Using the Depth of Knowledge Model to Create High School Mathematics Assessments--RESEARCH

This study examined the midterm exams of six high school math teachers and sought to (a) determine if teachers could accurately identify which level of Norman Webb’s Depth of Knowledge (DOK) model their test items aligned to, and (b) compare the actual percentage of test items at each DOK level to the targeted percentage based off Webb’s research. The study revealed that teachers were not accurate with their alignment of test items with Webb’s DOK model. They also came up short in comparison to the targeted percentages of test items at each level. Comprehensively, they were asking more questions at Level 1 and 2 instead of at Level 3 or 4. Recommendations are provided on how teachers can write questions at the targeted level for their course. Advancing high school students’ depth of knowledge (DOK) in mathematics can be challenging, so it is important for assessments to meet the appropriate levels of DOK. Finally, assessing the DOK levels of created test items is a task that can be difficult for most high school teachers. These challenges were the backdrop of this study

Robotic right ventricle is a biohybrid platform that simulates right ventricular function in (patho)physiological conditions and intervention

The increasing recognition of the right ventricle (RV) necessitates the development of RV-focused interventions, devices and testbeds. In this study, we developed a soft robotic model of the right heart that accurately mimics RV biomechanics and hemodynamics, including free wall, septal and valve motion. This model uses a biohybrid approach, combining a chemically treated endocardial scaffold with a soft robotic synthetic myocardium. When connected to a circulatory flow loop, the robotic right ventricle (RRV) replicates real-time hemodynamic changes in healthy and pathological conditions, including volume overload, RV systolic failure and pressure overload. The RRV also mimics clinical markers of RV dysfunction and is validated using an in vivo porcine model. Additionally, the RRV recreates chordae tension, simulating papillary muscle motion, and shows the potential for tricuspid valve repair and replacement in vitro. This work aims to provide a platform for developing tools for research and treatment for RV pathophysiology.</p

A Tunable Soft Silicone Bioadhesive for Secure Anchoring of Diverse Medical Devices to Wet Biological Tissue

Silicone is utilized widely in medical devices for its compatibility with tissues and bodily fluids, making it a versatile material for implants and wearables. To effectively bond silicone devices to biological tissues, a reliable adhesive is required to create a strong and long‐lasting interface. This study introduces BioAdheSil, a silicone‐based bioadhesive designed to provide robust adhesion on both sides of the interface, facilitating bonding between dissimilar substrates, namely silicone devices and tissues. The adhesive's design focuses on two key aspects: wet tissue adhesion capability and tissue‐infiltration‐based long‐term integration. BioAdheSil is formulated by mixing soft silicone oligomers with siloxane coupling agents and absorbents for bonding the hydrophobic silicone device to hydrophilic biological tissues. Incorporation of biodegradable absorbents eliminates surface water and controls porosity, while silane crosslinkers provide interfacial strength. Over time, BioAdheSil transitions from non‐permeable to permeable through enzyme degradation, creating a porous structure that facilitates cell migration and tissue integration, potentially enabling long‐lasting adhesion. Experimental results demonstrate that BioAdheSil outperforms commercial adhesives and elicits no adverse response in rats. BioAdheSil offers practical utility for adhering silicone devices to wet tissues, including long‐term implants and transcutaneous devices. In this study, we demonstrate its functionality through applications such as tracheal stents and LVAD (Left Ventricular Assist Device) lines