Tailored Computing Instruction for Economics Majors

Richard Lawrence, Zhenhua He, Wesley Brashear, Ridham Patoliya, Honggao Liu, and Dhruva K. Chakravorty

Volume 13, Issue 1 (April 2022), pp. 32–37


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  author={Richard Lawrence and Zhenhua He and Wesley Brashear and Ridham Patoliya and Honggao Liu and Dhruva K. Chakravorty},
  title={Tailored Computing Instruction for Economics Majors},
  journal={The Journal of Computational Science Education},
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Responding to the growing need for discipline-specific computing curricula in academic programs, we offer a template to help bridge the gap between informal and formal curricular support. Here, we report on a twenty-contact-hour computing course developed for economics majors at Texas A&M University. The course is built around thematic laboratories that each include learning objectives, learning outcomes, assignments, and assessments and is geared toward students with a high-school level knowledge of mathematics and statistics. Offered in an informal format, the course leverages the wide applicability of the Python programming language and scaffolding offered by discipline-specific, hands-on activities to introduce a curriculum that covers introductory topics in programming while prioritizing approaches that are more relevant to the discipline. The design leverages technology to offer classes in an interactive, Web-based format for both in-person and remote learners, ensuring easy access and scalability to other institutions as needed. To ensure easier adoption among faculty and offer differentiated learning opportunities for students, lectures are modularized to 10-minute segments that are mapped to other concepts covered during the entire course. Class notes, lectures, and exercises are pre-staged and leverage aspects of flipped classroom methods. The course concludes with a group project and follow-on engagements with instructors. In future iterations, curriculum can be extended with a capstone in a Web-based asynchronous certification process.