Arlington, Virginia
March 12, 2023
March 12, 2023
March 14, 2023
Professional Engineering Education Papers
16
10.18260/1-2--44992
https://peer.asee.org/44992
193
Ioulia Rytikova is a Professor and an Associate Chair for Graduate Studies in the Department of Information Sciences and Technology at George Mason University. She received a B.S./M.S. and Ph.D. degrees in Automated Control Systems Engineering and Information Processing. Her research interests lie at the intersection of Data Science and Big Data Analytics, Cognitive and Learning Sciences, Educational Data Mining, Personalized Learning, and STEM Education.
Mihai Boicu, Ph.D., is Associate Professor of Information Technology at George Mason University, Associate Director of the Learning Agents Center (http://lac.gmu.edu), Directtor of Laboratory for Collective Intelligence, Co-Director of Personalized Learning in Applied Information Technology Laboratory (http://plait.gmu.edu/).
Harry is currently Associate Professor at George Mason University's Department of Information Sciences and Technology. He earned his doctorate in Information Technology in 2003 from George Mason University's Volgenau School of Engineering (Fairfax, VA), and has since taught graduate courses there in big data analytics and ethics, operating systems, computer architecture and security, cloud computing, and electronic commerce.
Dr. Olesova is Assistant Professor of Educational Technology in College of Education, the University of Florida. Her research interests are Community of Inquiry, cognitive presence, metacognition, learning analytics, social network analysis, online engagement and interactions and online instructional strategies.
Graduate Engineering students need to understand and use the concepts and methods of applied research when they enter the engineering workforce. Using the principles of the Practical Inquiry Model (PIM) for such instruction can be effective in guiding such students in the research process to enhance their interest in and use of applied research methods. The PIM is a socio-constructivist approach that can enhance reflective thinking and collaboration to prepare them for their future workplace. To understand learning within the PIM, we examined students’ perceived cognitive presence during applied research activities. Cognitive presence consists of four levels including: triggering events, exploration, integration, and resolution. The majority PIM studies examined students' perceived cognitive presence in discussions in Education, Foreign Languages, or Professional Development. The field is still limited in research on how engineering students perceive cognitive presence in online courses. We believe that findings can fill the gap by providing more evidence about engineering students. This study developed and implemented a suite of customizable online learning modules to guide students in applied research. The learning modules were divided into three steps: research question, literature research, and conducting research using a generic template with the following sections: annotated open source learning materials, a random knowledge test with a pool of case study questions, a discussion board for brainstorming which required students to post their draft ideas, to comment on other students’ posts and integrate the comments in their submission, a self-reflection assignment to summarize the lesson learned, and a written assignment to organize their findings, make connections, elaborate ideas, and construct an argument based on their research. The modules were implemented in five courses in the Master of Science in Applied Information Technology program and in the Master of Science in Data Analytics Engineering at the College of Engineering and Computing at George Mason University. A post-course self-assessment survey about the research modules was administered to the 167 enrolled students and 126 responses were received. The survey was the modified version of the Community of Inquiry survey and included 5-point Likert-scale questions assessing the students’ levels of perceived cognitive presence, satisfaction with components of the modules, including their interest in and curiosity about applied research, and their motivation to use what they had learned, resulting in an overall 86.2% responding Satisfied or Extremely Satisfied with the modules. Subsets of the respondents, including online vs in-person instruction, individual courses, and programs of study, for example, showed similar results. While the sample size was small there was a strong indication that the modules were successful in promoting greater understanding and planned use of applied research concepts and methods. Furthermore, the research modules may be applicable to general research education, in addition to applied research. The early and broad introduction of applied research instruction in the engineering curriculum may enhance efforts to increase STEM participation in future research employment opportunities and doctoral education, especially for underrepresented groups and first-generation graduate students.
Rytikova, I., & Boicu, M., & Foxwell, H. J., & Liao, D., & Olesova, L. (2023, March), Cognitive Presence Learning for Graduate Engineering Education Paper presented at ASEE Southeast Section Conference, Arlington, Virginia. 10.18260/1-2--44992
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