Instructor Talk—noncontent language used by instructors in classrooms—is a recently defined and promising variable for better understanding classroom dynamics. Having previously characterized the Instructor Talk framework within the context of a single course, we present here our results surrounding the applicability of the Instructor Talk framework to noncontent language used by instructors in novel course contexts. We analyzed Instructor Talk in eight additional biology courses in their entirety and in 61 biology courses using an emergent sampling strategy. We observed widespread use of Instructor Talk with variation in the amount and category type used. The vast majority of Instructor Talk could be characterized using the originally published Instructor Talk framework, suggesting the robustness of this framework. Additionally, a new form of Instructor Talk—Negatively Phrased Instructor Talk, language that may discourage students or distract from the learning process—was detected in these novel course contexts. Finally, the emergent sampling strategy described here may allow investigation of Instructor Talk in even larger numbers of courses across institutions and disciplines. Given its widespread use, potential influence on students in learning environments, and ability to be sampled, Instructor Talk may be a key variable to consider in future research on teaching and learning in higher education.

Active-learning pedagogies have been repeatedly demonstrated to produce superior learning gains with large effect sizes compared with lecture-based pedagogies. Shifting large numbers of college science, technology, engineering, and mathematics (STEM) faculty to include any active learning in their teaching may retain and more effectively educate far more students than having a few faculty completely transform their teaching, but the extent to which STEM faculty are changing their teaching methods is unclear. Here, we describe the development and application of the machine-learning-derived algorithm Decibel Analysis for Research in Teaching (DART), which can analyze thousands of hours of STEM course audio recordings quickly, with minimal costs, and without need for human observers. DART analyzes the volume and variance of classroom recordings to predict the quantity of time spent on single voice (e.g., lecture), multiple voice (e.g., pair discussion), and no voice (e.g., clicker question thinking) activities. Applying DART to 1,486 recordings of class sessions from 67 courses, a total of 1,720 h of audio, revealed varied patterns of lecture (single voice) and nonlecture activity (multiple and no voice) use. We also found that there was significantly more use of multiple and no voice strategies in courses for STEM majors compared with courses for non-STEM majors, indicating that DART can be used to compare teaching strategies in different types of courses. Therefore, DART has the potential to systematically inventory the presence of active learning with ∼90% accuracy across thousands of courses in diverse settings with minimal effort.active learning | evidence-based teaching | science education | lecture | assessment C urrent college STEM (science, technology, engineering, and mathematics) teaching in the United States continues to be lecture-based and is relatively ineffective in promoting learning (1, 2). Undergraduate instructors continue to struggle to engage, effectively teach, and retain postsecondary students, both generally and particularly among women and students of color (3, 4). Federal analyses suggest that a 10% increase in retention of undergraduate STEM students could address anticipated STEM workforce shortfalls (5). Replacing the standard lecture format with more active teaching strategies has been shown to increase

The arrival of a new species of the fungus which causes Dutch elm disease into Great Britain in the 1960s caused widespread elm death and continues to be problematic following elm regeneration. Attempts at managing the disease have been largely unsuccessful. Forty years after the outbreak, however, researchers continue to be interested in both the underlying biology of such a severe and dramatic disease event and in the policy lessons that can be drawn from it. We develop a spatial model at a 1 km 2 resolution. Following parameterization to replay the historical epidemic, the model is used to explore previously proposed counterfactual management strategies. A new introduction date of late 1962 is estimated. We show that, even had there been high intervention at a national level in terms of disease management early in the epidemic, there would have been little long-term effect on elm numbers. In Brighton, a local pocket of elm which survived the peak of the initial epidemic has been successfully managed. However, Brighton and similar locations are subject to repeated waves of the disease at a 15-to 20-year intervals following regeneration and reinfection of the surrounding areas, during which much more intensive management is required.Keywords: epidemiology, Ophiostoma novo-ulmi, spatial modelling, Ulmus IntroductionThroughout the 1970s an epidemic of a newly introduced Dutch elm disease fungus swept through Britain, killing the majority of mature elm trees (Gibbs, 1978a;Jones, 1981). The epidemic was caused by the scolytid bark beetle-borne fungus Ophiostoma novo-ulmi Brasier & Kirk, 2001), a new species which had not been identified at the time of introduction. This fungus had been causing widespread elm death in North America, in conjunction with the original Dutch elm disease fungus O. ulmi, which had been introduced from Europe (Gibbs, 1978b). In North America, the native elm species were very susceptible to both pathogens, and a distinction had not been made between them, although a change of disease intensity was identified (Pomerleau, 1961).In Europe, the original fungus had been causing elm death since at least the 1920s, when it was first identified. In Britain, the official line (Peace, 1960) was that the disease did not justify significant government intervention since a degree of recovery could be expected, and epidemic flareups were localized (provided that the disease did not change its character). Following the introduction of the new fungus on infected timber from Canada , there was a resurgence of the disease. In a recent analysis of the science and policy of the epidemic, Tomlinson & Potter (2010) record how the received wisdom of Peace, widely disseminated and largely accepted within plant pathology circles, had the effect of delaying a response, as the resurgence was understandably perceived as a local flareup of O. ulmi. Hindsight suggests that the potential existed for the new fungal species to be identified outside Britain, and that management could have been better coordinated and managed...

The importance of quantifying existing ecosystem services, assessing the impacts of various land use decisions and ultimately evaluating the overall costs and benefits of different land use patterns having internalized ecosystem services, is now widely recognized and such work is at the forefront of current landscape management planning. We aim to quantify ecosystem services derived from different land uses within the Atibainha Reservoir catchment in Brazil, determine the spatial distribution of ecosystem services and quantify the impacts of land use changes on the provision of ecosystem services. Four ecosystem services were considered: carbon sequestration, mitigation of sediment delivery into the reservoir, purification of water and maintenance of soil fertility. Results indicate strong increase in the provision of ecosystem services among the main land uses in the following order: urban area/bare soil; pastures; plantation of eucalyptus and native forests. The most important services provided by native forests, when compared with bare soil, were carbon sequestration and prevention of sedimentation, with an additional 864 569 tons of carbon stored in forest biomass in 30 years, and prevention of 244 511 tons of sediment delivery into the reservoir per year, respectively, from 7624 ha of lands around the reservoir. Spatial variation in the provision of ecosystem services were mapped to develop a tool to support decision making at the landscape scale. Results and maps from the decision support tool can support policies that ensure effective land-use planning and can serve as the basis for the development of payment for ecosystem service schemes in the region.

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