substantial. With support from the local and state governments, FFC has been able to acquire significantagricultural land to experiment with different technologies and crop varieties to find the best wayto farm autonomously. Established in 2015, FFC took some time to ramp up, as autonomousfarming is a complex undertaking that requires not just the use of automation technology,including devices, platforms, and services, but also associated scientific development forimproving crop health and productivity. Consequently, projects currently underway at the FFCTest Site include soil health monitoring, uncrewed aerial systems, uncrewed
representation. For example, lecture content could be presented in a video or a text file of audio transcription. • Multiple means of expression. For example, students are allowed to demonstrate the course project through written report or oral presentation. • Multiple means of engagement. For example, students can ask questions and share opinions in the classroom or through the online forum.2.3 Active Learning Active Learning is a well-known and widely studied set of educational practices and prin-ciples that suggests students create higher order knowledge and understand more effectivelywhen they engage in learning activities that are beyond passively receiving information[6].Active Learning is supported by
self-efficacy is understood to be driving self-perceptions and eventually performance in those tasks. For instance, self-concept in calculus (i.e., a domain) can be expressed as “I am able to understand and follow along the calculus classes”, and self-efficacy in calculus (i.e., task performance) can be expressed by “I am confident I can score at least a B in the upcoming test”.The above definitions for both constructs are adapted from previous research and validating orverifying them is not within the scope of this project. This study agrees with previous findings[7], [44], [45], [46], that state self-concept is a prime predictor for favorable academic outcomesand well-being as a student. Self-efficacy, although crucial for an individual’s
notes, emails, and medicaldocumentation to create my autoethnography [28], [32]. After building the phenomenology andautoethnography, I triangulated the results. Triangulation is the use of multiple sources ofinformation to build a coherent justification of themes based on convergence [27]. Using amixed-method approach with Harvey’s process allowed me to use two strategies to check thequalitative validity of the results. Qualitative validity refers to the consistency of the researcher’sapproach across data sources, methodologies, and projects [27].Results and discussionOnce I completed the data collection and analysis portion of the broader study, I met with twocontributors. Both contributors were previously authorized by the University of
Machine Learning, he has authored four books (Shale Analytics, Data-Driven Reservoir Modeling, Application of Data-Driven Analytics for the Geological Storage of CO2, Smart Proxy Modeling), more than 230 technical papers and carried out more than 60 projects for independents, NOCs and IOCs. He is an SPE Distinguished Lecturer (2007 and 2020) and has been featured four times as a Distinguished Author in SPE’s Journal of Petroleum Technology (JPT 2000 and 2005). He is the founder of SPE’s Technical Section dedicated to AI and machine learning (Petroleum Data-Driven Analytics, 2011). He has been honored by the U.S. Secretary of Energy for his AI-based technical contribution in the aftermath of the Deepwater Horizon
bachelor’s degree at Rowan University in New Jersey before attending graduate school for her PhD at the University of Massachusetts in Amherst, MA. Her research interests in- clude engineering communication, process safety, and undergraduate student mental health. Recently, she was awarded an NSF RIEF grant to student mental health-related help-seeking in undergraduate engineer- ing students. She is completing this project in collaboration with faculty members from educational and counseling psychology. With this work, they aim to better understand the help-seeking beliefs of under- graduate engineering students and develop interventions to improve mental health-related help-seeking. Other research interests include
organized concept maps.Assessment Administration Time and Details Provided. Lavi et al.’s [23] assessment had oneof longest administration times with teams submitting their first version of their concept modelsmid-semester and a second version at the end of a semester. With more time, came more levelsof detail as the first conceptual model had to have at least three levels of detail and the secondmodel had to have four or five levels of detail (see “complexity levels” in “Identifying IndividualElements” above). Rehmann et al.’s [27] assessment took place over seven weeks, or half of onesemester, with instructors providing feedback to students on one part of their projects each week.With more time, came more details about a system. In the case of
team hasconducted a research project that provides the environment and its accompanying diverseresources to different universities in North America and South America. In Spring 2016, Prime(pseudonym) University decided to use Freeform for an undergraduate dynamics course.The goal of this study was to examine how students perceived the Freeform learningenvironment at Prime University, whose school context differs from that of Purdue University.Much research has focused on estimating the quantitative impact of educational interventions(especially curricular) on student learning outcomes. However, previous research has paid lessattention to how students perceive the potential affordances of the learning environmentassociated with an intervention
different groups. Such training could promote understandingand cooperation between individuals from different national and cultural groups, contributing tothe success of international engineering projects and technological work.Since this study was exploratory in nature, it suffers from numerous shortcomings that will beaddressed in future work. The sample used in this study was relatively homogenous and notentirely representative. Going forward, future research will use different, more diverse studentsamples.References[1] C. E. Harris, M. Pritchard, M. Rabins, R. James, and E. Englehardt, Engineering Ethics: Concepts and Cases, 6th ed. Cengage Learning, 2018.[2] M. Martin and R. Schinzinger, Introduction to Engineering Ethics, 2nd ed. New