University Press, 2014).6. Clements, D. H. Curriculum research: Toward a framework for ‘Research-based Curricula’. J. Res. Math. Educ. 38, 35–70 (2007).7. Dym, C., Agogino, A., Eris, O., Frey, D. D. & Leifer, L. J. Engineering design thinking, teaching, and learning. J. Eng. Educ. 94, 103–120 (2005).8. Daly, S. R., Adams, R. S. & Bodner, G. M. What does it mean to design? A qualitative investigation of design professionals’ experiences. J. Eng. Educ. 101, 187–219 (2012).9. Bannan-Ritland, B. The Role of Design in Research: The Integrative Learning Design Framework. Educ. Res. Page
Total 248 (64%) 138 (36%) 386Figure 2 shows the population breakdown by major. Students could report multiple majors, thusthe total count here is greater than our population total. 70 60 50 Number of Students 40 30 20 10 0 om e Ch cal al r S er
insight into how well this framework impresses on them. The sum of thesefindings will provide the foundation for scaled infusion of EOP throughout the curriculum andpotential adoption of this approach across many engineering and design programs.REFERENCES[1] N. A. of Engineering, The Engineer of 2020: Visions of Engineering in the New Century. 2004.[2] “Engineering for One Planet,” Engineering For One Planet, 2020. https://engineeringforoneplanet.org/.[3] United Nations, “The 17 Sustainable Development Goals,” sdgs.un.org, 2015.https://sdgs.un.org/.[4] I. S. Rampasso, R. Anholon, D. Silva, R. E. Cooper Ordóñez, O. L. G. Quelhas, and L. A. D. Santa-Eulalia, “Developing in engineering students a critical analysis about
online classes.Participating instructors also discussed various strategies to overcome these barriers during thefocus group setting. Our research team is currently working to also identify these strategies andtheir effectiveness in overcoming barriers to using active learning in online teaching.AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grant NoDUE-1821488. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.References[1] M. Dancy, C. Henderson, &, C. Turpen, (2016). How instructors learn about and implementresearch-based instructional strategies: The
University for reviewingthis paper and providing constructive feedback.References[1] W. Zhou and X. Shi, “Culture in groups and teams: A review of three decades of research,” Int. J. Cross Cult. Manag., vol. 11, no. 1, pp. 5–34, 2011.[2] A. S. Tsui, S. Nifadkar, and A. Y. Ou, “Cross-national, cross-cultural organizational behavior research: Advances, gaps, and recommendations,” J. Manage., vol. 33, no. 3, pp. 426–478, 2007.[3] S. Wei, D. M. Ferguson, M. W. Ohland, and B. Beigpourian, “Examining the cultural influence on peer ratings of teammates between international and domestic students,” in the American Society for Engineering Education Annual Conference & Exposition, 2019.[4] J. Wang, G. H.-L. Cheng, T
. Further analysis and modeling of the data areforthcoming, and will provide details of the competencies developed among the newcomers andhow they were developed. We anticipate that articulating the competency models of professionaland technical competence developed in this learning ecology will provide a deeper understandingof what newly hired engineers learn and how they learn as they develop into their careers.References[1] R. Korte, “Learning to practice engineering in business: The experiences of newly hired engineers beginning new jobs,” in The Engineering-Business Nexus: Higher Aims or Triumphant Markets? S. Christensen, B. Delahousse, C. Didier, M. Meganck, & M. Murphy (Eds), Cham, Switzerland: Springer, 2019, pp. 341
the same page.”Feelings toward AmbiguityStudents also expressed their feelings towards ambiguity. Bob expressed fear and ambiguitytogether by describing his experience as “I think generally overall speaking ambiguity would belike being in the unknown. Kind of like almost fear of the unknown then like, yeah, you're notsure what you need to do or what is going to be happening.” Jon discussed how taking the wrongpath for ambiguous problem increases his anxiety, “if something is too ambiguous…I know I getalmost like anxiety if it's ambiguous and I'll never really get going or never know if I'm going inthe right direction.” Jon’s anxiety also became evident when he discussed ambiguity in theworkplace versus academia, stating that he “believe[s
in college, but notin your major? 5. Tell me about how doing PBSL in your major has affected you personally, especially inthe way you describe yourself to others. We summarized four domains based on the interviews and transcription as follows. Due tothe page limit, we only excerpt what they said corresponding to domain 4 which gives uspreliminary data related with question 1. Domain 1: What it’s like to be in the program—relationships amongst students Domain 2: What type/s of people are like to be in the program—people types Domain 3: What type/s of people are like to be in the program—type/s of yourself Domain 4: What impacts of PBSL on you are—changes of your personality or identity Student A participated in PBSL 4
], [14], [18], [19].Need for a STEM Observation ProtocolIn addition to the challenge of defining STEM education, there have been challenges in assessingintegrated STEM instruction in K-12 classrooms. Given the rapid development of both K-12engineering and integrated STEM, it is critical that researchers have access to valid and reliableinstruments to determine the efficacy of different teaching and curricular approaches related toboth teacher effectiveness and student learning. The lack of a protocol designed specifically forsuch teaching will lead to reliance on the use of teacher self-report data or the use of protocolsthat measure “just good” teaching without consideration of the nature of the discipline(s) beingtaught. Existing instruments
collected prior to the beginning ofthe first year of study to answer the following research questions:- To what extent do the data collected for this study support the Gender Similarity Hypothesis?- For characteristics which show a difference, is there evidence that these differences are decreasing over this four year period?Background:Prior to the 1980’s, theories that male students were superior to female students in mathematicalability were widely accepted. For example, in 1974, Maccoby and Jacklin5 wrote “Boys excel inmathematical ability” under the heading “Sex Differences That Are Fairly Well Established.” Page 14.612.2They state that
recommendations expressed in this material are those of the author(s) and do notnecessarily reflect the views of the National Science Foundation.References1. Borkowski, J. G., Carr, M., & Pressley, M. (1987). “Spontaneous” strategy use: Perspectives from metacognitive theory. Intelligence, 11(1), 61-75.2. Bransford, J. D., Brown, A., & Cocking, R. (1999). How people learn: Mind, brain, experience, and school. Washington, DC: National Research Council.3. Chopra, S. K., Shankar, P. R., & Kummamuru, S. (2013, August). MAKE: A framework to enhance metacognitive skills of engineering students. In Teaching, Assessment and Learning for Engineering (TALE), 2013 IEEE International Conference on (pp. 612-617). IEEE.4. Cross, D. R., &
thatacademic preparation is typically not one of the main reasons for attrition 4,5. In other words, moststudents who leave academia choose to leave because of their own personal decision, not becausethey failed qualifying exams or are doing poorly in their courses 5–7. Indeed, Barnes et al.’s 8,9studies of graduate attrition showed that the attributions that professors give for their students thatleave are different than the rationale that the corresponding non-completing students give forleaving. The misalignment, misunderstanding, or attribution bias that may exist (from both parties)is worthy of study and is likely due to the issues that have arisen with sampling a sensitivepopulation.Further, most attrition literature takes a sociological view of
overlaps were not expected to cause any biasin the results. Categories 3 and 4 were formed to understand how the information learned in anentry-level gatekeeper course such as mathematics was carried forward to an advanced levelcourse. Table 1. Grading scale used for questions in the categories 1-4 Grade Explanation 5 Displays excellent understanding of the new concept and the pre- requisite(s) 4 Knowledge of the pre-requisite concept(s) is satisfactory and correctly applies it to the current concept, but the solution is incomplete 3 Knowledge of the pre-requisite concept(s) is satisfactory, but its
Rater 4 -0.91 -0.99 -1 -1.17 -1.25 -1.26 -1.43 -1.41 -1.46 -1.5 -1.51 -1.54 -1.71 -1.76 -1.82 -2 -2.01 -2.06 -2.5Figure 6. Calculation of the range of rater severity from FACET parameter estimationFurther diagnosis revealed some of the overarching areas of disagreement. For example, Table 2reveals statistically significant bias regarding how Rater 5 scored the first PROCESS item,“Identify the Problem,” and Rater 3’s rating of the second item, “Represent the problem.” Thescores the
le es ob Pr Structuredness 1. Did the problem have more than one solution? ✓ Task complexity 2. Do students need to use information/knowledge/skills from other concurrent ✓ course(s) in the term in order to successfully complete the task? 3. Please list the course/course
4.08 .97 technology. Item 5. I know how engineering can be used to help society. 4.25 .81 Item 10. I know how to apply engineering-related concepts in my daily life. 2.97 1.21 Item 11. I know how to explain engineering-related concepts to my child(ren). 2.97 1.18 Item 12. I know how to help my child(ren) with his/her engineering ideas and 3.00 1.15 skills. Item 14. I know how to find out more about engineering information to help 3.58 1.30 my child(ren)’s learning. Item 16. I am aware of engineering curriculum at my child(ren)’s school. 2.94 1.29 Component 2: Attitude
: “For me it‟s more the math. Just because I relate really well to the algebra side of it where, okay here‟s the formula, manipulate it this way and this is what my outcome‟s going to be. But actually conceptualizing things and being able to explain like the picture of it and say, „This is what electricity is.‟ It‟s one of those things where I kind of wish I would understand that side better”.The interviews for this study were conducted as part of a larger study of student understanding ofdifficult concepts in both mechanical and electrical engineering. Reporting on the results of theinterviews with mechanical engineering students, Douglas et al.5 identified misconceptions thatstudents have about force and how
Performance(GRASP).IntroductionProficiency in engineering domains requires experience applying the governing principles withina specified domain and the tools needed to support the comprehension and monitoring of factorsindicating a system‟s performance (ability to achieve a function). These tools may appear simpleto describe in its form and function, but difficult to apply strategically to a context. The contextis defined as strategically, because it requires a multi-step logical, systematic interaction with Page 15.28.2domain knowledge. As experts we may be blind to this interaction1; therefore, we makeassumptions about what it takes for our
). Effects of Problem-Based Learning: A meta-analysis from the angleof assessment. Review of Educational, 75 (1) 27-61.8. Brown, J. S., Collins, A., & Duguid, (1989). Situated cognition and the culture of learning. Educational Researcher, 18, 32-42.9. Collins, A, Brown, J. S., & Newman, (1989). Cognitive apprenticeship: Teaching students the craft of reading, writing, and mathematics. In L. Resnick (Ed), Knowing, learning, writing, and instruction: Essays in honor of Robert Glaser (pp. 453-493). Hillsdale, NJ: Erlbaum.10. Palincsar, A. S., & Brown, A. L., (1984). Reciprocal teaching of comprehension-fostering monitoring activities. Cognition & Instruction, 1, 117-175.11. Lepper, M.R. & Henderlong, J
registration; and 3) to motivate students to learnengineering concepts related to other fields by generating enough interest in the subject5, 6. Thepast research shows that motivating the students to learn in service courses is a challengebecause most students are unable to understand the link between the knowledge acquired in theservice courses and their majors7, 8.This longitudinal study was conducted on Electronic Instrumentation and Systems (EI&S)course, a typical service course offered by the Electrical and Computer Engineering (ECE)department of a large Midwestern university. The objective was to explore and understand theroot causes of why students underperform in service courses. The research question formulatedfor the study was: “What are
engineers’ satisfaction with helping people and society through their jobs. European Journal of Engineering Education, 44(6), 939–953.Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.Canning, E. A., Harackiewicz, J. M., Priniski, S. J., Hecht, C. A., Tibbetts, Y., & Hyde, J. S. (2018). Improving performance and retention in introductory biology with a utility-value intervention. Journal of Educational Psychology, 110(6), 834.Cech, E. A. (2014). Culture of disengagement in engineering education? Science, Technology, & Human Values, 39(1), 42–72.Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of
models, statewide pre-college math initiatives, teacher and faculty professional development programs, and S-STEM pro- grams.Ms. Olivia W. Murch, Purdue University Senior at Purdue University pursuing a Bachelor of Science degree in Biological, Food Process, Engi- neering. Currently conducting research under Dr. Ferguson through Engineering Education.Dr. Daniel M. Ferguson, Purdue University, West Lafayette (College of Engineering) Daniel M. Ferguson is CATME Managing Director and a research associate at Purdue University. Prior to coming to Purdue he was Assistant Professor of Entrepreneurship at Ohio Northern University. Before assuming that position he was Associate Director of the Inter-Professional Studies
assessment instruments.III. E XPERIMENTAL S TUDY D ESIGNBuilding on the related research and pedagogical underpinnings in Section II, we consider herethe design of the experimental study. The primary hypothesis of the research study is as follows:“There exists significant improvement in the engagement, student interest, and motivation forsoftware engineering content using an integrated approach of active and deign-based learningcompared to traditional teaching approaches.” Traditional approaches refer to a combinationof lectures, tutorials and lab sessions for a software engineering course.To test this hypothesis, the experimental study included the design of software-engineeringcourse content, coordination of the study’s control (traditional) and
at Howard University and a Carnegie Scholar. She served as a Co-Principal Investigator of the Center for the Advancement of Engineering Education (CAEE). Dr. Fleming earned her Ph.D. in civil engineering from the University of California at Berkeley and holds a Master of Science and Bachelor of Science degree in civil engineering from George Washing- ton University and Howard University, respectively. Dr. Fleming’s research interest is concentrated on the reform of engineering education, broadening participation in engineering and the scholarship of teaching and learning.Robin Adams, Purdue University, West Lafayette Robin S. Adams is an Assistant Professor in the School of Engineering Education at Purdue
75th percentiles,respectively, and the whiskers extend to data points not considered to be outliers. Outliers areplotted as red +’s. If there are no boxes, then all responses besides the median response areconsidered to be outliers.Figure 1: Statistics for responses to survey question 1: How would you rate your study habits whilelearning remotely as compared to learning in person? 1=better in person, 7=better remotelyFigure 2: Statistics for responses to survey question 2: How would you rate your access to re-quired technology (e.g., computer and internet) while learning remotely as compared to learningin person? 1=better in person, 7=better remotelyAs shown in Figure 1, students generally reported a significant negative impact of
]. Available: http://arxiv.org/abs/1904.09408.[9] T. Mikolov, K. Chen, G. Corrado, and J. Dean, “Efficient Estimation of Word Representations in Vector Space,” arXiv:1301.3781 [cs], Sep. 2013, Accessed: Nov. 06, 2020. [Online]. Available: http://arxiv.org/abs/1301.3781.[10] J. Pennington, R. Socher, and C. Manning, “GloVe: Global Vectors for Word Representation,” in Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), Doha, Qatar, Oct. 2014, pp. 1532–1543, doi: 10.3115/v1/D14-1162.[11] J. Firth, A synopsis of linguistic analysis. Oxford, UK: Blackwell, 1957.[12] S. Crossley, J. Ocumpaugh, M. Labrum, F. Bradfield, M. Dascalu, and R. S. Baker, “Modeling math identity and
and Their Pedagogical AssessmentAbstractImparting real world experiences in the classroom for a software verification and validation(S/W V&V) course is typically a challenge due to lack of effective Active Learning Tools(ALTs). At Robert Morris University (RMU, the author’s institution), this educational resourcegap has been addressed by developing several ALTs in the form of class exercises, case studies,and case study videos that were created by collaborating with the academia and industrialprofessionals. Through this three-year work 20 delivery hours of case studies, 18 delivery hoursof exercises and 6 delivery hours of role play videos totaling 44 delivery hours of Software V&Vcourse materials have been developed. The developed
teacher professionaldevelopment experience may trickle down to impact student self-efficacy and interest.Fortunately, our research is ongoing with the results of these implementation changes remainingto be seen.AcknowledgmentThis material was supported by the National Science Foundation under Grant DRL-1513175.References[1] National Science Board, "Science and engineering indicators digest 2012," Author, Arlington, VA,2012.[2] K. D. Welde, S. Laursen, and H. Thiry, "Women in science, technology, engineering and math (STEM)," Sociologists for Women in Society, University of Kansas, Lawrence, KS,2007.[3] P. M. Sadler, G. Sonnert, Z. Hazari, and R. Tai, "Stability and volatility of STEM career interest in high school
professor in the Agricultural and Biosystems Engineering Department. He co- ordinates the occupational safety option of the industrial technology degree program and the occupational safety certificate program for the department. His research interests are in agricultural and workplace safety and the scholarship of teaching and learning associated with safety, engineering, and technology curricula.Prof. Mack Shelley, Iowa State University Mack Shelley is a Full Professor with joint appointment in the Departments of Statistics and Political Science. He holds the title of University Professor [”The University Professorship recognizes faculty members who have had a significant impact on their department(s) and the university