Engineering: Origami bridges, building, structures would soon be possible.Hands on experience: Folding a printer paper and making a basic miuri ori fold: The instructordemonstrated the miuri-ori fold and the students followed. It is a relatively challenging fold tomaster and students needed a couple of hours to complete the fold.Test: The students stacked books on the folded paper and tested to see when it would fail. Thiswas done on zoom and students cheered as others tested their structure.Analysis and Discussion: There was a discussion on why some of the structures could hold up to7 lbs. Other concepts were demonstrated like 1. Poisson’s ratio was negative.breaFig 2. Summary and Reflection Assignment -Student 1 Fig 2
of HCD in existing engineering courses.Several research studies included the integration of HCD in existing engineering courses such asmechanical engineering [12] and electrical engineering [13]. The integration was guided by anevidence-based human-centered engineering design (HCED) framework that merges the HCDprocesses with the engineering design processes and lists a set of practices that students canimplement within the context of a design project [11]. These processes are understanding thechallenge, building knowledge, weighing options and making decisions, generating ideas,prototyping, reflecting, and revising/iterating. Research studies indicate that learning about theseprocesses and implementing them in the context of a design
additional question was added related to ChatGPT,which had risen to prevalence in that time. 5. I think I will need to use ChatGPT at some point in my career.In addition to the MATE 245 class, in the summer of 2023, two undergraduate research studentswere employed to aid in the development of the plastic 3D printing dataset and case study. Thesestudents spent 8 weeks working on developing the 3D printing case study in the Citrine Platform.During this time the students gained more in-depth knowledge of AI and ML through guided andindependent research. The students were invited to provide prompt-based written reflections ontheir understanding and perceptions of ML and how it might be applied to their future careers.Preliminary Findings and
teaching styles tend to rely on thedissemination of fundamental concepts in a lecture-style format with limited learner stimulation,active and experiential learning approaches prioritize both learner engagement and reflectionthroughout and often include lesson contextualization [9], [10].Although sometimes used synonymously, active learning and experiential learning are twoseparate pillars in modern education. The most widely accepted and cited definition of activelearning is provided by Bonwell and Eison in 1991 as: “Involving students in doing things andthinking about what they are doing [6].” Millis further elaborates on this definition and adds thatit often involves reflection and doing or taking action, and often uses cooperative
resultsseem to suggest there might be a favorable bias in the sections taught by the faculty in the videos(502 and 503).End of Semester SurveyA survey was created and administered near the end of the course that asked students to reflect onthe course. The questions aimed to assess if the students were enthusiastic about the course, if thecourse helped in solving real-world problems, and if the students were interested in pursuing amaster’s or doctoral degree in the subject area. For comparative purposes, this survey was firstadministered as a baseline survey in a section of the course that did not implement the videos inFall 2021, when significantly fewer students took this course (off-schedule group). The results areshown in Figure 2. Students
small minority (3.8%) felt that the speakers did not effectively address sustainabilityconsiderations. It is worth noting that a majority of respondents felt that the industry speakerseffectively addressed sustainability which indicates that students value industry's responsibility inpromoting sustainable practices. This suggests that students are not only interested in learning aboutthe technical aspects of materials processing but also in understanding the environmental and socialimplications of these processes. Figure 4: Survey response when asked if the industry speakers address sustainability effectively in their respective fields (Q.4)The last question on the survey was a reflection prompt that students provided their commentson
meanratings from the project-based sections. Results are presented in Table 1 below. Note that thelecture content across all course offerings was essential the same, it was the method ofassessment that differed.Table 1. Statistical analysis of student ratings for assessment practices and course impactcomparing a lecture-based version of the course to a PBL version Category Title Question t-value p-value Assessment Relevance of The assessments/assignments 4.62 0.000853 Practices assessment reflected what was covered in the course. Grading The grades I have received thus 3.13 0.00703
populations.As the institution being studied, the junior-level MSE lab courses have robust computational modelingand simulation curricular content. Our findings therefore suggest a strong positive impact that frequentuse of simulation tools in MSE courses can have on students’ attitudes toward these tools in the contextof engineering work. However, because we did not directly measure students’ actual competency, butonly their self-efficacy, it is not clear whether their lack of confidence with these tools accurately reflectsa low level of proficiency or whether it reflects a greater level of appreciation of the complexity of thesetools, which novices would not appreciate. It would be valuable for a future study to examine therelationship between actual
inventory of the subject matter based on the learning materials shared hitherto,and to enable the formation of new home groups. The post-lecture test was administeredafter the teaching sessions facilitated by the group champions (experts) after the jigsaws.It was found that integrating the jigsaw classroom into the materials science lessons waspositive as reflected in the performance of the student’s post-lecture. The results showedthat all the students that participated in the post lecture tests scored above 50% of the totalscore as compared to scores reported during the pre-lecture assessment. The increase intest scores post-lecture can be ascribed to the improvement in learning methods based onthe activities in the jigsaw groups proving the
CHALLENGING CALM(HCP). The module consists of a short introductory video and three lengths of interactivelectures with embedded pop-up low-stake questions for students to choose. Then students areguided to CMR questions as described earlier. Based on their performance, students may bedirected to a set of short supplemental interactive videos. All students then continue with a morehands-on simulation instructional tool (3D Crystal Builder,https://conceptwarehouse.tufts.edu/cw/crystalVL/) and reflection activities before beingpresented with a resources review page. Lastly, students work on adaptive summative assessmentwith various difficulty levels of concept questions and a survey. More details of the structure andcomponents of the CALM was previously
, for the instructor, formulating questions that elicit appropriate mental processing on thepart of students is undoubtedly also difficult. The authors wrestled with finding a mechanism to motivate students to conceptunderstanding, and eventually they came up with some ideas. First, it was decided to designassignments for students requiring them to provide answers to concept-related questions.Answers would be in the form of written descriptions, explanations, and definitions, and couldbe recorded/reported on digital devices such as a laptop, iPad, smartphone, etc. Generatinganswers would require some mental activity for the student; some reflective thinking andpondering, more than just memorization. Grading of answers would be based on
,having familiarity with search engines and open AI. This is reflected in the highest self-evaluation scores even before the lab session commenced. The lab strategically incorporateddatabases from the college library, highlighting their importance for finding peer-reviewedpublications and ensuring proper citation in reports. Most students observed an improvementin learning skills through lab practice, with only a couple having prior experience in search andcitation. Communication, Poster, & Data: Sophomore students already had experience aboutoral presentation, which includes poster presentation, data processing in the freshman year fromtheir intro to engineering course at Union college. Students feel they already come with a
and discussion of the tools purpose anduse.Together, we leverage both of positionalities to analyze and disseminate this review in a way thatwould be of interest to both the materials engineering community and the engineering educationcommunity. Specifically, we engaged each other in reflexivity to ensure the study would beaccessible to both communities.Literature Review MethodsWe utilized a combination of a systematized review and scoping review methodology to examineengineering tools available to teach particle science fundamentals. Our research questionsreflected a scoping review and the querying and reviewing method reflected a systematizedreview, all established by Borrego et al. [6] and Grant & Booth [7]. As recommended, weutilized
conditions. The numbers in the gray boxesalong the top row reflect the boiling points of 5% and 10% sulfuric acid solutions, respectively,which are higher than the boiling point of water.Once one tabular graph is shown, there is no need Titaniumto repeat the numerical headings on subsequentgraphs. We can make smaller graphs using thesame grid pattern to help compare one materialwith another. This smaller graphic shows thattitanium is good at low concentrations of sulfuricacid at all temperatures, while it corrodes readily athigher concentrations at all temperatures.Colored graphical tableexample: FormingProcesses for StainlessSteelsThe previous examplesincluded tables usingsymbols or numbers.This table from Vol. 14of the ASM
Employers Students 0.0 20.0 40.0 60.0 80.0 100.0 Very well prepared Well prepared Fairly prepared Somewhat prepared Not at all prepared Don't know/unsureFigure 1. Overall sentiment about the preparedness of Materials Engineering graduates in theMaterials Science and Engineering industryThe stakeholders were further asked to reflect on the relevance of key knowledge and skillsobtained from Materials Engineering degree (i) when applying for jobs and (ii) in relation tothe actual duties performed in their roles. a. Relevance of key knowledge and skills obtained
both undergraduate and graduateeducation should reflect that change [1], [2], [3]. This commitment to a shift in the educationalapproach within MSE departments is highlighted in the strategic plan of the National Scienceand Technology Council’s Materials Genome Initiative, which posits that the next generation ofthe MSE workforce will need to master three competencies: experimentation, data management,and computation [4].MSE educators have worked to construct educational offerings that develop competencies in theareas identified by the Materials Genome Initiative. Several departments have developedcomputational courses or add-on computational modules for existing courses [5], [6], [7], [8],[9], [10]. However, while inroads have been made in
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