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The student development initiatives of the BUILDing SCHOLARS Center at The University of Texas at El Paso comprise a program intended to prepare undergraduate students to enter and succeed in advanced graduate and professional biomedical degree programs, ultimately contributing to the diversity of the biomedical research workforce. The program adopted the Johnson/Bozemann Asset Bundles model, which recommends addressing five areas necessary to support minority students as they prepare for and continue towards scientific careers: a) educational endowments, b) science socialization, c) network development, d) family expectations and e) material resources. Through a variety of activities, which included a minimum of two years of research training, all five asset bundles were integrated into the program. Validated scales on science identity and research self-efficacy were completed by program fellows, and academic metrics such as retention, grade point average (GPA), and time to degree were collected for both program fellows and a comparison group. Thorough records of all students who participated in the program, including their presentations and co-authored publications, have been maintained, and students are being tracked post-graduation to determine their entry and completion of advanced degrees. Academic-based results for the first three cohorts of program participants show large, significant, and positive differences in retention, 4-year graduation rates and entry into advanced degrees between program participants and the comparison group. Comparison of academic and non-academic metrics indicate that the asset bundles approach is effective in retaining and preparing students for advanced degrees and careers in STEM disciplines. Using our results in combination with research by others on retention of students in STEM, we suggest factors contributing to the push-out of very talented majority Hispanic students in the comparison group from completing STEM degrees or not pursuing advanced studies in STEM areas. [ABSTRACT FROM AUTHOR]

Summer undergraduate research experience (SURE) programs are proven interventions that provide undergraduate students with opportunities to develop research skills under the mentorship of a faculty member. These are essential programs, particularly for members of underrepresented minorities, because SUREs are known to broaden their participation and increase retention. We present the results of a study investigating the influence of faculty mentorship quality on the quality of research presentations for undergraduate students attending a 10-week, distributed, multi-institutional SURE program focused on biomedical research training. Upon returning to the home institution, students presented research posters at a local symposium. Poster presentations were judged using a scale validated as part of this project. Combining collected information on student demographics and their self-reported assessments of research gains and belonging to the scientific community, we made use of data analytics methodologies to appropriately merge and analyze the data to address the overarching research question: What are the independent and combined effects of the quality of faculty mentorship and student characteristics on the quality of SURE student poster presentations? Results show that faculty mentor quality functions as a moderating influence for student characteristics on research presentation quality. Implications and recommendations for SURE program implementation are discussed.

Course-based undergraduate research experiences (CUREs) serve to increase student access to authentic scientific opportunities. Current evidence within the literature indicates that engagement in CUREs promotes students' science identity development, science self-efficacy, motivation, and ability to "think like a scientist." Despite the importance of these findings, few studies have examined the behaviors and interactions occurring within CURE and non-CURE settings and the impact of those behaviors on said student outcomes. To address these concerns, we conducted a mixed-methods study to explore student and instructor behaviors in four CURE and four non-CURE introductory biology laboratory sections. Representative video data were collected in each section and coded using the Laboratory Observation Protocol for Undergraduate STEM. In addition, pre/postsemester affective survey data were obtained from CURE and non-CURE participants. Results indicated that CURE students and instructors engaged in more interactive behaviors (e.g., one-on-one dialogue, questioning) than their non-CURE counterparts, a finding confirmed by analyzing behavioral patterns via construction of partial correlation networks. Multiple regression analyses further revealed that both student and instructor interactive behaviors and enrollment in a CURE were strong predictors of pre/postsemester shifts in student motivation, science identity development, collaboration, and perceived opportunities to make relevant scientific discoveries.

A large-scale (n = 1323) survey of mnemonic recall, self-reported familiarity, cued explanation, and application by introductory statistics students was conducted at a large research university in the southeastern United States. The students were presented 14 mnemonics during the fall 2017 term. Different nonoverlapping cohorts of students were asked at different time points to complete a survey about mnemonic use. At each time point, the students were asked to recall any mnemonic that they remembered, explain the mnemonic when cued, self-report their degree of familiarity, and apply the mnemonic. Of the 14 mnemonics, acronym-type mnemonics were recalled more frequently, but longer phrase-type mnemonics were explained and applied more often. These findings suggest that instructors should provide scaffolding to move a student from recalling a mnemonic to using a mnemonic toward successful completion of the statistics problem at hand. [ABSTRACT FROM AUTHOR]

C-C Chemokine Receptor 7 (CCR7) mediates T-cell acute lymphoblastic leukemia (T-ALL) invasion of the central nervous system (CNS) mediated by chemotactic migration to C-C chemokine ligand 19 (CCL19). To determine if a CCL19 antagonist, CCL198-83, could inhibit CCR7-induced chemotaxis and signaling via CCL19 but not CCL21, we used transwell migration and Ca2+ mobilization signaling assays. We found that in response to CCL19, human T-ALL cells employ β2 integrins to invade human brain microvascular endothelial cell monolayers. In vivo, using an inducible mouse model of T-ALL, we found that we were able to increase the survival of the mice treated with CCL198-83 when compared to non-treated controls. Overall, our results describe a targetable cell surface receptor, CCR7, which can be inhibited to prevent β2-integrin-mediated T-ALL invasion of the CNS and potentially provides a platform for the pharmacological inhibition of T-ALL cell entry into the CNS. [ABSTRACT FROM AUTHOR]

The interaction between language and the learning of statistical concepts has been receiving increased attention. The Communication, Language, And Statistics Survey (CLASS) was developed in response to the need to focus on dynamics of language in light of the culturally and linguistically diverse environments of introductory statistics classrooms. This manuscript presents a cross-cultural evaluation of the characteristics of the CLASS III (third generation of the instrument) and provides a user-friendly cross-culturally valid version of the CLASS. Mixed methods are employed to investigate further characteristics of the CLASS III and provide a scale (CLASS IV) that may be utilized in diverse settings. These research results have implications for instructors, professional developers, and researchers to improve instruction with culturally and linguistically diverse student populations.

English language learners are a growing demographic in secondary, two-year, four-year and research institutions where many students encounter their first course in statistics. In the statistics education literature, recent calls have been made to improve statistical education for underserved student populations, including English Language Learners (ELLs). Some have investigated how ELLs interpret instructional material and classroom practices in the statistics classroom. This study uses a sequential mixed methods approach to investigate how Spanish-speaking ELLs may respond differently to assessment items about measures of center and variation. Comprehensive analyses of this type are essential in order to identify bias and ensure fair comparisons across participant populations. Findings indicate that ELLs do not comprehend context or understand some statistical terms in the same way as non-ELLs. Study limitations, implications, and recommendations are discussed.

Mnemonics (memory aids) are often viewed as useful in helping students recall information, and thereby possibly reducing stress and freeing up more cognitive resources for higher-order thinking. However, there has been little research on statistics mnemonics, especially for large classes. This article reports on the results of a study conducted during two consecutive fall semesters at a large U.S. university. In 2014, a large sample (n = 1,487) of college students were asked about the usefulness of a set of 19 published statistics mnemonics presented in class, and in 2015, the students (n = 1,468) were presented 12 mnemonics related to inference and then asked whether or not they used mnemonics on that exam. This article discusses how students assess the usefulness of mnemonics and evaluates the relationship between using mnemonics and reducing anxiety. Additionally, the relationship between mnemonic usage and learning outcomes achievement will be discussed, along with this study's limitations and implications for teaching.

English language learners (ELLs) are a rapidly growing part of the student population in many countries. Studies on resources for language learners--especially Spanish-speaking ELLs--have focused on areas such as reading, writing, and mathematics, but not introductory probability and statistics. Semi-structured qualitative interviews investigated how a purposeful sample of six (Spanish-speaking) ELLs experienced a bilingual coin-flipping simulation applet (NLVM, 2015) and how students might use such resource to confront content misconceptions and language misunderstandings related to probability concepts covered in college introductory statistics courses. We discuss findings, limitations, directions for future research, and implications for teaching, such as handling the phrases "in the long run" and "longest run".

A corpus of current editions of statistics textbooks was assessed to compare aspects and levels of readability for the topics of "measures of center," "line of fit," "regression analysis," and "regression inference." Analysis with lexical software of these text selections revealed that the large corpus can be described well by three index variables that summarize the lexical and grammatical complexity of the textbook excerpts. Assessment of those three variables indicates that substantial differences exist in the readability of the topics within textbooks with respect to lexical and grammatical complexity. This analysis suggests that general readability of introductory statistics topics within textbooks varies substantially and it is a recommendation that instructors: (1) be prepared to provide additional support for topics that are more grammatically and lexically complex, and (2) be aware that they can input their instructional materials into LexTutor VP or Coh-metrix as a quick screen for possible readability issues.

Generalized linear mixed models are frequently applied to data with clustered categorical outcomes. The effect of clustering on the response is often difficult to practically assess partly because it is reported on a scale on which comparisons with regression parameters are difficult to make. This article proposes confidence intervals for estimating the heterogeneity due to clustering on a scale that is easy to interpret. The performance of the proposed asymptotic intervals and percentile bootstrap intervals are compared by simulations and in an application.

The framework of linguistic register and case study research on Spanish-speaking English language learners (ELLs) learning statistics informed the construction of a quantitative instrument, the Communication, Language, And Statistics Survey (CLASS). CLASS aims to assess whether ELLs and non-ELLs approach the learning of statistics differently with respect to the distinctive linguistic features of the field of statistics and with respect to language resources they bring to the class. The CLASS was administered to all (n = 137) students in an introductory statistics literacy course at a university with a majority Mexican-American student body. Findings suggest ELLs often have distinctive patterns in how they experience aspects of statistics instruction (e.g., wait time) as well as movement between mathematics/statistics and everyday registers. (Contains 5 tables.)

Research training is an important intervention for preparing undergraduate students to pursue further studies and develop research skills. Furthermore, there is mounting evidence indicating that mentored research impacts student success metrics. At the University of Texas at El Paso, a Freshman Year Research Intensive Sequence (FYRIS) was developed to prepare first-year students for research experiences. The FYRIS courses combine research foundations and research-intensive courses. In this manuscript, we present findings demonstrating the impact of FYRIS and subsequent mentored research experiences on 4-year retention and graduation. Results suggest that participation in FYRIS and independent mentored research has a large positive impact on 4-year retention and graduation, while other historical socioeconomic variables have minimal to no impact.

One of the key challenges many peer-to-peer mentoring programs face is the lack of high-quality mentor training. In order to address this issue, the BUILDing SCHOLARS (BUILD) program at The University of Texas at El Paso (UTEP) implements a structured peer mentor training and provides the training to BUILD fellows at UTEP for four academic years. This paper focuses on introducing the BUILD Peer Mentor Training (BPMT) model and investigates its impacts on students using program evaluation data. Our results reveal that BUILD peer mentors were satisfied with the BPMT and their relationships with the mentees. They also reported that the training greatly improved their problem solving and action planning skills, and slightly improved their communication skills and ability to assess a mentee's understanding. Finally, four practical recommendations are provided for institutions and programs that might be interested in implementing a similar peer mentor training.