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In recent years, eye-tracking (ET) methods have gained an increasing interest in STEM education research. When applied to engineering education, ET is particularly relevant for understanding some aspects of student behavior, especially student competency, and its assessment. However, from the instructor’s perspective, little is known about how ET can be used to provide new insights into, and ease the process of, instructor assessment. Traditionally, engineering education is assessed through time-consuming and labor-extensive screening of their materials and learning outcomes. With regard to this, and coupled with, for instance, the subjective open-ended dimensions of engineering design, assessing competency has shown some limitations. To address such issues, alternative technologies such as artificial intelligence (AI), which has the potential to massively predict and repeat instructors’ tasks with higher accuracy, have been suggested. To date, little is known about the effects of combining AI and ET (AIET) techniques to gain new insights into the instructor’s perspective. We conducted a Review of engineering education over the last decade (2013–2022) to study the latest research focusing on this combination to improve engineering assessment. The Review was conducted in four databases (Web of Science, IEEE Xplore, EBSCOhost, and Google Scholar) and included specific terms associated with the topic of AIET in engineering education. The research identified two types of AIET applications that mostly focus on student learning: (1) eye-tracking devices that rely on AI to enhance the gaze-tracking process (improvement of technology), and (2) the use of AI to analyze, predict, and assess eye-tracking analytics (application of technology). We ended the Review by discussing future perspectives and potential contributions to the assessment of engineering learning.

We review the scholarly contributions that utilise natural language processing (NLP) techniques to support the design process. Using a heuristic approach, we gathered 223 articles that are published in 32 journals within the period 1991–present. We present state-of-the-art NLP in-and-for design research by reviewing these articles according to the type of natural language text sources: internal reports, design concepts, discourse transcripts, technical publications, consumer opinions and others. Upon summarising and identifying the gaps in these contributions, we utilise an existing design innovation framework to identify the applications that are currently being supported by NLP. We then propose a few methodological and theoretical directions for future NLP in-and-for design research.

The COVID-19 pandemic has caused an unprecedented crisis for the air transportation industry, affecting millions of aviation users and stakeholders. As the aviation sector has faced disease outbreaks and extreme events before—albeit not at the same scale—and will, in all likelihood, face them again, we provide an assessment in this study that a) gives an overview of the effects of the pandemic, b) categorizes the response mechanisms that were observed, and c) proposes a framework for a coordinated global response to future disease outbreaks. We highlight that of the many lessons, recommendations, and suggestions that emerged during previous outbreaks, few were introduced effectively into civil aviation practices and operations. Based on multiple data sources for passengers, cargo, and flight schedules, we assess the impact of COVID-19 on the global aviation industry and compare the data of some prominent airports to highlight the need for a coordinated response to effectively deal with future disruptions. As global aviation navigates its ongoing recovery, we discuss different responses during the pandemic including guidelines issued by bodies such as the International Civil Aviation Organization (ICAO), operational decisions such as closing terminals, increased cleaning frequencies, and mask mandates etc. We emphasize the need for resilience to accommodate disease outbreaks in future planning, design, and preparedness strategies for airports and airlines. We further argue that the existing civil aviation system needs a coordinated global response mechanism to combat future outbreaks and propose a framework with a threat response matrix to keep aviation safe and operational during future pandemics and mitigate socioeconomic fallout.