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It is widely acknowledged that active learning strategies increase engagement and long-term retention, while reducing attrition and frustration of students with less academic preparation and self-efficacy. Promoting active learning methods in STEM has been a long-term project in higher education. This study examines the perceptions of active learning techniques in online STEM education, leveraging a large, diverse sample (N = 727) across four STEM fields. The post-pandemic context of the study offers unique insights into how students and faculty perceive the effectiveness of various active learning methods in a rapidly changing educational environment. For eight of the nine methods studied, more than half of students and faculty found each active learning strategy to be helpful for online learning achievement. On average, both students and faculty found active learning methods to be modestly more important in online courses than face-to-face courses. A novel finding that was striking was that by a wide margin, both students and faculty perceived requiring activities more helpful than offering them on an optional basis. This implies that active learning methods become a meaningful portion of the course grade. However, faculty and students disagree on how heavily such activities should contribute to course grades. On average, students believe about half of their grade (52%) should comprise active learning activities, whereas faculty report that 32% of grades in their courses come from formative active learning assessments. The implications of activity-based STEM learning in online courses are discussed. 

The advent of heterogeneous integration (HI) places new demands on EDA tooling. Building large systems requires (1) methods for chiplet disaggregation that map the system to smaller chiplets, working in conjunction with system-technology co-optimization to determine the right design decisions that optimize computation and communication, together with the choice of substrate and chiplet technologies; (2) multiphysics and multiscale analyses that incorporate thermomechanical aspects into performance analysis, ranging from fast machine-learning- driven analyses in early stages to signoff-quality multiphysics-based analysis; (3) physical design techniques for placing and routing chiplets and embedded active/passive elements on and within the substrate, including the design of thermal and power delivery solutions; and (4) underlying infrastructure required to facilitate HI-based design, including the design and characterization of chiplet libraries and the establishment of data formats and standards. This paper overviews these issues and lays out a set of EDA needs for HI designs. 

This study investigates students’ perceptions of rehearsal (test preparation) and testing after the pandemic forced increased online teaching use and experimentation. Data was gathered from information and decision sciences (IDS) students in an underrepresented minority (URM) serving university. Responses from 136 participants were analyzed and revealed four major findings. The single most interesting finding was that students, on average, preferred graded rehearsal activities over optional activities. Second, rehearsal activities were more important in online than face-to-face settings. Third, students overwhelmingly prefer online exams, on which they feel they perform better and which they find less anxiety-producing. Finally, despite research showing the importance of online proctoring for major defined-answer testing, instructor use of proctoring and monitoring is split between those who do and do not use concrete methods, with lockdown browser being common and live webcam less common. These interconnected findings are discussed.