Montreal, Quebec, Canada
June 22, 2025
June 22, 2025
August 15, 2025
Computing and Information Technology Division (CIT) Technical Session 3
Computing and Information Technology Division (CIT)
Diversity
11
10.18260/1-2--55424
https://peer.asee.org/55424
5
Mahima Agumbe Suresh is an Assistant Professor at San Jose State University. She received her Ph.D. from the Department of Computer Science and Engineering at Texas A&M University in December 2015. After her Ph.D., she was a postdoctoral researcher at Xerox Research Labs, India, where she worked on crime analytics and process mining. Her research interests include edge computing, machine learning, modeling and system design for cyber-physical systems and the Internet of Things, and engineering education. She has published in several peer-reviewed conferences and journals and has been a program committee member at several conferences.
Algorithms and Data Structures are core concepts taught in all computing undergraduate programs. It is important to ensure that student activities in the class lay the foundation and prepare them for future courses and career. In addition, assessment should allow for students to develop a growth mindset. The course may benefit with a grading system can be designed to allow for students to revise and resubmit their programming tasks, have formative assessments to test their understanding, and focus on students mastering skills rather than chasing after points. In addition, active learning is a great way to provide hands-on engagement with the materials, which might prepare students better for future courses and career. This paper describes the author's experience in designing activities and specifications grading for an undergraduate core algorithms and data structures course.
Agumbe Suresh, M. (2025, June), Active Learning and Specifications Grading for Undergraduate Algorithms and Data Structures courses Paper presented at 2025 ASEE Annual Conference & Exposition , Montreal, Quebec, Canada . 10.18260/1-2--55424
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