This full research paper describes the research areas and funding trends through NSF funded awards in engineering education. Engineering Education Research (EER) has traditionally spanned fives main areas of research [1] including engineering learning mechanisms, engineering learning systems, engineering epistemologies, engineering assessment and engineering diversity and inclusiveness as written by the original author. However, in a recent online content analysis of the U.S. institutions that offer engineering education academic programs or serve as engineering education research centers and research groups, we found additional areas that are missing in research. These gaps were mapped between the existing research areas and the ones advertised on institutional websites. This study considered the National Science Foundation (NSF) funded awards from the Division of Engineering Education and Centers (EEC) publicly available on the website which listed about 752 projects with a starting date between 2012 and 2022. The list of these awards was extracted from the website on August 25, 2022. These awards were mapped onto five research areas to aid in identifying unexplored and underexplored research areas. The funded awards were divided into different categories based on the labelled titles of funded awards by NSF. Additionally, this study explored the universities/organizations that had the highest number of funded awards and the highest amount of funding within this timeframe. The findings suggest a dire need for research in epistemologies, learning mechanisms, and assessments in engineering education. It sheds light on the uneven distribution of funding trends in the field of engineering education. This exploratory study builds upon the significance of the research areas in EER and funding trends for different institutions in engineering education. The paper concludes with a call for the engineering education research community to discuss ways to incorporate more research in the gap areas, equitable funding, as well as consider the possibilities for future work in engineering education.

This innovative practice full paper analyzed over 900 responses related to awareness of the hidden curriculum to explore the relationships between expressed emotions among students and faculty members. The hidden curriculum refers to the implicit values, behaviors, and norms that are not formally included in educational programs but are learned through the social and cultural environment of an institution. Using both emotional and demographic data collected from a larger national survey of engineering educators and students across the U.S., we examined correlations between participants' responses and the sentiment classifications observed. Our analysis employed two distinct tools: VADER for sentiment analysis and a pre-trained Recurrent Neural Network (RNN) model capable of classifying six specific emotions. Through detailed analysis and comparison, we uncovered significant insights into the emotional dynamics within engineering education. Overall, we found a predominance of positive sentiment, with “joy” emerging as the most frequently expressed emotion among both students and faculty. However, we also identified nuanced variations in emotional expression, influenced by factors such as gender, engineering disciplines, and the sentiment analysis methods employed. These findings contribute to the ongoing discourse on the hidden curriculum's impact on emotional experiences, emphasizing the importance of considering both sentiment and distinct emotional states in educational research and practice. By providing a deeper understanding of emotional patterns, this research offers valuable perspectives on how emotions shape the educational experience in engineering.

Engineering Education has emerged as an interdis-ciplinary field of research which focuses on gaining effective knowledge on engineering concepts, improving teaching method-ologies and enhancing students' learning. There is a need for more U.S. institutions to establish engineering education centers for expansion of existing research agendas as well as delving deeper in the research areas identified. This research undertakes an online content analysis of engineering education centers in seven (07) U.S. institutions to explore emerging trends of research being conducted, the existing programs offered, and the academic background of faculty members working in these centers. The research areas in Engineering Education spans engineering epistemologies, engineering learning mechanisms, engineering learning systems, engineering diversity, and inclusiveness and engineering assessment as written by the original author [1]. According to these institutional websites, the research areas that are most worked upon include engineering learning mechanisms and engineering learning systems. The research areas that are least worked upon fall under the category of engineering epistemologies, and engineering diversity and inclusiveness. The programs offered in these centers include certifications, fellowship programs (for faculty and graduate students), while some centers also offer master's degree programs. The faculty members working in these centers are predominantly Ph.D.s in engineering (55%); the top three being mechanical engineering, biosystems and agricultural engineering, and engineering education. It is found that the research areas, that consider students' social contexts and diverse human talents, are least worked upon, or communicated by these centers although these areas are endorsed by National Science Foundation (NSF), National Academies Science Engineering Medicine (NASEM), and ABET criteria. The objectives of the academic programs are also limited in terms of research areas in these institutions. The findings also suggest the need of more engineering education centers to offer training and teaching programs covering all five research areas in engineering education.

This panel is dedicated to a comprehensive exploration of the critical role that multimodal measurement plays in enhancing our understanding of complex human experiences. It serves as a valuable resource for both seasoned researchers and aspiring students who aspire to create their own multimodal laboratories. In today's research landscape, where human experiences are increasingly multidimensional and nuanced, the importance of employing diverse measurement techniques cannot be overstated. Through this panel, attendees will gain a profound appreciation for how combining various modalities, such as electrodermal measurement, surveys, and eye-tracking, can yield a more holistic and profound comprehension of human perception, cognition, and emotional responses.