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1. Toward Benchmarking Student Progress in Mechanics: Assessing Learning Cycles through Mastery Learning and Concept Questions

   Papadopoulos, C. ; Santiago-Román, A. I. ; Hillman, E. F. ; Figueroa, G. L. ; Vega Morales, I. ( July 2021 , ASEE Virtual Annual Conference)

   In mechanics, the standard 3-credit, 45-hour course is sufficient to deliver standard lectures with prepared examples and questions. Moreover, it is not only feasible, but preferable, to employ any of a variety of active learning and teaching techniques. Nevertheless, even when active learning is strategically used, students and instructors alike experience pressure to accomplish their respective learning and teaching goals under the constraints of the academic calendar, raising questions as to whether the allocated time is sufficient to enable authentic learning. One way to assess learning progress is to examine the learning cycles through which students attempt, re-think, and re-attempt their work. This article provides data to benchmark the time required to learn key Statics concepts based on results of instruction of approximately 50 students in a Statics class at a public research university during the Fall 2020 semester. Two parallel techniques are employed to foster and understand student learning cycles. • Through a Mastery Based Learning model, 15 weekly pass/fail “Mastery Tests” are given. Students who do not pass may re-test with a different but similar test on the same topic each week until the semester’s conclusion. The tests are highly structured in that they are well posed andmore »highly focused. For example, some tests focus only on drawing Free Body Diagrams, with no equations or calculations. Other tests focus on writing equilibrium equations from a given Free Body Diagram. Passing the first six tests is required to earn the grade of D; passing the next three for C; the next three for B; and the final three for A. Evaluations include coding of student responses to infer student reasoning. Learning cycles occur as students repeat the same topics, and their progress is assessed by passing rates and by comparing evolving responses to the same test topics. • Concept Questions that elicit qualitative responses and written explanations are deployed at least weekly. The learning cycle here consists of students answering a question, seeing the overall class results (but without the correct answer), having a chance to explore the question with other students and the instructor, and finally an opportunity to re-answer the same question, perhaps a few minutes or up to a couple days later. Sometimes, that same question is given a third time to encourage further effort or progress. To date, results from both cycles appear to agree on one important conclusion: the rate of demonstrated learning is quite low. For example, each Mastery Test has a passing rate of 20%-30%, including for students with several repeats. With the Concept Questions, typically no more than half of the students who answered incorrectly change to the correct answer by the time of the final poll. The final article will provide quantitative and qualitative results from each type of cycle, including tracking coded responses on Mastery Tests, written responses on Concept Questions, and cross-comparisons thereof. Additional results will be presented from student surveys. Since the Mastery Tests and Concept Questions follow typical Statics topics, this work has potential to lead to a standardized set of benchmarks and standards for measuring student learning – and its rate – in Statics.« less
2. Categorizing student interactions with manipulatives in statics

   Rupe K. ; Davishahl, E. ( May 2022 , 2022 ASEE Zone IV Conference)

   This work in progress paper describes ongoing work to understand the ways in which students make use of manipulatives to develop their representational competence and deepen their conceptual understanding of course content. Representational competence refers to the fluency with which a subject expert can move between different representations of a concept (e.g. mathematical, symbolic, graphical, 2D vs. 3D, pictorial) as appropriate for communication, reasoning, and problem solving. Several hands-on activities for engineering statics have been designed and implemented in face-to-face courses since fall 2016. In the transition to online learning in response to the COVID 19 pandemic, modeling kits were sent home to students so they could work on the activities at their own pace and complete the associated worksheets. An assignment following the vector activities required students to create videotaped or written reflections with annotated pictures using the models to explain their thinking around key concepts. Students made connections between abstract symbolic representations and their physical models to explain concepts such as a general 3D unit vector, the difference between spherical coordinate angles and coordinate direction angles, and the meaning of decomposing a vector into components perpendicular and parallel to a line. Thematic analysis of the video and writtenmore »data was used to develop codes and identify themes in students’ use of the models as it relates to developing representational competence. The student submissions also informed the design of think-aloud exercises in one-on-one semi-structured interviews between researchers and students that are currently in progress. This paper presents initial work analyzing and discussing themes that emerged from the initial video and written analysis and plans for the subsequent think-aloud interviews, all focused on the specific attributes of the models that students use to make sense of course concepts. The ultimate goal of this work is to develop some general guidelines for the design of manipulatives to support student learning in a variety of STEM topics.« less
3. Categorizing student interactions with manipulatives in statics

   Rupe, K. M. ; Davishahl, E. ( May 2022 , 2022 ASEE Zone IV Conference)

   This work in progress paper describes ongoing work to understand the ways in which students make use of manipulatives to develop their representational competence and deepen their conceptual understanding of course content. Representational competence refers to the fluency with which a subject expert can move between different representations of a concept (e.g. mathematical, symbolic, graphical, 2D vs. 3D, pictorial) as appropriate for communication, reasoning, and problem solving. Several hands-on activities for engineering statics have been designed and implemented in face-to-face courses since fall 2016. In the transition to online learning in response to the COVID 19 pandemic, modeling kits were sent home to students so they could work on the activities at their own pace and complete the associated worksheets. An assignment following the vector activities required students to create videotaped or written reflections with annotated pictures using the models to explain their thinking around key concepts. Students made connections between abstract symbolic representations and their physical models to explain concepts such as a general 3D unit vector, the difference between spherical coordinate angles and coordinate direction angles, and the meaning of decomposing a vector into components perpendicular and parallel to a line. Thematic analysis of the video and writtenmore »data was used to develop codes and identify themes in students’ use of the models as it relates to developing representational competence. The student submissions also informed the design of think-aloud exercises in one-on-one semi-structured interviews between researchers and students that are currently in progress. This paper presents initial work analyzing and discussing themes that emerged from the initial video and written analysis and plans for the subsequent think-aloud interviews, all focused on the specific attributes of the models that students use to make sense of course concepts. The ultimate goal of this work is to develop some general guidelines for the design of manipulatives to support student learning in a variety of STEM topics.« less
4. Undergraduate Student Learning of Market-Driven Design Topics in a Third-Year Design Course

   Hoffenson, Steven ; Pitterson, Nicole ( July 2021 , 2021 ASEE Virtual Annual Conference)

   Generally, the focus of undergraduate engineering programs is on the development of technical skills and how they can be applied to design and problem solving. However, research has shown that there is also a need to expose students to business and society factors that influence design in context. This technical bias is reinforced by the available tools for use in engineering education, which are highly focused on ensuring technical feasibility, and a corresponding lack of tools for engineers to explore other design needs. One important contextual area is market systems, where design decisions are made while considering factors such as consumer choice, competitor behavior, and pricing. This study examines student learning throughout a third-year design course that emphasizes market-driven design through project-based activities and assignments, including a custom-made, interactive market simulation tool. To bridge the gap between market-driven design and engineering education research, this paper explores how students think about and internally organize design concepts before and after learning and practicing market-driven design approaches and tools in the context of an engineering design course. The central research question is: In what ways do student conceptions of product design change after introducing a market-driven design curriculum? In line with the constructivismmore »framework of learning, it is expected that student conceptions of design should evolve to include more market considerations as they learn about and apply market-driven design concepts and techniques to their term projects. Four different types of data instruments are included in the analysis: Concept maps generated by the students before and after the course, open-ended written reflection assignments at various points in the semester, surveys administered after learning the market simulation tool and at the end of the course, and final project reports in which student teams listed their top 3-5 lessons learned in the course. Using the changes between the pre- and post-course concept maps as the primary metric to represent evolving design conceptions, data from the reflections, surveys, and reports are evaluated to assess their influence on such learning. Because market-driven design is a multi-faceted topic, a market-driven design is hierarchically decomposed into specific sub-topics for these evaluations. These include profitability (which itself encompasses pricing and costs), modeling and simulation, and market research (which encompasses consumers and competition). For each topic, correlation analyses are performed and regression models are fit to assess the significance of different factors on learning. The findings provide evidence regarding the effectiveness of the course’s market-driven design curriculum and activities on influencing student conceptions of design.« less
5. Undergraduate Student Learning of Market-Driven Design Topics in a Third-Year Design Course

   Hoffenson, Steven Pitterson ( July 2021 , American Society of Engineering Education)

   Generally, the focus of undergraduate engineering programs is on the development of technical skills and how they can be applied to design and problem solving. However, research has shown that there is also a need to expose students to business and society factors that influence design in context. This technical bias is reinforced by the available tools for use in engineering education, which are highly focused on ensuring technical feasibility, and a corresponding lack of tools for engineers to explore other design needs. One important contextual area is market systems, where design decisions are made while considering factors such as consumer choice, competitor behavior, and pricing. This study examines student learning throughout a third-year design course that emphasizes market-driven design through project-based activities and assignments, including a custom-made, interactive market simulation tool. To bridge the gap between market-driven design and engineering education research, this paper explores how students think about and internally organize design concepts before and after learning and practicing market-driven design approaches and tools in the context of an engineering design course. The central research question is: In what ways do student conceptions of product design change after introducing a market-driven design curriculum? In line with the constructivismmore »framework of learning, it is expected that student conceptions of design should evolve to include more market considerations as they learn about and apply market-driven design concepts and techniques to their term projects. Four different types of data instruments are included in the analysis: Concept maps generated by the students before and after the course, open-ended written reflection assignments at various points in the semester, surveys administered after learning the market simulation tool and at the end of the course, and final project reports in which student teams listed their top 3-5 lessons learned in the course. Using the changes between the pre- and post-course concept maps as the primary metric to represent evolving design conceptions, data from the reflections, surveys, and reports are evaluated to assess their influence on such learning. Because market-driven design is a multi-faceted topic, a market-driven design is hierarchically decomposed into specific sub-topics for these evaluations. These include profitability (which itself encompasses pricing and costs), modeling and simulation, and market research (which encompasses consumers and competition). For each topic, correlation analyses are performed and regression models are fit to assess the significance of different factors on learning. The findings provide evidence regarding the effectiveness of the course’s market-driven design curriculum and activities on influencing student conceptions of design.« less