Natural language processing and machine learning can be applied to student feedback to help university administrators and teachers address problematic areas in teaching and learning. The proposed system analyzes student comments from both course surveys and online sources to identify sentiment polarity, the emotions expressed, and satisfaction versus dissatisfaction. A comparison with direct-assessment results demonstrates the system's reliability.

New and innovative technologies enable a variety of instructional environments that help students overcome many traditional boundaries and constraints to learning. As the classroom becomes more of an abstraction than a physical space, educators and learners embrace a variety of pioneering tech-powered teaching and learning paradigms that will serve students well upon graduation.

Until the day comes when all vehicles are fully autonomous, self-driving cars must be more than safe and efficient--they must also understand and interact naturally with human drivers.

Neurotechnologies in clinical applications can image the brain noninvasively, but they typically require surgical insertion to stimulate it. Although an increasingly popular alternative is to use noninvasive stimulation to enhance nervous system functions, questions about its effectiveness and ethical use remain unanswered.

Through a combination of wearable cameras, hardware accelerators, and algorithms, a vision-based automatic shopping assistant allows users with limited or no sight to select products from grocery shelves.

In the workplace of the future, people will need to be comfortable working alongside digital intelligence, and businesses will need to find the optimal pairing of humans and machines.

New editor Scooter Willis reflects on his journey to becoming an electrical engineer and how we can promote the work of students who've found their passion. Scooter Willis, "You Never Forget Your First Project", Computer, vol.

In a global economy, online meeting participants often have different backgrounds, making it difficult to know their mental and physical states. The Mental Motion State Model, trained by applying the Gaussian mixture model to electroencephalogram data, can indicate degrees of engagement and fatigue levels, providing a feedback channel for self-regulation. In the web extra at https://youtu.be/-lO3jsMUJVU, guest editor Katarzyna Wac interviews author Renate Fruchter, founding director of the Project Based Learning Laboratory at Stanford University. Tongda Zhang, Renate Fruchter, Maria Frank, "Are They Paying Attention?

Despite new technologies that make face detection and recognition more sophisticated, long-recognized problems in security, privacy, and accuracy persist. Refining this technology and introducing it into new domains will require solving these problems through focused interdisciplinary efforts among developers, researchers, and policymakers. Zahid Akhtar, Ajita Rattani, "A Face in any Form: New Challenges and Opportunities for Face Recognition Technology", Computer, vol.

Advances in embedded systems and communication technologies--along with the availability of low-cost sensors--have led to a pervasive presence of cyber-physical systems. However, several intelligent functionalities that are necessary to meet user and application demands are missing from current solutions. A homogeneous and integrated framework supporting intelligent mechanisms can fill this gap.