Making Sense of Uncertainty in the Science Classroom: A Bayesian Approach.

Uncertainty is ubiquitous in science, but scientific knowledge is often represented to the public and in educational contexts as certain and immutable. This contrast can foster distrust when scientific knowledge develops in a way that people perceive as a reversals, as we have observed during the ongoing COVID-19 pandemic. Drawing on research in statistics, child development, and several studies in science education, we argue that a Bayesian approach can support science learners to make sense of uncertainty. We provide a brief primer on Bayes' theorem and then describe three ways to make Bayesian reasoning practical in K-12 science education contexts. There are a) using principles informed by Bayes' theorem that relate to the nature of knowing and knowledge, b) interacting with a web-based application (or widget-Confidence Updater) that makes the calculations needed to apply Bayes' theorem more practical, and c) adopting strategies for supporting even young learners to engage in Bayesian reasoning. We conclude with directions for future research and sum up how viewing science and scientific knowledge from a Bayesian perspective can build trust in science. Supplementary Information: The online version contains supplementary material available at 10.1007/s11191-022-00341-3.

Balancing' privacy and open science in the context of COVID-19: a response to Ifenthaler & Schumacher (2016).

Privacy and confidentiality are core considerations in education, while at the same time, using and sharing data-and, more broadly, open science-is increasingly valued by editors, funding agencies, and the public. This manuscript responds to an empirical investigation of students' perceptions of the use of their data in learning analytics systems by Ifentahler and Schumacher (Educational Technology Research and Development, 64: 923-938, 2016). We summarize their work in the context of the COVID-19 pandemic and the resulting shift to digital modes of teaching and learning by many teachers, using the tension between privacy and open science to frame our response. We offer informed recommendations for educational technology researchers in light of Ifentahler and Schumacher's findings as well as strategies for navigating the tension between these important values. We conclude with a call for educational technology scholars to meet the challenge of studying learning (and disruptions to learning) in light of COVID-19 while protecting the privacy of students in ways that go beyond what Institutional Review Boards consider to be within their purview.

Examining Relationships among Choice, Affect, and Engagement in Summer STEM Programs.

Out-of-school time programs focused on science, technology, engineering and mathematics (STEM) have proliferated recently because they are seen as having potential to appeal to youth and enhance STEM interest. Although such programs are not mandatory, youth are not always involved in making the choice about their participation and it is unclear whether youth's involvement in the choice to attend impacts their program experiences. Using data collected from experience sampling, traditional surveys, and video recordings, we explore relationships among youth's choice to attend out-of-school time programs (measured through a pre-survey) and their experience of affect (i.e., youth experience sampling ratings of happiness and excitement) and engagement (i.e., youth experience sampling ratings of concentration and effort) during program activities. Data were collected from a racially and ethnically diverse sample of 10-16 year old youth (n = 203; 50% female) enrolled in nine different summer STEM programs targeting underserved youth. Multilevel analysis indicated that choice and affect are independently and positively associated with momentary engagement. Though choice to enroll was a significant predictor of momentary engagement, positive affective experiences during the program may compensate for any decrements to engagement associated with lack of choice. Together, these findings have implications for researchers, parents, and educators and administrators of out-of-school time programming.

Development of a Community-Driven Mosquito Surveillance Program for Vectors of La Crosse Virus to Educate, Inform, and Empower a Community.

The fields of entomology, geospatial science, and science communication are understaffed in many areas, resulting in poor community awareness and heightened risks of vector-borne diseases. This is especially true in East Tennessee, where La Crosse encephalitis (LACE) causes pediatric illness each year. In response to these problems, we created a community engagement program that includes a yearlong academy for secondary STEM educators in the 6-12 grade classroom. The objectives of this program were to support inquiry-driven classroom learning to foster student interest in STEM fields, produce community-driven mosquito surveillance, and enhance community awareness of LACE. We trained educators in medical entomology, geospatial science, and science communication, and they incorporated those skills into lesson plans for a mosquito oviposition experiment that tested hypotheses developed in the classroom. Here, we share results from the first two years of the MEGA:BITESS academy, tailored for our community by having students ask questions directly related to Aedes mosquito oviposition biology and La Crosse encephalitis. In year one, we recruited 17 educators to participate in the project, and 15 of those educators returned in year two. All participating educators completed the academy, conducted the oviposition experiment, and informed over 400 students about a variety of careers and disciplines for their students. Here, we present a community-based program that helps to address the problems associated with long-term mosquito surveillance, health and science education and communication, career opportunities, and the community needs of Appalachia, as well as the initial data on the effectiveness of two years of an educator-targeted professional-development program.

Hypothetical case replacement can be used to quantify the robustness of trial results.

OBJECTIVES: We apply a general case replacement framework for quantifying the robustness of causal inferences to characterize the uncertainty of findings from clinical trials. STUDY DESIGN AND SETTING: We express the robustness of inferences as the amount of data that must be replaced to change the conclusion and relate this to the fragility of trial results used for dichotomous outcomes. We illustrate our approach in the context of an RCT of hydroxychloroquine on pneumonia in COVID-19 patients and a cumulative meta-analysis of the effect of antihypertensive treatments on stroke. RESULTS: We developed the Robustness of an Inference to Replacement (RIR), which quantifies how many treatment cases with positive outcomes would have to be replaced with hypothetical patients who did not receive a treatment to change an inference. The RIR addresses known limitations of the Fragility Index by accounting for the observed rates of outcomes. It can be used for varying thresholds for inference, including clinical importance. CONCLUSION: Because the RIR expresses uncertainty in terms of patient experiences, it is more relatable to stakeholders than P-values alone. It helps identify when results are statistically significant, but conclusions are not robust, while considering the rareness of events in the underlying data.

From genome to function: the Arabidopsis aquaporins.

BACKGROUND: In the post-genomic era newly sequenced genomes can be used to deduce organismal functions from our knowledge of other systems. Here we apply this approach to analyzing the aquaporin gene family in Arabidopsis thaliana. The aquaporins are intrinsic membrane proteins that have been characterized as facilitators of water flux. Originally termed major intrinsic proteins (MIPs), they are now also known as water channels, glycerol facilitators and aqua-glyceroporins, yet recent data suggest that they facilitate the movement of other low-molecular-weight metabolites as well. RESULTS: The Arabidopsis genome contains 38 sequences with homology to aquaporin in four subfamilies, termed PIP, TIP, NIP and SIP. We have analyzed aquaporin family structure and expression using the A. thaliana genome sequence, and introduce a new NMR approach for the purpose of analyzing water movement in plant roots in vivo. CONCLUSIONS: Our preliminary data indicate a strongly transcellular component for the flux of water in roots.