The Value of Forming a Computational Mindset as Undergraduates
Anne Raich, Civil and Environmental Engineering, Valparaiso UniversityI have worked for the past 15+ years as a civil engineering professor at Valparaiso University and Lafayette College. Both Valpo and Lafayette College offer undergraduate-only, engineering degree programs and both place a strong emphasis on facilitating undergraduate learning and research experiences. My teaching experience covers the areas of structural design and analysis and computational methods and applications (numerical methods, programming, traditional and heuristic optimization and machine learning). These courses span over three different aspects of the engineering process: analysis (single solution driven), design (multiple solutions possible), and search and optimization (modeling and computer programming intensive).
Two of the main challenges that I have found in teaching computational topics are 1) the time required for students to gain the fluency, and the needed confidence, to start working independently on computational problems and 2) to the institutional resource investment required, in terms of time, support and technology, needed to design compelling, engaging, realistic problems for students to tackle that 'hook' them in and ignite their curiosity to learn more.
Overcoming both of these challenges requires that departments not only recognize the value of computational skills and mindset for students, both in practice and in research, but also that they actively involve faculty across disciplines in designing integrated computational experiences throughout the four years of the curriculum. This requires faculty to work together and specifically target learning outcomes and assessments to help students learn computational skills.
I have been part of these efforts since I began teaching. My goal is to "convince" students to become so familiar with a broad set of 'tools' and skillsets that it becomes second nature to turn to these when solving complex problems.
There is an opportunity to teach students to think computationally and to seek computational solutions. These efforts can result in a systematic change in how these students solve problems and in general use information to make decisions, including by:
- Expanding the type of information (data) that they can rely on to make decisions.
- Performing their own data analysis and classification to 'see' patterns or use it to predict behavior.
- Optimizing designs so that they use resources more wisely
- Using sensors to monitor systems and detect trigger events
My efforts help support curricular and course development within the department include developing problem studio-based modules that help students learn how to program and learn about numerical methods at the same time while working on applications from different areas of civil engineering and across the college by designing first-year introduction to engineering projects that are interdisciplinary and help students see connections across engineering disciplines while learning about programming, controllers, sensors, data acquisition and data processing. These efforts promote the integration of design thinking, experiential learning and a computational mindset and allow me to pursue work that I am passionate about – introducing students to the world of design and computational thinking and working with faculty and students on computationally-intensive projects that seek to increase decision-making capabilities and improve quality of life.
The challenges related to content and resources will likely continue since there is intense competition in our curriculum for what content will be covered in the 128 credit hours we have with and for resources overall. Since the most effective solutions to global challenges will increasingly require synthesizing knowledge from engineering, computer science, information technology, economics, policy studies, psychology and sociology and other areas, any argument against helping students form a computational mindset is hard to win! Even though the field of knowledge involved in applying computational modeling techniques to solve these problems continues to grow, the core topics and experiences that give students the 'basics' and the mindset needed are in reach of our undergraduate students.