BRIDGING THEORY AND PRACTICE

A Case Study in Engineering Design Education

Joanna Joseph

Engineering Education

Engineering education typically comprises of a combination of theory and design. A sound theoretical foundation is essential for practical application. The purpose of engineering education is to prepare students to define and solve problems with the constraints of cost, time, and performance. While there may exist theoretical solutions that are state of the art, practical application demands an understanding for translation into adoptable technologies. Additionally, engineering is a very multi-disciplinary field, and the combination of knowledge from various domains is typical for arriving at a feasible and desirable solution.

Another consideration is the students themselves. With increasing diversity in classrooms today and learners with varying demographic backgrounds, educators are tasked with ensuring that the course design is adequate in equipping learners to achieve the desired learning outcomes.

Thus, engineering education and educators face the unique challenge of integrating several teaching methods, accounting for student learning styles across tasks, rooting course design in pedagogical foundations, and attempting to bridge theory and practice through synthesis of theoretical knowledge into applicatory design.

How can we teach engineers to synthesize theory into design?

Learning Styles and VARK Types

The concept of Learning Styles refers to the different methods through which individuals receive and synthesize information. There are varied views and opinions on this concept in scientific literature, and a few popular models include Kolb's model of experiential learning, Honey and Mumford's model of the learning cycle, and Barbe's proposed learning modalities. Neil Fleming's VARK model built upon Barbe's modalities, and introduced the fourth formal learning modality.

The VARK model defines four sensory modalities for learning: visual, aural, reading/writing, and kinesthetic. Based on the VARK Model, learners can be classified into either categories depending on their preferred modality. There is also a classification for learners that may have a mixture of preferred modalities. Though this model may not encompass every facet of individual learning, it sets a basis for the educational design paradigm.

The two key factors to note while utilizing this approach are:

Most individuals are multi-modal learners.
Learning can be facilitated by pairing the modality to the learning outcome.

Studies indicate that engineering students typically fall into the category of kinesthetic learners, however variations in modality are observed when tasks are modified. Another factor to note is that engineering education requires the holistic development of varied skill-sets and a multi-disciplinary approach is essential to truly facilitate learning. Thus, the conclusion drawn here is that being mindful of student learning styles, understanding the modality that fits best with the learning component, and combining these factors through pedagogical theory and evidence based teaching practices, allows for maximization of learning.

My Teaching Philosophy

TAR Question

What are the study habits employed and course materials used by students in the environmental engineering course ‘CHEE 476 576: Wastewater Treatment Design System’ to learn and synthesize the theory taught, and apply it in practice to their design project?

This project was diagnostic in nature, and was aimed at understanding the resources utilized by students to synthesize the theory they learned while they were completing their final project. By answering this question, the goal was to understand how those resources were utilized and why they were favored by the learners. In order to draw this inference, the VARK type of students was found and literature was referenced to determine which modality suited each learning component best.

By doing this, it provided insight into student preferences of learning tools with specific goals in mind. It also allowed for an understanding of an optimal tool selection dependent on the learning goal to be achieved.

Thus, the overall process can be summarized as:

Student Learning Style + Learning Tool + Optimal Method of Delivery = Maximum Learning

EDUCATIONAL LANDSCAPE

The Background

As an engineer myself, the process of integrating concepts with design is a challenge I have faced in both my academic and professional life. I have also enjoyed certain classes more than other, and been able to understand the material and retain it better. Separating my personal preferences of subject matter, I found that I learnt better in classes specifically catering to the learning need.

As an educator, I want to understand the needs of my students to provide them with appropriate tools for success. I aim to do this through a robust and comprehensive course design. With an evolving educational landscape, the introduction of AI tools, multi-faceted challenges in the engineering landscape, hybrid learning, and increasingly diverse classroom environments, I believe educators are presented with a unique opportunity.

An understanding of student learning style & pedagogical evidence of learning content delivery will equip engineering educators with the tools needed to design courses effectively and efficiently.

The Course

The course ‘CHEE 476 576-Wastewater Treatment Design System’ is a 3-credit upper level engineering course offered to undergraduate students in their junior or senior year, and to graduate students. The course teaches students the theory and practical design of wastewater systems.

The course is taught by Dr. Byron Hempel, a Professor of Practice in the Department of Chemical and Environmental Engineering, at the University of Arizona. Dr. Hempel used evidence-based teaching practices, and his course design is strongly rooted in pedagogical foundations.

There were 9 pre-defined learning outcomes in this course, and the prerequisite CHEE 377 was recommended. The grading system followed in this course was specifications grading, which is complement to mastery learning. This ensures that the grades received by a student if accurately reflective of their mastery in the course and success in meeting the defined learning outcomes.

COURSE COMPONENTS

EVOLVING CLASSROOM ENVIRONMENT

The Learners

There were 22 students in the Spring 2024 cohort, of which 16 were graduate students and 6 were undergraduate students. The language of instruction was English. Learners were full-time students and class was conducted in-person, with lecture recordings available for subsequent viewings on the LMS.

The majority of students were pursing undergraduate or graduate degrees in Environmental Engineering. Other degree majors included Chemical Engineering and Civil Engineering. Most undergraduate students were juniors, with a few seniors too. Graduate students however were evenly divided between master's students and doctoral students.

This cohort was a good example of a diverse classroom environment. The multidisciplinary nature of the course aims to teach students both theoretical aspects as well as application through design, and follows a very hands on approach.

STUDENT EDUCATION LEVEL

STUDENT MAJOR

Timeline & Learning Outcomes

Methods

Since the course was diagnostic in nature, it consisted of observation of the class, analysis of the course design, and obtaining both quantitative and qualitative data from the students. The goal was to answer the TAR question of what course materials were used the most by students to retain and reference theory, and apply it to their final project design. A combination of methods like passive observation, surveys, and focus groups were employed to collect data. This data was then analyzed to draw both qualitative and quantitative inferences.

PHASE 1

Observation of Teaching

Observation of teaching was done on 3 separate occasions. Since the course was split into the theory portion (10 weeks and the design portion (5 weeks), I wanted to observe the teaching practices for each segment. Additionally, I wanted to gauge the classroom environment and the interaction of the students with each other, as well as with the instructor. In addition, I also wanted to observe students as they asked questions regarding the homework, and worked through in class-activities on BioWin.

Analysis of Course Design

The other component of my analysis was the course design. Reading through the syllabus and understanding the grading structure allowed me to understand the expectations for students. Additionally, I studied the resources available to students, like in-person lectures & recordings, online modality, office hours, readings, tutorials for BioWin, and supplemental practice materials. These resources, combined with the methods of implementation, set the background for answering my TAR question.

PHASE 2

Student Demographics

Section 1

This section of the survey was to collect information about student demographics like education level, major, minor, engineering design experience, and prerequisite knowledge (CHEE 377). This was done in order to understand the background of the learners in this course, and the existing knowledge they possessed coming into it. It was also essential to gauge student expertise in design, as the analysis of efficiency of teaching methods was dependent on the existing baseline of experience.

Course Feedback & Resources

Section 2:

The next section of the survey gathered information of each students' preferred mode of receiving information, performing tasks, and learning certain concepts. This section was tailored specifically to this course, so students were able to select the course resources they utilized for specific tasks. Students were also asked for their feedback on the instruction of the course, the resources available to them, their opinion on in-class group activities, & difficulty level of examinations.

PHASE 3

VARK Style Survey

The VARK Questionnaire (Version 8.01) was distributed to each student. Based on their answers, each student was attributed a learning style corresponding to each of the VARK modalities. The purpose of this survey was to test the general claim in the literature of engineering students being primarily kinesthetic learners. Another purpose of this survey was to map individual student learning style to the initial course feedback received, and resources utilized by students. This combination was done to contextualize the use of student learning styles in engineering course design.

Focus Groups

Once the course was over and the surveys were answered, I conducted group interviews in-person with students to obtain feedback and understand their experience in their own words. I divided students into 4 focus groups. The two questions I posed to the students were:

Q1: While studying for the mid-term exams and completing homework assignments, what resources did you find helped you the best?

Q2: During the design portion, what resources did you use to reference theory & to troubleshoot in BioWin?

Results

COURSE FEEDBACK & RESOURCES SURVEY

The following are the results of the Course Feedback & Resources Survey. Each question was rated using a Likert Scale ranging from 1 to 5, with 1 corresponding to 'Strongly Agree' and 5 corresponding to 'Strongly Disagree'. This survey had an 86% response, with 19 students of 22 from the cohort filling it.

Mode of Instruction

The preferred mode of instruction was in-person, with most students preferring to work with their peers during class to solve problems as opposed to solving them alone. This also highlights the importance of teamwork in an engineering classroom, which is reflective of an engineering work environment. Engineering often demands a collaborative environment, and fostering cooperation at an early educational level is a goof recipe to set students up for success. It is also essential to note that while in-person attendance was mandatory, lectures were recorded for subsequent viewings. Additionally, students were granted a percentage of excused absences. If additional absences were required, students were allowed to make up for them by providing a commentary on the material taught within a stipulated time period.

Course Content Organization

Having a well-organized LMS reduces the cognitive load placed on students while accessing course resources. Additionally, it allows students to fully utilize resources if they have no trouble finding what they are looking at. Another factor for consideration is the mental models arising out of the organization of content and the sequence of delivery.

There is shown to be higher retention when students are able to link the readings, in-class lectures and activities, homework, and design assignments. This allows for a smooth flow and increases possibility of connection and synthesis.

Student Learning Styles

This section of the survey contained generalized questions aimed at understanding student preferences with respect to receiving information, as well as specific examples to gauge student preferences within offered course resources. Through answers, it was clear that most students preferred complex problems, such as those found in engineering education. Additionally, methods like note taking, and rewatching lectures as opposed to reading theoretical material were preferred by most students.

Student Course Feedback

These questions aimed to gauge the way students felt about the course. The hypothesis this project was based on was that the course design was robust and sufficient, and the resources provided was sufficient to allow students to mee the learning outcomes. This was validated by the answers received. Most students felt comfortable completing the readings before class, and that the resources provided to them to be successful in the midterm exams and BioWin project, were sufficient. Though students may have preferred certain resources to others, this exercise in validation demonstrates the sufficiency of the course material provided.

Supporting Student Learning

The role of the educator is to equip students with the necessary tools for success. In a well designed course, the instructor aids the students in their learning journey, but does not spoon-feed them. The results below display the desire that students have to work on problems by themselves, and only if unsuccessful, approach their instructor. Thus, it is important to be available to students when they need it, but also give them room to try themselves.

VISUAL

AUDITORY

READING/ WRITING

KINESTHETIC

MULTIMODAL

FOCUS GROUPS

All students in the cohort participated in the focus group sessions. Groups were demographically divided, and the interviews were conducted after both the theory and design portions were completed. The sessions were conducted on Reading Day, and the only remaining submission was the final design project. This allowed students to reflect on the course as a whole, and provide their feedback independent of final grades received.

The focus groups were divided as follows:

Focus Group 1: 7 Undergraduate Students
Focus Group 2: 7 Undergraduate Students
Focus Group 3: 4 Graduate Students
Focus Group 4: 4 Students (Asynchronous)

The main opinions shared were as follows:

The majority of students seemed to like to mandatory attendance policy, as they believed it to motivate them to attend class and work with their peers. Since a majority believed that working with their peers allowed them to build on each others' competencies, this made a case for active learning and in-person involvement in engineering education.
The grading of the course followed a pass/ fail system. Students agreed in unison that this grading system took the pressure of performing tasks for grade points, and allowed them to be immersed in the learning experience. However, opinions on this system specifically for the midterms were polarized, with some students in favor and oters against. The ones in favor shared the opinion of the reduction in pressure to perform allowing them to do better in the test. The ones opposed to it added that while they favored the pass/ fail grades in all other course components, they wished the midterm had specific points so as to serve as motivators to push harder. This observation was interesting, because it allows for a clear display of the diversity in opinion.
Students were generally appreciative of the readings assigned, as they believed it provided them with a basis for understanding the concepts. When it came to revising the material however, they mainly relied on lecture slides, in-class notes, and homework. Thus, this demonstrated the flow of method of instruction that students utilized.
Something that stood out was the general consensus on 'Character Growth Assignments'. These assignments were optional and allowed student to make up for grades missed in other sections. Students seemed to unanimously agree that these assignments helped them reflect on themselves and their journey. After all, isn't education an endeavor for holistic development?
As for their design project, most students felt equipped to design a wastewater treatment plant at this point in the semester. The resources that they relied on when in doubt was mainly the BioWin tutorials, lecture slides, and homework assignments. The BioWin tutorials covered individual portions of the WWTP, and hence allowed students specific troubleshooting. In addition, the BioWin FAQ Guide provided them with quick solutions to any issues they may have with the software. Overall, students did not seem to struggle with the tool. As for integrating concepts, the majority felt that the in-class exercises and homework assignments involving problems allowed them to integrate multiple concepts, which is a crucial aspect of engineering design.

So, what resources did students rely on?

With a combination of quantitative and qualitative data, as well as observations of teaching and learning, & analysis of course design, I was able to answer my TAR Question

In Closing

The aim of this project is not to present data in a silo, or claim the superiority of a single learning theory. Instead, the primary message is that context is key. Being an engineer myself, and having studied an engineering classroom for this project, I was able to provide feedback and suggestions for engineering education. The theory of individual learning styles on its own may be debated, but when combined with learning content and modes of instruction, it become a useful tool for course design. A merit of this theory is the inclusion of diverse perspectives. In this project, though the majority of students of the course were found to be kinesthetic learners, there were a few students that fit into other modalities as well. When aggregated, this formed a significant proportion of the population. By considering diverse perspectives, course design allows for inclusivity. Catering to different learning challenges requires a mixture of flexibility and rigidity.

Another significant observation was the importance of collaboration. Facilitating a collaborative environment in which students may explore problem spaces themselves & with their peers is essential for understanding and long term retention. There is ample evidence in pedagogy of active learning being a direct contributor to student success. This, then, is an example of how student learning preferences, learning styles, and method of instruction is aggregated for success.

A key observation throughout the duration of this course was the role of the instructor. Dr. Byron Hempel was an outstanding support and resource to his students. His malleability and willingness to adapt to the needs of the students allowed him to be approachable and reliable. I would personally like to acknowledge the beauty in his course design, rooted in experience based teaching methods and pedagogical foundations. Understanding the why of the course design allowed me account for the how.

The final note is that reflection in individual teaching practices allows for a deeper understanding of what may have worked, what may have not, and what could be done better. Reflection not only makes us better instructors, but better people. When in doubt, the science of pedagogy may contain answers to building the classrooms of the future and instilling in students the lifelong gift of learning.

Acknowledgements

As the saying goes, it truly takes a village. this is especially evident in the educational sphere, where growth and learning is heavily coupled with the environment it is set in. I am extremely grateful to my course instructors Dr. Kristin Winet & Dr. Byron Hempel for their guidance, patience, and support through my journey. Kristin, thank you for your very valuable insights on communication, collaboration, and connection. I especially appreciate you always having a moment to lend me a ear for my seemingly endless questions. Byron, thank you for allowing me to utilize your course as the basis for my project. Through this experience, I not only learnt about the content of my project, but also about the thoughtfulness surrounding your course design and instruction.

To my accountability partners and fellow 'TAR Baddies' Heather, Oluchi, and Sushma, thank you for keeping me on my toes and aspiring me to do better always. To my fellow cohort members Paola, Josie, and Joe, what a pleasure it has been learning with you and working beside you! I thoroughly enjoyed this process of learning to teach by teaching to learn!

To the reader, if you have made it so far, thank you. I hope I kept you entertained and told my story well. If anything, I hope through this endeavor I have inspired you to look within, as I have in many moments through this journey. May we all work towards shaping the future through self-awareness, empathy, and kindness!

About the Author

I’m Joanna, a graduate student in the Department of Systems and Industrial Engineering at the University of Arizona. I have a bachelor’s degree in Mechanical Engineering, a master’s degree in Systems Engineering, and experience working in the energy and environmental industry.

My research lies at the intersection of the theoretic foundations of systems engineering and cognitive science. I am currently a researcher in the Disruption Lab, studying the role of human cognition and intelligence in engineering verification design and implementation.

In my free time I like to sleep, eat cheesecake, and am constantly on the lookout for the next best coffee spot to contemplate the mysteries of the universe. I've trained in Kathak, I like to hike, run away from my problems, watch obscure campy films, take my cactus Britney Pears on adventures, lovingly peeve my cats Violet and Felix, and my sister Angelina, find new music for my infinite playlist, and read anything I can get my hands on! I am also an amateur photographer, and several pictures on this page are mine.

I believe in education through empathy, and freedom through service. Kindness, acceptance, curiosity, humility, and love lie at the heart of my teaching philosophy.

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