My approach to teaching an undergraduate level course is different from my plan to teach a graduate level course. My experience from observing and teaching the statics course, as well as having been an undergraduate student, has lead me to believe that a majority of the students find it hard to make the transition from high school to college level. Hence, my philosophy for teaching fundamental courses like statics, mechanics of solids, reinforced concrete etc. is as follows. I will use the first few class periods to go slow with the concepts while relating every new concept to something they are already familiar with. Considering taking stairs as an analogy to learning, I will proceed one step at a time because it is easy to lose students if I start jumping too early. It is easier for students to make harder jumps up the stairs of learning when they possess the skills of relating concepts to each other. As chapters progress, I will continuously refer back to concepts they learned in earlier chapters to facilitate the establishment of these relations.
Structural engineering courses involve problems that require critical thinking and clever solution skills to succeed in exams. In addition to solving problems during lecture hours, my students will also get access to pre-recorded tutorial videos (recorded by myself) that emphasize on trickier problems and their solutions. I will create an environment in the class conducive to asking questions by pausing for questions as well as encouraging the students to interrupt me at any point. In my limited experience, appreciating good questions, answering them and posing a related question (when needed) and answering that one as well has seemingly increased class participation.
In addition to coursework, I will encourage interested undergraduate students with good academic standing to perform independent research. Depending on their interest, this will either be studies that would add value to the field such as creation of software tools to perform problem specific analyses or hands on contribution to projects explored by graduate students. This will enhance their understanding of the subject as well as their portfolio for the job market.
For graduate level courses, I do not see the same approach being effective. The students at this level have chosen this field of study and hence will be much more intrigued to know more. Building up from basics that they already know is still an effective strategy. However, the similarities with undergraduate level courses end there. Graduate students need to be challenged more. Although lectures will be the primary source of information, some information required to complete weekly homework will have to come from external sources. More than solving ‘text book’ problems, graduate students need to solve open ended problems that are either research or practice oriented.
My goal is to include state-of-the-art research within the coursework. Also included in the coursework will be problems in the respective area that are currently being researched. For example, in a course pertaining to Earthquake Engineering, nonlinear time-history analysis is taught as the the tool used for design verification. However, the nuances of ground motion selection for such analyses are often given short shrift. One reason for this is because this is an open area of research and a conclusive answer as to what ground motions need to be used has not been found. Regardless, the concept of the Conditional Mean Spectrum has sprung up as a viable option. I will incorporate state-of-the-art concepts such as these in my curriculum albeit it will be some time before these are incorporated in design codes.
I would like to create a graduate level course offering on Probabilistic Earthquake Engineering that will contain basic and advanced concepts from both sides of the seismic design equation; demand and capacity viewed through the lens of classic probability theory. An important objective of the course will be to prepare students to perform probabilistic hazard risk assessment. With the advent of big data and machine learning, I envision a future where probabilistic algorithms can help humans make better informed decisions.
My Inspiration to teach stems from a self-realization of finding it easy to make people understand technical concepts. I could sense the level of understanding of the listener and frame my explanation suited to that level. I discovered this at a summer internship I did in 2015 with Duke Talent Identification Program (TIP). The internship was for a period of two months teaching two separate classes (one each month) for gifted middle-school students. The course was ‘Design Challenges: Physics and Engineering”. My job was to create and execute a crash course of advanced concepts in physics tailoring to the needs of gifted 6th to 8th grade students to challenge them and encourage rapid academic development. My syllabus was inspired from my background in civil engineering and focused on topics such as kinematics, and Newtonian mechanics and how these simple concepts help engineers solve real world problems. I received positive feedback from the students as well as the academic coordinator. I think back to this as the experience that solidified my interest to teach.
As a graduate student, I have had opportunities to mentor undergraduate students. The first was to mentor a single undergraduate student in his research as part of a university wide undergraduate research program. This research was for 4 months wherein the student assisted me as well as performed tests on his own. These tests directly contributed to my final dissertation. From conversations with him, I learned his expectations of a mentor. This allowed me to adjust my approach to make both of our time worthwhile. For instance, when instructing him on certain research methods, I would often repeat myself regarding minute details. I had assumed that this would reinforce his learning. However, I soon learned that he was a fast learner and repetitive instructions were superfluous to the whole process. I changed my approach appropriately as a result.
A second opportunity came along when I was elected as the advisor for the undergraduate team participating in the seismic design competition (SDC) representing NC State University at the annual meeting of the Earthquake Engineering Research Institute (EERI). This team consisted of eight members and my role was to act as a consultant to the team. Their goal was to build a small-scale balsa wood building that would perform well in an artificially simulated earthquake. Designing such a building involved understanding basic concepts of structural dynamics and earthquake engineering that are only covered in the graduate level courses. My responsibility included educating the team on these concepts to prepare them for presenting their research at the EERI Annual Meeting during 5th to 8th March, 2019 held at Vancouver, Canada. I advised the team during weekly meetings regarding the basics of earthquake resistant building design. This required bridging a large gap between their current knowledge on structural analysis and design for static systems, and the introduction of complex variables such as dynamic loads, vibration theory, and unintentional consequences of simplified design.
Presently, I am part of a cohort in a program offered at NC State University titled Preparing the Professoriate. This program has provided me with a unique opportunity of observing and being mentored by an established faculty member of my choice for a semester in the execution of an undergraduate course. I am currently being mentored by Dr. Rudi Seracino in the undergraduate course on statics. In Fall semester of 2019, I will be teaching the same course to a full class of undergraduates. Although the teaching part of the program is not until the spring semester of 2019, I have already taught four class periods to a class of 107 students while filling in for Dr. Seracino when he was travelling.
Knowledge is a special thing because it allows people to progress by achieving goals they could not have achieved without it. Therefore, passing knowledge comes with high responsibility as well as pleasure of giving something back to the society.