proven to promote the understanding of STEM concepts, increase testscores, improve technical communication skills, encourage participation in constructivistlearning activities and manage cognitive load for difficult subjects [1] - [9]. In engineeringeducation, the benefits of tangible objects have been predominantly studied in subjects likedesign. Studies have shown that engagement with mechanical objects improves students’performance on producing assembly instructions, students are more engaged and in-control oftheir learning helps with transforming their conceptual knowledge into ideas for product design[1]. Engineers are surrounded by physical artifacts throughout their education and work-placeenvironments. Our research project
observationalprotocols of the games being played. Observational studies (phenomenography, for example) willbe used on the students in classes that include the game-based ethical interventions - to explore thequalitatively different ways in which the students are realizing, conceptualizing, and understandingthe various aspects of the play experience. Follow-up debriefing sessions will also be conductedto further elucidate underlying play aspects that may contribute to developing ethical reasoning.Pre/post tests using the EERI and DIT2 will be carried out on game and non-game student groups(similar to Year 1). Demographic analyses of the results will also be performed at this stage todetermine how the game-based ethical interventions impact various demographic
into an REU Site in the U.S. SouthIntroductionParticipating in a research experience for undergraduates (REU) site provides opportunities forstudents to develop their research and technical skills, raise their awareness of graduate studies[1], and understand the social context of research [2]. In support of this mission, our REU site atThe University of Alabama (Sensors, Systems and Signal Processing Supporting SpeechPathology) is exploring research at the intersection of engineering and communicative disorders.Our site has a focused theme of developing technology to support clinical practice in the field ofcommunication sciences and disorders; which is an applied behavioral science that includesscreening, assessment, treatment, and technology
project are the formalized opportunity to continue to engage in the discipline byproviding professional expertise and to contribute to a more diversified next generation ofengineering faculty.The mentoring and advocacy-networking paradigm was developed through an extensive reviewof the literature across disciplines with a targeted focus on diverse mentoring relationships inscience, technology, engineering, and mathematics fields (Johnson, 2015; Kram, 1985; Zellers,Howard, & Barcic, 2008). The model moves beyond advisory mentoring to include professionalnetworking and advocacy by emeriti faculty who are uniquely situated to provide theseresources. The new paradigm encompasses three domains of mentorship: (1) career development(emeriti faculty
Fall was tracked, but not used to form teams in the Spring, resulting in teams composed of students who received various training protocols in the Fall. This will make it possible to measure the effect of various training and feedback interventions on student's ability to rate their teammates, perform in teams, and effects on a variety of other outcomes including conflict, cohesion, and satisfaction. These follow‐on data have not been fully analyzed yet due to the loss of a research team member. Measures of improvement resulting from interventions There are two main challenges in assessing the quality of peer evaluations: (1) when used in real teams, there is generally no true score available because the team was not observed by an external
spacing also has the potential to enhance long-lasting memory in other STEMfields wherein success depends on the cumulative acquisition of knowledge.AcknowledgmentThis material is based upon work supported by the National Science Foundation under Grant No.DUE – IUSE – 1609290.References[1] D. R. Bacon & K. A. Stewart, “How fast do students forget what they learn in consumerbehavior? A longitudinal study,” Journal of Marketing Education, vol. 28, pp. 181–192, Dec.2006.[2] M. A. Conway, G. Cohen, & N. Stanhope, “On the very long-term retention of knowledgeacquired through formal education: twelve years of cognitive psychology,” Journal ofExperimental Psychology. General, vol. 120, pp. 395–409, Dec. 1991.[3] F. U. Kamuche & R. E. Ledman
school teachers andcommunity college faculty who will develop skills in manufacturing research, technical writing,curriculum development, and conference presentation. The goals of the proposed program are to:1) provide a STEM-based platform to engage high school teachers and community collegeinstructors in state-of-the-art manufacturing research, 2) explore a sustainable educational modelthat connects high schools, community colleges, university, and industry to instill futuregenerations with greater awareness and interest in manufacturing, 3) facilitate the developmentof curricular modules, classroom activities, and other instructional materials that will beimplemented in the participating schools and colleges eventually to be disseminated to a
Society for Engineering Education, 2019 Sustaining Change: Embedding Research Outcomes into School Practices, Policies and NormsWith an NSF Revolutionizing Engineering and Computer Science Departments (RED) grant, theSchool of Chemical, Biological and Environmental Engineering seeks to create (1) a culturewhere everyone in the CBEE community feels valued and that they belong, and (2) to create alearning environment that prompts students and faculty to meaningfully connect curricular andco-curricular activities and experiences to each other and to professional practice. We aim tohave students connect what they learn to the context of their lives, identities, and emergingcareers. We want CBEE graduates to be
4 3 2 1 0 C or Better C- or Worse GradeFigure 4: Performance of 2009 Summer Bridge Students who placed into Intermediate Algebrafor the Fall 2009 semester.When analyzing all of the results, it must be remembered that the sample sizes are small in eachsubcategory, and so most of the focus will be on the general observations in the results. First,considering the results from Calculus I as shown in Figure 2, there are two categories of studentsto be considered: one group placed
ratings.MaterialsComputerized materials Each participant received the computerized materials consisting of an interactive programthat included the following sections: (1) a demographic information questionnaire in which Page 25.1121.6students were asked to report their gender, age, and ethnicity; (2) a pretest; (3) an instructionalsession providing a conceptual overview of electrical circuit analysis; and (4) a problem-solvingpractice session. The pretest consisted of 12 multiple-choice questions (internal reliability of .79). It wasdesigned to measure the participant’s knowledge of the topic before entering the instructionalsession. The instructional
Figure 1. The center path(blue boxes) represents the elements pertaining to content shown to the student as well as inputrequested of the student. The green boxes to the right of the center path represent instances inwhich the application applies a method to infer meaning from a student’s response. The greenboxes to the left of the path represent locations at which a set of rules are employed to identifyinstances in which a student’s language is suggestive of metacognitive activity. The semantic andmetacognitive reviews are described in a subsequent section. As portrayed in Figure 1, a writingexercise begins with a brief introductory statement to provide the student with the general ideabehind the question’s underlying concept. The two writing
Professor and the Department Chair in Electrical and Computer Engineering at the University of California, San Diego. His research has led to more than 200 journal and conference publications, including a number of Best Paper awards and nominations. He also holds five awarded patents. He has been the General Chair and on the executive and technical program committee of many IEEE and ACM conferences, and he has been Associate and Guest Editors for several IEEE and ACM journals. ©American Society for Engineering Education, 2024 Toward understanding engineering transfer students' transitions from community colleges to 4-year institutionsAbstractCommunity college students
their rolesfor the next cycle of questioning and answering interaction.To facilitate students to ask thought-provoking questions for different roles at different phases ofsocial and cognitive process, social interaction oriented prompts developed by educationalresearchers are provided to students through both the online system and collaborative learningassignments before their collaborative learning, aiming to help students to generate thought-provoking questions for their online discussion. Those adopted prompts include social interactionprompts 24 in Table 1 (left side), question stem prompts developed by King 5, and inquiryprompts developed by Swan and Pead 17 and adopted by PRIMAS (http://www.primas-project.eu). Students are required to
-guided student learning [1],[2]. This is especially true within engineeringand other STEM topics due to the complexity of the material. A large amount of both researchand school curricula generally adopts a one-size-fits-all approach [3],[4]. While easilyimplemented and generally best for all students, a number of students are still left behind whentheir ideal learning approaches deviate largely from the standard. Further, some students can lackmotivation or prior knowledge, negating any benefits that exploration-based learning might havefor them.Another recent trend within engineering education is a focus on problem-based learning (PBL)[5]. This approach engages students in a learning process through the use of one or severalreal-world problems
groupswere evaluated using a series of quantitative formal assessments which include conceptinventories and homework, quiz, and exam grades. Qualitative data was also collected throughfocus groups for both groups to gather the students’ impressions of the programs for theexperimental group and general teaching styles for the control group.Due to some issues with the server that runs Mechanix, the students were not able to properly useMechanix during the in-class evaluations. We believe that this caused the results to show thatthere was no change in the homework and concept inventory scores between both groups for thecurrent evaluation. However, the results show that Mechanix is a capable tool for enhancingstudents learning and performance in exams
development community about the model-basedenterprise (MBE). The MBE could provide significant opportunities for efficiency andeffectiveness in product development 1. At the core of the MBE are computer-aided design(CAD) models that allow for the more efficient completion of tasks associated with productdevelopment. These include computer-aided engineering simulations, computer-aidedmanufacturing processes and other manipulations of the digital artifacts. CAD models combinedwith product lifecycle management (PLM) systems have long been proposed as providing greatbenefits 2. However, these benefits are predicated on the ability of CAD models to be easilyreused and understood by the various actors across the commercialization process. This requiresa
fresh-man level, students will be engaged in the scientific discovery process using exciting hands-on designchallenges to analyze artificial organs. In more advanced core engineering courses and laboratories, stu-dents will explore the function of artificial organs in the laboratory and investigate the variables affectingtheir performance. The engineering goals of this project are: (1) to explore the function of human and artificial organs; (2)to apply current research methodology state-of-the-art medical devices for a hands-on investigation ofartificial organs; and (3) to introduce fundamental engineering principles through experiments with artifi-cial organs; (4) to investigate the factors affecting artificial organ performance and design
district policies—teachers successfully introduced foundational ML principles through both formal instructional modules and informal classroom activities. This study contributes to the expanding body of STEM education research by illustrating practical strategies for empowering secondary educators to integrate machine learning and computational thinking into their instruction. The findings underscore the potential for in- terdisciplinary learning and the cultivation of critical thinking skills that are essential for preparing the next generation of STEM professionals.1. IntroductionSTEM (Science, Technology, Engineering, and Mathematics) fields are widely regarded as intellectually
entangled with the instructionaldesign [8], it is imperative for the instructors to keep technical staff updated the latestinstructional plan, so that they can use their domain knowledge to anticipate any technicalissue in advance and troubleshoot when the issues actually occur. In practice, it should becareful not to constrain the instructional design based on the technological capability. It wasinteresting to observe that, generally speaking, students were rather tolerant and patient withthose unexpected technical issues. This may be largely attributed to the fact that theparticipating students are all Millennials, who grew up with computers and the Internet.The course is coupled with some logistical complications with respect to academic
(Schilling, 2008). The above-mentioned indicates that there are quite a lot of difficulties part-time students may face during their graduate journey that may not be visible but can have effectson their graduate experience. There is a growing need for individuals with analytical and applied research skills in theknowledge-based economy. This knowledge-based economy is characterized as having areliance on knowledge, information and high analytical or technical skills (OECD, 2005). Theseattributes are typically associated with experienced individuals with Ph.D. educational levels(Cross, 2014). Thus, as a result, professional or non-traditional doctorate programs that supportnon-traditional students have arisen as one option for providing these
-Transistor Logic and CMOS:Complementary Metal Oxide Semiconductors) have been replaced by Programmable LogicDevices (CPLD: Complex Programmable Logic Devices and FPGA) [1, 2, 3]. Today, a morestandard development process is widely used in industry. The process uses Hardware DescriptionLanguages as a design entry to describe the digital systems. The two most widely used HardwareDescription Languages in industry are VHDL (Very High Speed Integrated Circuit HardwareDescription Language) and Verilog (Verifying Logic). Although most traditional electrical andcomputer engineering programs have updated their curriculum to include topics in hardwaredescription language and programmable logic design (FPGA/CPLD), two-year and four-yearelectrical engineering
the lowest quantitativestudent success rates, as indicated by our own Institutions’ DFW (D/F grade and withdrawal)percentages (Table 1). The inclusion and degree of experiential learning in Circuits varies by institution. Evenat schools where a laboratory course accompanies the lecture course, the laboratory assignmentstend to be straightforward demonstrations of the basic circuit principles discussed in the lectures.In our view, this approach cultivates the learning of little more than commodity skills. Moreover,it is generally viewed that the ability of U.S. graduates to successfully compete in our globalsociety depends on them possessing a broad, interconnected knowledge base. Integrating real-world problems into Circuits can
difficulty DHH students experience in developingthe critical skill of problem solving, which requires the integration of information to iterativelygenerate hypotheses and solutions around the traditional scientific method. The struggles thatmany DHH students face in mathematics as well as general problem-solving skills are well-documented and limit the potential for DHH students to be successful while pursuing careers inSTEM. 1-3Several important findings in DHH research have provided some insight as to why DHH studentslag behind their hearing peers in the development of problem-solving skills. First, DHHstudents, on average, do not possess the same level of conceptual knowledge as their hearingpeers.4-6 As a result, when faced with a problem
team of researchers at a Southwest Hispanic-Serving Land-GrantUniversity embarked on an National Science Foundation-funded study to provide workshops forfirst year engineering students to introduce them to metacognitive awareness learning strategiesthat have the potential to help their study skills, and in turn, their academic performance. Toassess if these strategies were utilized and if they were helpful for students, we collected pre- andpost-intervention surveys and reflective writing journals. The survey items came from themetacognitive awareness inventory (MAI) [1] to measure pre- and post-knowledge andregulation of cognition. These surveys were administered to the introductory level engineeringclasses at the beginning and end of their
concurrent shift in unitculture (e.g. values, norms, policies and procedures).Our project is structured around four pillars: (1) Curricular redesign and implementation of second- and third- year studio classes to include more realistic, consequential work via situated pedagogies like model-eliciting activities and problem-based learning; (2) Advancing faculty and staff capacity to engage issues of equity and inclusivity under the leadership and efforts of several new faculty/staff/student working groups; (3) Implementation of student professional development ‘Pods’ (self-forming student teams structured to be highly inclusive) where students can convene to better understand their curricular and co-curricular
applied mechanics, materials science and applied mathematics tocompute a structure's deformations, internal forces, stresses, support reactions under prescribedloads and/or other external effects [1], [2]. Despite its critical role in the curriculum, most novicelearners in this course do not appear to have a sound understanding of fundamental concepts,such as load effects and load path; and in general, they lack the ability to visualize the deformedshape of simple structures, a necessary skill to conceptualize structural behavior beyondtheoretical formulas and methods [1], [2]. In particular, students have difficulty in relating basicstructural members, including trusses, beams, frames, and others, to more complex structuralsystems, such as
Paper ID #17812Blended vs. Flipped Teaching: One Course - Three Engineering SchoolsDr. Renee M Clark, University of Pittsburgh Renee M. Clark serves as research assistant professor focusing on assessment and evaluation within the University of Pittsburgh’s Swanson School of Engineering and its Engineering Education Research Center (EERC), where her interests focus on active and experiential learning. She has 25 years of experience as an engineer and analyst, having worked most recently for Walgreens and General Motors/Delphi Automotive in the areas of data analysis, IT, and manufacturing. She received her PhD in
Engineering and Computer Science 4 Department Industrial and Operations Engineering 2 Mechanical Engineering 5 Materials Science and Engineering 2 Naval Architecture and Marine Engineering 3 Nuclear Engineering and Radiologic Sciences 1 Technical Communication 2Data and ResultsThe focus group data were transcribed and imported into NVivo for qualitative analysis, and wecombined both inductive and deductive approaches for our analysis (an
/operations to achieve enhancements in energy efficiency, improved safety,utilization of resources and reduction of capital costs, waste generation, and energy consumption.Process intensification involves thinking about chemical processing in new ways such that (1)recognition of inherent limitations imposed by using sequential unit operations to accomplishchemical and/or physical transformations is achieved; and (2) methods of concurrentlyperforming more than one unit operation are considered. This requires undergraduates to thinkin different ways about the processes they have learned about in their traditional unit operationscourses. Process intensification is essential to industrial competitiveness as it can enhancesafety, increase operating
education in instructional systems from Penn State, a master’s of education in computing in education from Rosemont College, and a bachelor of science in mathematics education from Penn State. Her research centers on the sustainability of innovations in education.Dr. Amy Freeman, Pennsylvania State University, University Park Amy L. Freeman is Assistant Dean of Engineering Diversity at the Pennsylvania State University, where she received her Ph.D. in workforce education and her M.S. in architectural engineering. She is Co-PI on the NSF-Sponsored Toys’n MORE grant and currently manages several retention programs targeting more than 2,000 women and underrepresented technical students at all levels of the academic and career