Columbus, Ohio
June 24, 2017
June 24, 2017
June 28, 2017
Educational Research and Methods
Diversity
15
10.18260/1-2--28092
https://peer.asee.org/28092
754
Bugrahan Yalvac is an associate professor of science and engineering education in the Department of Teaching, Learning, and Culture at Texas A&M University, College Station. He received his Ph.D. in science education at the Pennsylvania State University in 2005. Prior to his current position, he worked as a learning scientist for the VaNTH Engineering Research Center at Northwestern University for three years. Yalvac’s research is in integrated STEM education, implementation of evidence-based pedagogies, 21st century skills, and design and evaluation of learning environments informed by the How People Learn framework.
Antonia Ketsetzi is a graduate student in the Department of Teaching Learning & Culture at Texas A&M University.
She received her BS degree in Mechanical Engineering at the Technological Educational Institute in Crete. She received her M.Sc degree in Environmental Technologies at University of Crete in Greece. Ketsetzi’s research is in How People Learn / Engineering Design and evaluation of educational innovations. She also serves as a Research Assistant in the project.
Antonia Ketsetzi, M.Ed.
Texas A&M University
ketsetzi@tamu.edu
Xiaobo Peng is an Associate Professor in the Department of Mechanical Engineering at Prairie View A&M University. He received his PhD in Mechanical Engineering from Missouri University of Science and Technology in 2005. His research interests include CAD/CAM, additive manufacturing, virtual prototyping, and engineering education. Dr. Peng is the member of ASME and ASEE.
Suxia Cui is an associate professor in the Department of Electrical and Computer Engineering at Prairie View A&M University (PVAMU). She joined PVAMU right after she obtained her Ph.D. degree in Computer Engineering from Mississippi State University in 2003. Her research interests include image and video processing, data compression, wavelets, computer vision, remote sensing, and computing education. Her projects are currently funded by NSF, United States Department of Agriculture, and Department of Education.
Lin Li is an associate professor of the Computer Science Department at Prairie View A&M University. He received his Ph.D. in computer science from the University of Nebraska at Lincoln in 2004. Before that, he received his B.S. and M.E. from Beijing Institute of Technology and Chinese Academy of Sciences in 1996 and 1999, respectively. His research interests are in Computer Networks, Machine Learning, and Computer Science Education.
Yongpeng Zhang received his BS degree in Automatic Control from Xi'an University of Technology in 1994, MS degree in Automation from Tianjin University in 1999, and PhD degree in Electrical Engineering from University of Houston in 2003. After one year post-doctoral research, he was appointed as the Tenure-Track Assistant Professor in Engineering Technology Dept at Prairie View A&M University in 2004 Fall, where he received promotion as the Tenured Associate Professor from 2010 Fall. His research interests include control system, mechatronics, motor drive, power electronics, and real-time embedded system design. As the Principal Investigator, his research has received significant sponsorship from Army Research Office, NSF, ED, and industry.
Deniz Eseryel joined North Carolina State University as a Chancellor’s Faculty Excellence Program cluster hire in the Digital Transformation of Education. She is an Associate Professor in the Department of Curriculum, Instruction, and Counselor Education specializing in Digital Learning and Teaching. She is also a Senior Research Fellow at the Friday Institute for Educational Innovation. The important but little understood question that has motivated her program of research is: How can we effectively and efficiently promote cyberlearning in complex knowledge domains such as STEM (science, technology, engineering and mathematics)? Towards this direction, she (1) investigates the development of higher-order thinking and complex problem-solving competencies following a comprehensive framework that includes cognition, metacognition, cognitive regulation, motivation, emotion, and epistemic beliefs; (2) develops innovative assessment methods that can benchmark progress of learning and the development of complex problem-solving competencies; (3) develops new and effective approaches to design state-of-the-art digital learning environments (such as intelligent tutoring, system dynamics modeling, simulations, virtual reality, and digital games) to facilitate complex problem-solving competencies; and (4) investigates effective ways to prepare teachers and administrators for digital transformation of education to support effective integration and seamless adoption of advanced learning technologies into education. In addition to her work focusing on STEM learning in K-20 educational settings, her research was also carried out in professional contexts including army, aircraft maintenance, air-traffic control, emergency response, environmental sciences, climate change, medical education, instructional design, architecture, construction science, mechanical engineering, industrial engineering, and systems engineering.
T. Fulya Eyupoglu is a Graduate Research Assistant at the Friday Institute and PhD student in TELS with a specialization in Digital Learning and Teaching. Aside from being enrolled in an NSF Project as a researcher, she also serves as a Teaching Assistant in the Instructional Design Course.
Tianyun Yuan is a graduate student and graduate research assistant in the department of Mechanical Engineering at Prairie View A&M University.Her research interests include evaluation of educational innovations,CAD modeling, product design and additive manufacturing (AM) technology.
Multiple efforts were undertaken to improve engineering professors’ teaching approaches. A review of literature revealed that engineering professors’ teaching approaches improved the most when they fully engaged in educational research. Professors’ teaching approaches significantly evolved from a knowledge-centered and teacher-focused orientation to a learner-centered and student-focused orientation when they designed and implemented their own evidence-based instructional strategies in their classrooms, collected data from their students, analyzed the data collected, and reported the findings in academic settings. Professors’ self-reflection on educational research and meta-cognition in evidence-based pedagogies were central, and instrumental, for their changes in approaches to teaching.
Based on this theoretical framework, four engineering professors and four learning scientists have worked together over two years to transform the culture of engineering education at a Historically Black College and University (HBCU) in US. The overarching goal is to increase the historically underrepresented students’ participation in STEM fields by enhancing the quality of the undergraduate engineering education at the selected HBCU. This three-year project is funded by the department of education and aimed at cultivating evidence-based pedagogies in engineering undergraduate education in the selected HBCU.
Four professors in Computer Science, Electrical Engineering, Mechanical Engineering, and Engineering Technology designed evidence-based instructional strategies that are learner-centered and student-focused. The learning scientists consulted the professors. Among the strategies designed and implemented are student-led recitation hours, discussion of current events, peer-teaching, peer-tutorial design, and peer-courseware design.
Our team designed and implemented evaluation instruments to capture the impact of the newly implemented strategies on students’ learning experiences and outcomes, including content understanding, life-long learning skills, and engineering attitudes. The data collected were analyzed and the findings were reported. Our professors iterated their design efforts. We anticipate that the professors’ active engagement in educational research will transform their teaching approaches. The main research question is “What are the changes in engineering professors’ approaches to teaching before and after the project activities?”
To answer the research question, we employed two evaluation instruments; an Approaches to Teaching Inventory (ATI) and a semi-structured interview protocol. ATI is a five-point Likert-scale with 16 items, designed to capture the academics’ approaches to teaching. Four professors completed ATI two times, once before the project (Spring 2015) and once after they taught two semesters (Summer 2016). ATI generates quantitative data. The interview protocol was used to collect qualitative data from the participants about their approaches to teaching. We conducted two interviews with each participant at the same time they completed ATI. Each interview lasted around 45 minutes. We recorded the conversations and transcribed verbatim. The constant-comparative method was used in the qualitative analyses. Each professor’s teaching approaches in Spring 2015 and in Summer 2016 were documented and compared.
In this paper, we will report our project activities, the research design, and findings from the first year. Both of the quantitative and qualitative findings reveal that participating engineering professors have already improved their teaching approaches from a knowledge-centered and teacher-focused orientation to learner-centered and student-focused orientation.
Yalvac, B., & Ketsetzi, A., & Peng, X., & Cui, S., & Li, L., & Zhang, Y., & Eseryel, D., & Eyupoglu, T. F., & Yuan, T. (2017, June), Cultivating Evidence-Based Pedagogies in STEM Education Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--28092
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