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Turbulent boundary layers on immersed objects can be significantly altered by the pressure gradients imposed by the flow outside the boundary layer. The interaction of turbulence and pressure gradients can lead to complex phenomena such as relaminarization, history effects and flow separation. The angular momentum integral (AMI) equation (Elnahhas & Johnson,J. Fluid Mech., vol. 940, 2022, A36) is extended and applied to high-fidelity simulation datasets of non-zero pressure gradient turbulent boundary layers. The AMI equation provides an exact mathematical equation for quantifying how turbulence, free-stream pressure gradients and other effects alter the skin friction coefficient relative to a baseline laminar boundary layer solution. The datasets explored include flat-plate boundary layers with nearly constant adverse pressure gradients, a boundary layer over the suction surface of a two-dimensional NACA 4412 airfoil and flow over a two-dimensional Gaussian bump. Application of the AMI equation to these datasets maps out the similarities and differences in how boundary layers interact with favourable and adverse pressure gradients in various scenarios. Further, the fractional contribution of the pressure gradient to skin friction attenuation in adverse-pressure-gradient boundary layers appears in the AMI equation as a new Clauser-like parameter with some advantages for understanding similarities and differences related to upstream history effects. The results highlight the applicability of the integral-based analysis to provide quantitative, interpretable assessments of complex boundary layer physics. 

New engineering educators need to be equipped with instruments that can provide easy and meaningful insight into students’ self-directed learning (SDL) status so they can better foster students’ success. Students who are self-directed learners can independently initiate and take full responsibility for learning, effectively utilize available resources in the pursuit of their goals, develop awareness of their learning, and demonstrate the appropriate attitude essential for individual and collaborative learning. Despite these benefits, developing SDL skills in engineering students is often overlooked. To address this, educators have a facilitating role to play in the development of engineering students’ SDL skills, however, this role can be challenging for them due to the (a) high cost of using SDL instruments, especially in a large classroom and (b) uncertainty about the validity of SDL instruments. Moreover, these challenges may be more pronounced for new engineering educators. This study addresses these challenges by reporting the validity evidence for an SDL assessment instrument called the Self-Rating Scale of Self-Directed Learning (SRSSDL). The SRSSDL instrument has been widely utilized in medical education, but in this study, it was modified for the engineering education context. The utility of this 8-constructs, 46-item scale was demonstrated in engineering education with 111 undergraduate students across all academic levels, and the validity test was conducted in line with the contemporary validity framework. The result of the validity test of the SRSSDL revealed inconsistencies or instability of its constructs in the engineering education context. 

Lifelong learning plays an important role in achieving success in one’s professional life. Engaging students in metacognition assists in the development of their lifelong learning abilities. Instructors can integrate reflection activities in their courses to provide multiple opportunities to students for metacognitive engagement. During reflection, students regulate their cognition by engaging themselves in three dimensions of metacognition: Planning, Monitoring, and Evaluating. Reflection is a complex process, and it takes time to reach the level of critical reflection. The purpose of the study was to investigate the change in students' level of engagement in three dimensions of metacognition when reflecting on the third and tenth-week assignments of the environmental engineering course. Data collection took place in the Fall of 2023 at a large Midwest University. Students’ responses to the assigned reflection prompts for each dimension were coded for their level of engagement in each element of the three dimensions using a revised prior coding scheme. Results showed that for both assignments, students' responses were mainly at the vague level for all elements of the three dimensions, indicating students' superficial engagement in the reflection activity. Recommendations for instructors are provided to improve students' understanding of the reflection activity and their level of engagement in the three dimensions of metacognition. 

This paper explores the implementation and impact of reflective practices in engineering courses, as perceived by faculty members and teaching assistants (TAs) who integrated these strategies in their Spring 2023 course offerings. Reflection provides a valuable opportunity for students to enhance their learning process and become more self-aware of their strengths, weaknesses, and overall progress. This study aims to investigate the experiences and perceptions of instructors who employed reflective practices and gain insights into the effectiveness and challenges associated with their implementation. The qualitative research design employed for this study involved conducting in-depth interviews with faculty members and TAs from two engineering disciplines, civil and environmental engineering, and biological systems engineering. These reflective practices encompassed six reflections over the semester, all aimed at promoting metacognition and fostering meaningful learning experiences. The interviews were structured to elicit detailed information regarding the perceived usefulness of reflective practices, the strategies employed, the perceived impact on student learning outcomes, and any observed challenges encountered during implementation. Preliminary results from interviews with three faculty members and three TAs highlighted the diverse ways in which reflective practices were integrated into engineering courses. Common themes emerged concerning the perceived benefits, including student and instructor growth, better self-regulation skills for the students, deeper learning, and enhanced critical thinking skills. Moreover, instructors found that these strategies could foster a more productive learning environment and improved student-teacher communication. However, challenges included time constraints, student resistance, and off-topic reflections. Faculty members and TAs stressed the importance of clear guidelines and scaffolding to optimize the effectiveness of reflective practices and mitigate these challenges. The findings from this study will contribute to the scholarship of teaching and learning by providing empirical evidence on the successful implementation and positive outcomes of reflective practices in engineering education. This study also pinpoints valuable recommendations for instructors seeking to implement reflective strategies effectively. Additionally, the insights gained provide a foundation for further research and discussion regarding the integration of reflective practices into alternative STEM disciplines. 

Understanding and predicting turbulent flow phenomena remain a challenge for both theory and applications. The nonlinear and nonlocal character of small-scale turbulence can be comprehensively described in terms of the velocity gradients, which determine fundamental quantities like dissipation, enstrophy, and the small-scale topology of turbulence. The dynamical equation for the velocity gradient succinctly encapsulates the nonlinear physics of turbulence; it offers an intuitive description of a host of turbulence phenomena and enables establishing connections between turbulent dynamics, statistics, and flow structure. The consideration of filtered velocity gradients enriches this view to express the multiscale aspects of nonlinearity and flow structure in a formulation directly applicable to large-eddy simulations. Driven by theoretical advances together with growing computational and experimental capabilities, recent activities in this area have elucidated key aspects of turbulence physics and advanced modeling capabilities. 

Many processes of biological diversification can simultaneously affect multiple evolutionary lineages. Examples include multiple members of a gene family diverging when a region of a chromosome is duplicated, multiple viral strains diverging at a “super-spreading” event, and a geological event fragmenting whole communities of species. It is difficult to test for patterns of shared divergences predicted by such processes because all phylogenetic methods assume that lineages diverge independently. We introduce a Bayesian phylogenetic approach to relax the assumption of independent, bifurcating divergences by expanding the space of topologies to include trees with shared and multifurcating divergences. This allows us to jointly infer phylogenetic relationships, divergence times, and patterns of divergences predicted by processes of diversification that affect multiple evolutionary lineages simultaneously or lead to more than two descendant lineages. Using simulations, we find that the method accurately infers shared and multifurcating divergence events when they occur and performs as well as current phylogenetic methods when divergences are independent and bifurcating. We apply our approach to genomic data from two genera of geckos from across the Philippines to test if past changes to the islands’ landscape caused bursts of speciation. Unlike previous analyses restricted to only pairs of gecko populations, we find evidence for patterns of shared divergences. By generalizing the space of phylogenetic trees in a way that is independent from the likelihood model, our approach opens many avenues for future research into processes of diversification across the life sciences.