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We present a lattice QCD calculation of the hadronic form factors for the semileptonic decays B→π and B(s)→D(s)ℓν, computed using the highly improved staggered quark action for both valence and sea quarks on the MILC collaboration’s 2+1+1-flavor ensembles with lattice spacings ranging from 0.09fm to 0.03fm, many with physical pion masses. On our finest ensembles, we compute the form factors directly at the physical b-quark mass. We discuss the computational setup and analysis strategies for two- and three-point correlation functions. For B(s)→D(s), we present preliminary results of chiral-continuum fits for the scalar and vector form factors. The goal of this project is a percent-level determination of the scalar and vector form factors to enable high-precision determinations of |Vub| and|Vcb|. This work fits into a broader program of lattice-QCD studies of weak B-meson decays by the MILC and Fermilab Lattice collaborations. 

We present the status of calculations of the form factors of the most relevant heavy-to-heavy and heavy-to-light decay channels. Using seven Nf=2+1+1 HISQ ensembles, with lattice spacings ranging from 0.15 fm down to 0.06 fm, we calculate the form factors of the decays, including correlations among them. More than half of our ensembles feature physical pion masses, and the heavy quarks are simulated at their physical masses using the Wilson-clover action with the Fermilab interpretation. Even though we have recently seen huge qualitative and quantitative leaps in the characterization of heavy-to-heavy decays, these advances have failed to translate into improvements for the inclusive vs exclusive question, or the matter of the Lepton Flavor Universality ratios. In particular, in the B→D∗ℓν channel, the current situation of the lattice-QCD form factors is far from clear. Further, the latest lattice-QCD results on the heavy-to-light form factors display unexplained tensions that must urgently be resolved. The work presented here is an attempt to address these issues. 

One of the goals of undergraduate education is to prepare students to adapt to a challenging career that requires continual learning and application of knowledge. Working professionals should have deep conceptual knowledge that they can apply in a range of contexts and possess the attitudes and skills of lifelong learners. The literature suggests the concept of Adaptive Expertise (AE), which can be defined as the ability to apply and extend knowledge and skills to new situations, describes some of these characteristics. Survey data concerning the level of AE displayed by various populations is extremely limited in most contexts, be it education or working professionals. As such, data concerning the level of adaptiveness displayed among various groups needs to be measured if activities designed to promote the development of AE are to be created and then tested in terms of their efficacy. This investigation provides this critical baseline data for future studies as we track the AE development of individual, first-year college students through their undergraduate program of study, with a focus on low-income students as a means to support retention. In this work, we assessed adaptive expertise among low-income STEM students using surveys and interviews. Low-income STEM students from various stages of their four year undergraduate program (n=208) completed an adaptive expertise survey in spring 2022. Following the survey, 24 of the low-income students (6 per year, 3 male, 3 female) were selected for targeted qualitative interviews to better understand the differences displayed by low and high AE students. Survey results from prior studies were used to draw comparisons between adaptiveness of low-income and non-low-income students. Results of the AE survey indicated no statistically-significant differences between low-income and non-low-income first-year students in terms of their level of adaptiveness. In addition, the level of AE displayed by low-income students increased through the program in a manner similar to that of non-low-income STEM students. Themes that emerged from the interviews included a general understanding of the importance and likelihood of learning new concepts continually while working in a professional role, and that students expressed growth in understanding the acceptance of reaching out for assistance from other students and faculty after exploring information on their own as they work through challenges in their academic assignments. Two dominant and divergent metacognitive processes were also observed: teaching/explaining concepts to others (highly adaptive) or primarily relying on exam/course grades for feedback on learning (low adaptiveness). Data gathered from interviews demonstrate the need for a greater emphasis on metacognitive practice to promote various aspects of AE. 

Engineering programs must weave coverage of disciplinary content with the ability of students to apply and extend this content knowledge to new contexts and for use in their professional practice as engineers. It is, therefore, necessary for schools to promote and cultivate additional dispositions within their students that better enable them to adapt and employ their disciplinary knowledge. The concept of an “adaptive expert” (AE) has been previously developed within the learning sciences to describe an individual with deep content knowledge but who also displays additional cognitive characteristics that better enable them to employ their knowledge and skills in practice. Four constructs have been identified in the literature as forming the basis of this adaptive expertise: 1) multiple perspectives (MP), 2) metacognition (META), 3) goals and beliefs (GB), and 4) epistemology (EPIST). Upon entry to an engineering program, it is likely that students will present with different levels of development and awareness within these particular dimensions. Baseline levels must, therefore, be measured in order to assess these levels of development and before research-based practices and activities can be designed to promote growth in these constructs. In this work-in-progress study, the “adaptiveness” of incoming undergraduate STEM students (n=711) is measured using a previously developed validated survey instrument used in other studies to measure levels of adaptive expertise amongst undergraduate students by determining their levels along the four identified dimensions of AE. Based on this survey data, statistically significant differences were found in the AE constructs for men and women, with women outscoring men in three of the four AE subscales (MP, META, EPIST) and men outscoring women in goals and beliefs (GB). White students were found to score statistically higher than Asian students in both multiple perspectives (MP) and goals and beliefs (GB), while no statistically significant differences were observed when White and Black/African American students were compared. The mean epistemology (EPIST) scores for White, non-Hispanic students was statistically higher than Hispanic students, with low-income students scoring lower than non-low-income students on this subscale. This project seeks to provide baseline data concerning the adaptivity of incoming first-year students. A structured mentoring program focusing on elements of AE will then be implemented and student growth in the dimensions of AE assessed through their program of study.