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Discipline: Technology & Engineering
Subcategory: STEM Research
Yachi Wanyan - Texas Southern University
Co-Author(s): Xuemin Chen and David Olowokere, Texas Southern University, Houston, TX
This study aims to initiate research-supportive curricula in the Department of Engineering for undergraduate students. The overarching goal is to infuse innovative electrical/computer engineering specialized Artificial Intelligence (AI) tools into traditional engineering problem-solving routines by problem-based learning (PBL) approach to bridge current curricula gap in the Department of Engineering at Texas Southern University (TSU). Several major steps were taken towards three specific objectives during the first one and half year of funded effort: 1) to develop an interactive and comprehensive intelligent database that can document, compare, and analyze cutting-edge AI applications in CE field and use it as the platform and educational media for curricula development and implementation; 2) to integrate AI approach into engineering curriculum; and 3) to support undergraduate students’ early involvement in research. The PI has carefully selected two core courses from current CE degree plan to pilot and study students’ responses to the new approach of applying AI tools in solving a traditional CE topics. Two pilot studies were carried out: In the first group, small number of undergraduate students (<5) were selected to explore the possibility of using one particular AI tool to solve a specified problem as extra-curriculum project. In the second group, the whole class (50+ students) was given the same open-end problem as term project. The PIs conducted observational and survey studies to observe the feasibility and effectiveness of infusing AI into traditional curriculum. These case studies will also serve as the foundation for later experimental and longitudinal studies. Based on the data collected during the first year the following conclusions were made: 1) The proposed knowledge-based expert system (KBES) provides rapid prototyping which enabled the “Lego-building” learning approach. The new instructional approach provides students excellent hands-on learning experiences that kept them motivated and interested. 2) Based on the preliminary case study results, the new approach has noticeably enhanced and enriched the students’ experience by in depth learning, generating new knowledge through the exploration of new ideas, improving communication and problem-solving skills. 3) PBL approach is an appropriate instructional method to infuse AI into traditional engineering curriculum. The proposed KBES platform for classroom teaching provided students rich and real-world problem scenarios. Student learning focused on solving the problems in diverse situations either by themselves or through group activities. The entire process is believed to better engage students in active learning through meaningful experiences of analyzing the scenarios, identifying problems, finding out the best solutions and applying them to solve the problems with guidance and facilitation from instructors.
Funder Acknowledgement(s): NSF HBCU-UP Targeted Infusion Award HRD1533569
Faculty Advisor: None Listed,
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