Texas Wesleyan University

Background and Purpose: Graduate nursing programs require structured processes to address clinical deficiencies while ensuring fairness and patient safety. However, existing remediation practices often lack standardization and transparency. To address this gap, a clinical remediation algorithm was developed and evaluated to assist in managing unsatisfactory clinical performance. Methods: The 26-item Graduate Nursing Student Clinical Remediation (GNS-CR) Algorithm, developed from literature and expert feedback, was reviewed by 20 invited experts in graduate nursing education. Content validity indices (CVI) were calculated at the item and scale level. Results: Item-level CVI scores ranged from .80 to 1.00, with a scale-level CVI of .923, surpassing accepted thresholds. Feedback confirmed the algorithm's clarity, logical structure, and relevance. Conclusions: The GNS-CR Algorithm demonstrated strong content validity and offers a systematic, transparent approach to clinical remediation. Future research should evaluate its effectiveness in academic and clinical settings.

ABSTRACT The case study provides students with hands-on experience performing and using data analytics as a risk assessment procedure. Students play the role of a newly hired accounting graduate who is presented with a large file of vendor invoice data and requested to use data analytics to assess the fraud risk associated with the vendor. This case study requires significant critical-thinking skills as students engage in a complex task involving ambiguity, and it simulates a real-world scenario in which students must determine which analyses are most helpful and can be performed based on the available data. The case learning objectives are (1) identify and recommend internal controls over the purchases and cash disbursement processes, (2) use data analysis software to identify anomalies in vendor data and transactions, and (3) demonstrate effective written communication skills.

Supporting graduate nursing students from diverse backgrounds who work full-time in the clinical environment is important in increasing retention rates for advanced practice nurses. Onboarding programs designed to connect students to institutional resources have demonstrated benefits such as reducing anxiety, reducing attrition rates, and improving academic preparedness. This study used a convergent mixed-methods design to investigate the benefit of an onboarding program. In 2023, graduate students were enrolled in an onboarding course. At the end of the semester, students completed a survey measuring the benefits of the onboarding program and participated in virtual focus groups. A total of 194 graduate students were enrolled in the Student Success Corner. Sixty-seven students completed the online survey, and five students participated in four focus group interviews. The survey and interview findings were united in supporting the potential onboarding programs have for promoting the success of graduate students.

Technology advancements have led to changes in traditional, face-to-face work models by enabling organizations to conduct business virtually. The new virtual models of work generate two main concerns for organizations. First, such models may not allow knowledge to flow smoothly within organizations as it travels through geographical boundaries. Second, organizations may not be able to store their lived experiences, or memories, to support future organizational decisions. To address these concerns, this paper develops a framework for selecting the optimal media choice to be used by organizations to promote organizational learning, particularly organizational memory, in virtual work settings. The framework discusses different media capacities, and the ability to achieve synchronicity, retainability, and reach. It is further proposed two dyads that are likely to influence organizational memory the most. This paper also concludes with implications, limitations, and future research directions.

SummaryRoots are essential for plant adaptation to changing environments, yet the role of roots in crop domestication remains unclear. This study examined the evolution of root phenotypes from teosinte to maize, a transition resulting in reduced nodal root number (NRN), multiseriate cortical sclerenchyma (MCS), and increased seminal root number (SRN).We reconstructed the root phenotypes of maize and teosinte, as well as the environments of the Tehuacán Valley over the last 18 000 yr using a combination of ancient DNA, paleobotany, and functional‐structural modeling.Our models reveal that increasing Holocene atmospheric CO2 concentrations favored the appearance of reduced NRN and MCS between 12 000 and 8000 yr before present (yrBP), promoting deeper root systems. The advent of irrigation by 6000 yrBP switched nitrogen distribution from topsoil to subsoil domains, a change that increased the utility of reduced NRN and MCS. Comparison of allelic frequencies among ancient samples ranging from 5500 to 500 yrBP suggests that increased SRN may have appeared c. 3500 yrBP, coinciding with a period of increased human population, agricultural intensification, and soil degradation.Our results suggest that root phenotypes that enhance plant performance under nitrogen stress are important for maize adaptation to changing agricultural practices in the Tehuacán Valley.

SummaryRoots are essential for plant adaptation to changing environments, yet the role of roots in crop domestication remains unclear. This study examines the evolution of root phenotypes from teosinte to maize, a transition resulting in reduced nodal root number (NRN), multiseriate cortical sclerenchyma (MCS), and increased seminal root number (SRN). We reconstructed the root phenotypes of maize and teosinte, as well as the environments of the Tehuacan Valley over the last 18,000 years using a combination of ancient DNA, paleobotany, and functional-structural modeling. Our models reveal that increasing Holocene atmospheric CO2concentrations favored the appearance of reduced NRN and MCS between 12000 to 8000 years before present (yBP), promoting deeper root systems. The advent of irrigation by 6000 yBP switched nitrogen distribution from topsoil to subsoil domains, a change which increased the utility of reduced NRN and MCS. Comparison of allelic frequencies among ancient samples ranging from 5500 to 500 yBP suggest that increased SRN may have appeared around 3500 yBP, coinciding with a period of increased human population, agricultural intensification, and soil degradation. Our results suggest that root phenotypes that enhance plant performance under nitrogen stress were important for maize adaptation to changing agricultural practices in the Tehuacan Valley.ClassificationPhysiology & Development