Renee M. Clark

A new approach to hazardous materials transportation risk analysis: decision modeling to identify critical variables.

We take a novel approach to analyzing hazardous materials transportation risk in this research. Previous studies analyzed this risk from an operations research (OR) or quantitative risk assessment (QRA) perspective by minimizing or calculating risk along a transport route. Further, even though the majority of incidents occur when containers are unloaded, the research has not focused on transportation-related activities, including container loading and unloading. In this work, we developed a decision model of a hazardous materials release during unloading using actual data and an exploratory data modeling approach. Previous studies have had a theoretical perspective in terms of identifying and advancing the key variables related to this risk, and there has not been a focus on probability and statistics-based approaches for doing this. Our decision model empirically identifies the critical variables using an exploratory methodology for a large, highly categorical database involving latent class analysis (LCA), loglinear modeling, and Bayesian networking. Our model identified the most influential variables and countermeasures for two consequences of a hazmat incident, dollar loss and release quantity, and is one of the first models to do this. The most influential variables were found to be related to the failure of the container. In addition to analyzing hazmat risk, our methodology can be used to develop data-driven models for strategic decision making in other domains involving risk.

The Model Eliciting Activity (MEA) Construct: Moving Engineering Education Research Into the Classroom

A growing set of “professional skills” including problem solving, teamwork, and communications are becoming increasingly important in differentiating U.S. engineering graduates from their international counterparts. A consensus of engineering educators and professionals now believes that mastery of these professional skills is needed for our graduates to excel in a highly competitive global environment. A decade ago ABET realized this and included these skills among the eleven outcomes needed to best prepare professionals for the 21st century engineering world. This has left engineering educators with a challenge: how can students learn to master these skills? We address this challenge by focusing on models and modeling as an integrating approach for learning particular professional skills, including problem solving, within the undergraduate curriculum. To do this, we are extending a proven methodology — model-eliciting activities (MEAs) — creating in essence model integrating activities (MIAs). MEAs originated in the mathematics education community as a research tool. In an MEA teams of students address an open-ended, real-world problem. A typical MEA elicits a mathematical or conceptual system as part of its procedural requirements. To resolve an MEA, students may need to make new connections, combinations, manipulations or predictions. We are extending this construct to a format in which the student team must also integrate prior knowledge and concepts in order to solve the problem at hand. In doing this, we are also forcing students to confront and repair certain misconceptions acquired at earlier stages of their education. A distinctive MEA feature is an emphasis on testing, revising, refining and formally documenting solutions, all skills that future practitioners should master. Student performance on MEAs is typically assessed using a rubric to measure the quality of solution. In addition, a reflection tool completed by students following an MEA exercise assists them in better assessing and critiquing their progress as modelers and problem solvers. As part of the first phase a large, MEA research study funded by the National Science Foundation and involving six institutions, we are investigating the strategies students use to solve unstructured problems by better understanding the extent that our MEA/MIA construct can be used as a learning intervention. To do this, we are developing learning material suitable for upper-level engineering students, requiring them to integrate concepts they’ve learned in foundation courses while teasing out misconceptions. We provide an overview of the project and our results to date.© 2008 ASME

A classroom-based simulation-centric approach to microelectronics education

Introductory courses in microelectronic circuits are integral components to electrical and computer engineering undergraduate curriculums. The nature of the material is well‐suited for the incorporation of simulation tools to enhance student understanding of core concepts. SPICE is an electrical circuit simulation tool that has been widely adopted for industrial applications and education. In many instances, engineering instructors have used SPICE‐based simulation tools for homework problems, laboratory exercises, and course projects. Although generally accepted as beneficial to electronics education, the use of SPICE simulation tools is typically restricted to these types of assignments and not heavily used for classroom activity. In this paper, we present a novel method for incorporating SPICE simulation tools into the classroom. Specifically, in a summer 2017 microelectronics course, we used simulation tools for all aspects of the course, incorporating simulation into lecture, in‐class active learning, as well as assignments, and projects. To evaluate this approach, we carried out a rigorous, comprehensive study of this pedagogical approach on student learning, and perspectives using a variety of direct and indirect assessment methods. The results across all measures showed substantial benefits for students to using this methodology and positive responses to the active learning. Beyond microelectronics and other electrical and computer engineering courses, this approach can be applied to other STEM courses where complex systems are studied and simulation tools for these systems are readily accessible to students.

Student perspectives on application of game-based learning within a graduate-level engineering course

In recent years, game-based learning has been increasing in popularity as a tool for providing students with experiential learning opportunities. Although there have been a few implementations at the graduate level, there is still the need for a greater number of studies documenting the effectiveness of game-based practices in graduate-level environments. In our study, we developed and implemented a digital game with technical content in a graduate-level, distance-enabled nuclear engineering course. As part of assessing this implementation, we gathered the perspectives of the students using a learning environment survey, a focus group, and individual interviews. The results of these methods demonstrated positive student viewpoints towards the learning environment and the use of the game in this course. Based on a double-coded content analysis of the focus group and interview data, the students found the game engaging and noted the possibility of points and “winning” associated with playing the game. They further indicated that the use of the game was a good approach with potential that “changed things up.” Although we received positive feedback, the students also provided constructive feedback on this initial implementation and how it could be improved, including increased gaming elements and challenge level as well as providing more performance feedback to students as they participate in the game.

Work in progress - ethical model eliciting activities (E-MEA) - extending the construct

Mastery of the professional skills is needed if our graduates will continue to excel in the increasingly global engineering environment. To date, much of the research associated with studying ethical decision making in organizations has focused on business and individual decisions with little empirical research focused on team-based ethical decision making specific to engineering. As part of a Phase III CCLI project, we are developing E-MEAs, which are open-ended, realistic problems that challenge student teams to recognize and resolve potential ethical dilemmas embedded within a larger engineering problem requiring skills integration. By extending the AMA construct to ethical situations we are able to better identify and understand the various strategies teams use to resolve complex ethical dilemmas. We are both adapting existing cases and creating our own scenarios that bring out differing perspectives, in order to provide a rich body of work that will enable the analysis of studentspsila ethical decision making processes in the context of engineering problem solving. To capture needed process data, we are adapting MEA reflection tools and utilizing PDA devices and team Wikis. Further, to assess performance outcomes, we are utilizing two rubrics, one of which (P-MEAR) was developed previously to assess the ethical dimension of student projects. Data collected will be analyzed using cluster and statistical methodologies to classify students according to performance and strategies employed.

Experiences with “Flipping” an Introductory Mechanical Design Course

We formally incorporated the “flipped classroom” into our undergraduate mechanical engineering curriculum during the fall of 2013. In addition to a second-year course in mechanics and statics, we also flipped the laboratory portion of a required second-year course in introductory mechanical design taken by over 200 students annually. The CAD modelling portion of the course was delivered in a flipped fashion, in which students applied their SolidWorks knowledge during the weekly two-hour laboratory session. In the “flipped classroom”, face-to-face time is used for application of skills versus the conveyance of facts. To enable this approach, students watched video lectures before class. This course was part of a school-wide initiative to drive active learning, engagement, and deeper learning. We obtained positive results with flipping this course, as perceived by the students, teaching assistants, and instructor. Structured classroom observation revealed many of the ideals of the flipped classroom, including teamwork, peer discussions, active questioning, and problem-solving. Using the Teaching Dimensions Observation Protocol (TDOP), we observed that nearly 100% of the observation segments contained problem-solving with SolidWorks as the TAs circulated and assisted students. This interactive environment aligned with our finding from the College and University Classroom Environment Inventory (CUCEI), in which students rated the Personalization dimension, which assesses student-to-teacher interaction, highest. We benchmarked our CUCEI results against those of STEM classrooms at two other schools. Our direct assessment of learning based on SolidWorks take-home assignments showed statistically equivalent results when comparing the pre-flipped to the flipped course, as have other mechanical engineering studies in the literature. However, during a semi-structured interview, the instructor reflected that students in the flipped class were more sophisticated, proficient SolidWorks users, attributing this to more practice time available with the flipped classroom. Based on student survey data, nearly 60% of respondents preferred using class time for active learning versus listening to a lecture; thus, the majority realized the value of the flipped approach. A content analysis showed the most frequently perceived benefit to be the flexibility associated with video or online learning, as noted by 46% of respondents. The instructor noted that students in the flipped classes displayed greater confidence and interest in SolidWorks compared to students in previous classes. However, the TAs noticed that students were not watching the videos in all cases, necessitating the use of accountability quizzes. Despite some challenges and a lack of statistical significance of the homework results, we considered this to be a successful implementation of the flipped classroom given the level of student engagement. Going forward, flipped instruction will be the teaching and learning format that we plan to use with this course as well as others in the mechanical engineering department.

Assessing Flipped Classrooms

We discuss a mixed methods approach for assessing the flipped classroom, which we applied to a school-wide initiative starting in the fall of 2013. Assessment of a flipped classroom is, in many ways, no different than rigorous assessment of any good pedagogy. Assessment planning must first consider the objectives of the pedagogical initiative. The critical question we asked was “What educational gains or advantages should students experience as a result of course flipping?” We then focused on the selection of instruments and protocols for measurement. To study student learning and achievement, we analysed pre-flip versus flip exam and homework results and formally interviewed instructors. To investigate in-class engagement and active learning, we conducted classroom observation using a validated protocol. Using web analytics video access data, we investigated preparation with the flipped classroom and its relationship to achievement. Finally, to assess student perceptions, we used an evaluation survey tailored to the flipped classroom and a research-based classroom environment instrument. A comprehensive and thorough assessment plan provides the advantage of both formative and summative data for an initiative and can guide future directions with it.

In-Depth Use of Modeling in Engineering Coursework to Enhance Problem Solving

There has been recent interest among engineering educators in the use of models and modeling as a means to promote vertical skills integration and problem solving within undergraduate engineering curriculums. We have extended the MEA (Model Eliciting Activities) construct to upper division engineering courses, reformulated the resultant exercises as MIAs (Model Integrating Activities). These were introduced as part of a pilot course focused on enhancing problem solving abilities for junior and senior level industrial engineering students. The course focused on developing systems thinking in order to solve unstructured problems, some of which incorporated global and ethical considerations. The course challenged students to practice various behavioral and professional skills, including ad-hoc teaming, written and verbal communication, revision and refinement of group work, and reflection. We learned valuable lessons from this unique, non-traditional class, which serves as a lead-in to an upcoming four-year research effort by six institutions to expand the application of MEAs to five engineering disciplines. One important lesson learned was the potential of a well-constructed MIA to uncover subject-area misconceptions held by students. We discuss this, other lessons learned, and challenges identified that should be addressed to better achieve our pedagogical objectives. This chapter discusses our experiences with this unique engineering course.

Scaffolding to Support Problem-Solving Performance in a Bioengineering Lab—A Case Study

Background: Engineering programs must equip students to solve open-ended workplace problems. However, the literature points to actual or potential difficulties faced by students in solving open-ended or complex problems. During Fall 2014, the authors’ students experienced difficulties in solving open-ended bio-signals laboratory problems of designing input signals to analyze unknown systems via MATLAB programming. These difficulties resulted in low performance. Intended Outcomes: To support, or scaffold, problem-solving in subsequent semesters, a strategy of frequent and timely monitoring and feedback was used. The hypotheses were that these scaffolding strategies would be associated with enhanced performance on open-ended projects, and would support students in similar future work once removed. Application Design: Based upon strategies from the scaffolding literature, assignments that guided problem decomposition were used. Flipped instruction challenged students to prepare for the laboratory by reviewing worked programming examples and completing online assessments. The laboratory sessions were reserved for collaborative, hands-on programming, with instructor oversight, as in a problem-based learning environment. Students submitted frequent progress reports for self-monitoring and feedback throughout each project. Findings: A statistical comparison of project scores across semesters revealed performance improvements with scaffolding. Post-scaffolding assessment in a follow-up course determined scaffolding to be helpful and applicable by these students for similar projects. These preliminary results are important for STEM students and instructors encountering challenges with open-ended problem-solving of this nature, and they provide quantitative evidence recently called for by the STEM scaffolding literature.

Influence of End Customer Exposure on Product Design within an Epistemic Game Environment.

Engineering product design requires both technical aptitude and an understanding of the nontechnical requirements in the marketplace, economic or otherwise. Engineering education has long focused on the technical side of product design, but there is increasing demand for market-aware engineers in industry. Market-awareness and customer-focus are also associated with entrepreneurship, which has been given increased focus in engineering education. A common tool for gauging customer interest in industry is the focus group. Herein we examine the effect of customer voice as presented in a focus group for influencing engineering product design generated by students as part of the virtual internship and epistemic game Nephrotex. We find that customer exposure is related to decreased product cost without a change in product quality. Therefore, we suggest that the injection of customer voice into the engineering curriculum is a valid method by which to improve engineering design pedagogy.