As the usage of wireless technology grows, it demands more complex architectures and conformal geometries, making the manufacturing of radio frequency (RF) systems challenging and expensive. The incorporation of emerging alternative manufacturing technologies, like additive manufacturing (AM), could consequently be a unique and cost-effective solution for flexible RF and microwave circuits and devices. This work presents manufacturing methodologies of 3D-printed conformal microstrip antennas made of a commercially available conductive filament, Electrifi, as the conductive trace on a commercially available nonconductive filament, NinjaFlex, as the substrate using the fused filament fabrication (FFF) method of AM technology. Additionally, a complete high frequency characterization of the prototyped antenna was studied and presented here through a comparative analysis between full-wave simulation and measurements in a fully calibrated anechoic chamber. The prototyped antenna measures 65.55 × 55.55 × 1.2 mm³ in size and the measured results show that the 3D-printed Electrifi based patch antenna achieved very good impedance matching at a resonant frequency of 2.4 GHz and a maximum antenna gain of −2.78 dBi. Finally, conformality performances of the developed antenna were demonstrated by placing the antenna prototype on five different cylindrical curved surfaces for possible implementation in flexible electronics, smart communications, and radar applications.

Massive Open Online Courses (MOOCs) are allowing education to become accessible to all learners. However, computers are currently not able to provide the same individual expertise and support as a human instructor, making it difficult to tailor the course for each student. This work proposes using machine learning analytics to provide useful individualized feedback to learners in a Cardiovascular Engineering Innovation-Based Learning course. The system will monitor students’ habits as they form learning objectives and progress through the course, allowing the system to learn to make recommendations for the student. The architecture of the developed system is presented, a test set is used to verify, and the context of future pilot tests is introduced. Although this work is presently specific to one particular course, it can be adapted to allow for personalization of any MOOC that allows for differentiated, higher level learning.

The additive manufacturing (AM) process is gaining massive popularity among engineers and researchers. Due to the ever increasing demands of communication speed and bandwidth for catering versatile applications, radio frequency circuits are becoming more complex leading to higher manufacturing costs. One technique to address such challenges to use AM technology for fabricating next generation radio frequency circuits with very high precision. However, materials with far lower melting points than conventional metals are a necessity for currently available AM techniques. This paper investigates the possibilty of incorporating an improved version of an industrially available conductive material to design high frequency circuits for applications from 100 MHz up to 5 GHz. Measurement data and verification result using full-wave simulation is presented.

MOOCs and Innovation-Based Learning (IBL) models are efficient individually, but they also contain points of friction that limit their potential. Our research team has developed a synergistic learning model that combines the scale and accessibility of MOOCs with the innovative thinking, research, and development of IBL. Together, these two models benefit one another. This new learning model has the potential to alter the current higher education system by creating an opportunity for massive open online collaboration to solve today’s vexing problems. The following describes how MOOCs and IBL, in combination, benefit and enhance higher education’s potential.

MOOCs and virtualized educational media have enhanced the reach of specialized learning throughout the world. However, traditionally styled, lecture-based classrooms are lagging in incorporating 21 ^st -century teaching and learning methodology to develop innovative thinkers and problem solvers inside brick and mortar institutions. Using the blended classroom approach, a teaching and learning model was constructed that features the integration of MOOCs and Innovation-based Learning (IBL). The ideation and implementation of this combined MOOC and IBL course model is discussed below.

Our research group is currently engaged in an enhanced learning environment, within higher education, using Massive Open Online Courses (MOOCs) in combination with Innovation-Based Learning (IBL). Both approaches to learning when arranged correctly, improve students learning and engagement towards the course. When using IBL, one of the main problems that students experience is the selection of their class project. We propose a methodology based on funding opportunity announcements (FOA) to aid in the selection process. Student groups are able to quickly compare and match their skills and interests to market demand as expressed by groups such as NIH or NSF. The students in the class experience a blended approach; they collaborate online and in-class, and they apply knowledge acquired from online content to their main project. In this blended approach, FOAs act as a catalyst to students’ learning; it both focuses them at the beginning and motivates them throughout the course. Students in this MOOC-enabled learning ecosystem grow in their intrinsic motivation and engagement. Furthermore, FOAs project selection solves scalability issues when dealing with inter-disciplinary projects and availability of proper experts/mentors for students. This tailored combination improves efficiency and targets project’s relevance, which makes it very attractive to higher education administrators.