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Recently, the Interactive-Constructive-Active-Passive (ICAP) framework has been gaining increasing prominence in cognitive and learning sciences. The ICAP theory asserts that students learn more deeply when they are cognitively engaged in generative and collaborative learning. Indeed, prior studies have established the value of the ICAP framework for predicting student learning. However, the framework has yet to become widely used by practitioners, possibly due to the lack of accessible resources for applying the framework instruction design. This study sought to fill that gap by implementing and validating the ICAP instructional rubric instrument to rate the design of college chemistry courses at a large public university in the southwest and exploring its relationships with several metrics of student performance via multiple regression analysis: a) level of participation; b) final exam grades; c) course grades; d) course retention; and e) course attrition. This study analyzed data from the university’s learning management system and included student-level controls such as markers of prior academic performance (i.e., GPA and SAT scores) as well as student demographics. The findings of this study suggest that the ICAP framework may be a useful tool for instructors to improve course design. In addition, the ICAP framework’s predictive claims on student deeper learning were further validated by the results of this study.

This study explores the feasibility of forming detailed inferences about museum visitor behavior based on analysis of data collected via Dr. Discovery—a mobile question-and-answer app. We analyzed 5656 questions asked by 795 visitor groups recorded by Dr. Discovery across two museums in the American Southwest. Analysis of this data supported the act of intuiting visitor movement through museum exhibit halls without the use of costly tracking or location technology by leveraging question keyword content, knowledge of exhibit hall layout, and question timestamp information. Additionally, data on question topic frequency enabled us to infer visitor engagement levels with specific exhibit hall content. We conclude that analysis of seemingly limited app-based data carries implications for the practice of museum evaluation since evaluators can gain evidence-based insight into visitor behaviors as well as illustrate helpful and promising technology-supported alternatives for conducting affordable, dependable, and scalable evaluations.

Question-asking is essential for reasoning, understanding, and investigating scientific problems within and beyond traditional classrooms. Nevertheless, questions generated in formal and informal learning environments can be infrequent and unsophisticated. This study explores museum visitors’ question-asking quality by considering their interactions with two different modes of a question-asking mobile app (Ask or Game Mode) in two different museum environments (linear non-interactive or non-linear interactive exhibits). Results showed that visitors’ question-asking quality was influenced by app modes and by museum environments. Specifically, we found that visitors’ question-asking quality was significantly higher when using the gamified version of the app (Game Mode) compared to a non-gamified version (Ask Mode) in a linear non-interactive exhibit. Findings also revealed that question-asking performance could be significantly influenced by instrumental factors (such as app performance in answering questions) and socio-contextual factors (such as visitor group inquiry frequency). The study provides fundamental and comprehensive insights for designing active learning environments by considering the influential factors of question-asking.

This study examines the impact of a mobile game app on science museum visitors’ level of engagement with exhibit content, compared to a non game-based version of the same app. Ask Dr. Discovery (Dr. D) is a question-asking app containing two versions: a Game Mode employing casual game mechanics and an Ask Mode providing a baseline version. We implemented both versions of Dr. D at two science museums located in the Southwestern United States with 1539 participants. In both conditions, participants could type or speak questions to receive vetted answers about museum content, but only Game Mode embedded question-asking within a simple game. Participants’ level of engagement was represented by the number of questions asked about exhibit content in Dr. D. Additionally, we explored the relationship between app engagement and participants’ self-reported level of interest in science. All participants completed pre- and post-questionnaires with questions related to science interest, impressions of the Dr. D app, and demographic information. Results in both museums indicated that users of Game Mode asked nearly twice as many questions on average as participants using Ask Mode. Science interest predicted engagement at one of two sites. Demographic variables, including gender, age, and race/ethnicity were not found to influence the rate of question asking in either mode. These results indicate that employing simple game mechanics in apps for museum visitors may lead to strong positive impacts on visitor engagement with museum content.

Mobile devices and apps have become a standard for the museum experience. Many studies have begun to explore the impact mobile apps may have on user experience and informal learning. However, there has been relatively little research on how visitor groups interact collaboratively while using these devices in computer-supported collaborative learning (CSCL) environments. In this paper, we explore the impact of a mobile question-asking app on museum visitor group interactions using the Interactive-Constructive-Active–Passive (ICAP) framework, a hierarchical taxonomy that differentiates modes of cognitive engagement. In a post-hoc analysis of survey findings from a study conducted at two large museums in the American southwest, we found that our app encouraged sharing of information among group members. In addition, users of a gamified version of the app were significantly more likely to report engaging in a group discussion during question-asking than groups using a non-game version of the app. We also found that group collaboration levels depended on the group-designated primary user of the app. Whenever a child or the group collaboratively asked the most questions, group discussion frequency was significantly higher. The study’s findings support mobile question-asking apps’ viability as a means to better understanding of museum visitor groups’ interactions with exhibit content and provide evidence that game-based mobile apps, designed to foster question-asking by visitors, may bolster collaborative group interactions and informal learning.

Dodd, in turn, points to a string of alarms he says he sounded as the housing market melted down -- speeches and letters to federal regulators urging an end to predatory lending practices and relief for homeowners facing foreclosure.

The human genome contains thousands of long non-coding RNAs 1 , but specific biological functions and biochemical mechanisms have been discovered for only about a dozen 2 – 7 . A specific long non-coding RNA—non-coding RNA activated by DNA damage ( NORAD )—has recently been shown to be required for maintaining genomic stability 8 , but its molecular mechanism is unknown. Here we combine RNA antisense purification and quantitative mass spectrometry to identify proteins that directly interact with NORAD in living cells. We show that NORAD interacts with proteins involved in DNA replication and repair in steady-state cells and localizes to the nucleus upon stimulation with replication stress or DNA damage. In particular, NORAD interacts with RBMX, a component of the DNA-damage response, and contains the strongest RBMX-binding site in the transcriptome. We demonstrate that NORAD controls the ability of RBMX to assemble a ribonucleoprotein complex—which we term NORAD -activated ribonucleoprotein complex 1 (NARC1)—that contains the known suppressors of genomic instability topoisomerase I (TOP1), ALYREF and the PRPF19–CDC5L complex. Cells depleted for NORAD or RBMX display an increased frequency of chromosome segregation defects, reduced replication-fork velocity and altered cell-cycle progression—which represent phenotypes that are mechanistically linked to TOP1 and PRPF19–CDC5L function. Expression of NORAD in trans can rescue defects caused by NORAD depletion, but rescue is significantly impaired when the RBMX-binding site in NORAD is deleted. Our results demonstrate that the interaction between NORAD and RBMX is important for NORAD function, and that NORAD is required for the assembly of the previously unknown topoisomerase complex NARC1, which contributes to maintaining genomic stability. In addition, we uncover a previously unknown function for long non-coding RNAs in modulating the ability of an RNA-binding protein to assemble a higher-order ribonucleoprotein complex. The long non-coding RNA NORAD interacts with proteins involved in DNA replication and repair, and controls the ability of RBMX to form a ribonucleoprotein complex that helps to maintain genomic stability.

This large-scale analysis of copy number alterations (CNAs) in patient-derived xenografts (PDXs) across 24 cancer types shows that new CNAs accumulate quickly and that the specific CNAs acquired during passaging differ from those acquired during tumor evolution in patients, suggesting that PDX tumors are under distinct selection pressures from tumors in human hosts. Patient-derived xenografts (PDXs) have become a prominent cancer model system, as they are presumed to faithfully represent the genomic features of primary tumors. Here we monitored the dynamics of copy number alterations (CNAs) in 1,110 PDX samples across 24 cancer types. We observed rapid accumulation of CNAs during PDX passaging, often due to selection of preexisting minor clones. CNA acquisition in PDXs was correlated with the tissue-specific levels of aneuploidy and genetic heterogeneity observed in primary tumors. However, the particular CNAs acquired during PDX passaging differed from those acquired during tumor evolution in patients. Several CNAs recurrently observed in primary tumors gradually disappeared in PDXs, indicating that events undergoing positive selection in humans can become dispensable during propagation in mice. Notably, the genomic stability of PDXs was associated with their response to chemotherapy and targeted drugs. These findings have major implications for PDX-based modeling of human cancer.

Direct oral anticoagulants (DOACs) exert anticoagulation effect by directly inhibiting Factor Xa (rivaroxaban, apixaban, and edoxaban) or thrombin (dabigatran). Though DOACs are characterized by fixed-dose prescribing and generally do not require routine laboratory drug-level monitoring (DLM), circumstances may arise where the DLM may aid in clinical decision-making, including DOAC dose adjustment, anticoagulant class change, or decisions to withhold or administer reversal agents. We review the current literature that describes high-risk patient groups in which DLM may be beneficial for improved patient anticoagulation management and stewardship. The review also summarizes the limitations of conventional coagulation testing and discuss the emerging utility of quantitative methods for routine and rapid emergent evaluation of DOAC drug levels—in particular, the Anti-Xa activity to detect Factor Xa Inhibitors (rivaroxaban, apixaban, and edoxaban). Both technical and regulatory barriers to widespread DLM implementation are limiting factors to further clinical research that must be overcome, in order to propose universal DOAC DLM strategies and provide clinical-laboratory correlation to formally classify high-risk patient groups.