This project is addressing a crisis throughout engineering education, and cyberinfrastructure education regarding decreasing enrollments, under preparation and disengagement of students, and the pressure of faculty to cover increasing volumes of material. Curricula have become stove-piped and disconnected, in spite of research indicating that science and engineering education best resonates with women and underrepresented minority students and when clear connections are drawn to transformative applications and other fields of study. Industry routinely lobbies for better engineering graduates that are at ease when collaborating on teams, and eager to attack hands-on design challenges.
The academic/industrial/professional society partnership between Rice University, Georgia Institute of Technology, Rose-Hulman Institute of Technology, the University of Texas at El Paso, National Instruments, Texas Instruments, Hewlett-Packard, and the Institute for Electrical and Electronics Engineers Signal Processing Society directly attacks these issues by aiming to revolutionize the way they teach and learn about cyberinfrastructure. They are guided by a common vision: to prepare the cyberinfrastructure leaders of tomorrow, to break away from the traditional textbook, lecture, homework-based approach to education, and to build a new framework where a vibrant network of educators, students, and field practitioners continually interact, collaborate, connect, and explore interactive content.
The innovative aspects and scientific merits of this collaborative project lie in their new approach to building and sustaining virtual educational communities around interactive content and applying the results to the full spectrum of engineering education venues: university undergraduate and graduate courses, industrial training and continuing education, just-in-time on the job learning, and high-school laboratories. Their research focuses on one strategic discipline in engineering, signal processing, and involves and balances education, community development, technology development, marketing and business planning, and impact assessment. The partnership is: 1. Implementing a light-weight Technology Framework that enables faculty and student users to exploit and expand upon the existing signal processing education content; 2. Building a signal processing Education Network of champions from faculty, students, and industry leaders nationwide that continually expands, improves, and diversifies the materials and that promotes the use of the framework both at network member institutions and at institutions in the wider engineering education community; 3. Assessing the effectiveness of the framework and network for accelerating adoption and use as well as the value of the mentoring and support provided by the network of champions; 4. Widely Disseminating the results and lessons learned.
Broader impacts of this research include the development of people-resources and technologies that will substantially increase the performance and capabilities of engineering educators, effectively opening up engineering education for motivated self-learners in all parts of the nation as well as the world. In particular, education in digital signal processing and related technologies is critical in sustaining many high-tech industries. Finally, digital signal processing educators, practitioners and students will be brought together to form dynamic knowledge sharing communities that greatly impact education not only on their home campuses but around the world.
Two notable outcomes from this project were the development of on-line questions and answer (Q&A) material for signal processing and engineering probability classes, and the sharing of that material by instructors at multiple universities. The style of learning used by today's students coupled with the rise of flipped classrooms, recitations, and on-line courses such as MOOCs necessitates a different approach to homework assignments in engineering classes. Repositories of quick-response homework questions that can be assessed immediately and automatically are valuable and useful for providing feedback to students, and also for providing an instructor real-time information about conceptual areas in which the students are struggling. In this project, two on-line Q&A systems were developed, ITS at Georgia Tech and Quadbase at Rice, and and these systems were used by many students at multiple universities. The ITS questions were integrated into a basic signal processing course as concept-tagged homework with immediate assessment. The Quadbase questions, which were developed by instructors at several institutions, were used in a flipped classroom environment to stimulate classroom interactivity for an introductory engineering probability course. Students have reacted favorably to these systems because they provide new learning opportunities. The significant outcome from this research project is that sharing such respositories offers a new resource for building basic engineering courses with more student engagement.
