UNDERSTANDING THE DYNAMICS OF TEACHER ATTENTION: CASE STUDIES OF HOW HIGH SCHOOL PHYSICS AND PHYSICAL SCIENCE TEACHERS ATTEND TO STUDENT IDEAS

Attending to student ideas is critical for supporting students' science learning (Driver, Guesne, & Tiberghien, 1985; National Research Council, 1996). But, paying attention to student ideas in science class is difficult and does not happen often (Davis, 2001; Feldman, 2002; Levin, 2008; Levitt, 2001; Simmons, et al, 1999). Researchers have looked at how institutional expectations, curricular materials, and a teacher's cognition influence how that teacher picks up on and makes sense of student ideas (Ainley & Luntley, 2007; Levin, 2008; Rop, 2002; Tabak & Reiser, 1999; Wallach & Even, 2005). I argue that we do not yet have adequate ways of characterizing and understanding teachers' attention at the level of the interaction. I have evidence that suggests that when we look in such a fine-grained way, many of our current explanations for what teachers do and pay attention to are not sufficient. The aim of this dissertation is to build on the burgeoning body of work on teacher attention by looking at how to characterize a teacher's attention as that teacher interacts with students in the classroom and studying how a teacher's attention is situated in the teacher's framing of his or her interaction with students. In short, a person's frame or framing of the situation is his or her definition of what is going on in the interaction (Tannen, 1993). I discuss the implications for how we can support teachers' attention to student ideas and some areas for future research motivated by the findings of this study

Managing for Change: Achieving Systemic Reform Through the Effective Implementation of Networks for School Improvement

In August 2018, the Bill & Melinda Gates Foundation (“the foundation”) launched its Networks for School Improvement (NSIs) initiative. To further its own continuous learning as well as the learning of its grantees and the educational field, the foundation engaged the Center for Public Research and Leadership (CPRL) to conduct a formative evaluation of the NSIs initiative during its first two years. The research questions that guided this study were: How are network hubs implementing the Network for School Improvement (NSI) strategy? What are the characteristics of effective networks and network hubs? To answer these questions, CPRL used a qualitative research design to deeply explore the work of nine networks representative of the broader pool of grantees. Selection was designed to ensure diversity with respect to the following characteristics: (a) geographic location, (b) number of schools in the network, (c) number of districts in the network, (d) grade band targeted, and (e) problem of practice. The findings presented in this paper emerge from an analysis of data collected from these networks across two years. In total, CPRL conducted over 160 interviews, observed 22 network convenings, and analyzed nearly 1,000 artifacts and documents

Parasitic weed incidence and related economic losses in rice in Africa

Parasitic weeds pose increasing threats to rain-fed rice production in Africa. Most important species are Striga asiatica, S. aspera and S. hermonthica in rain-fed uplands, and Rhamphicarpa fistulosa in rain-fed lowlands. Information on the regional spread and economic importance of parasitic weeds in cereal production systems is scant. This article presents the first multi-species, multi-country, single-crop impact assessment of parasitic weeds in Africa. A systematic search of public international and national herbaria and the scientific literature was conducted to collect all available data on the regional distribution, incidences and related yield losses of the most important parasitic weeds in rice. Herbaria specimens were geo-referenced and these coordinates were overlapped with rain-fed rice areas. Probabilistic diffusion waves of parasitic weeds were generated to derive most likely incidence values. Estimates from this spatial analysis were then combined with secondary data from the literature into a stochastic impact assessment model to generate a confidence interval of the likely economic impact per country and for sub-Saharan Africa as a whole. Rhamphicarpa fistulosa occurs in at least 36 African countries, 28 of which produce rice in rain-fed lowlands where this species thrives. Striga hermonthica is found in at least 32 countries, Striga asiatica in at least 44 and S. aspera in at least 17. A total of 50 countries have at least one of these three species of Striga, 31 of which produce rice in the rain-fed uplands where these species can be encountered. An estimated 1.34 million ha of rain-fed rice is infested with at least one species of a parasitic weed in Africa. Our stochastic model estimates that annual economic losses inflicted by all parasitic weeds exceeds, with 95% certainty, a minimum value of US $111 million and most likely reaches roughly US$200 million and increases by US $30 million annually. To reverse this trend and support small-holder rice farmers in Africa with effective, sustainable and affordable solutions for control, targeted investments in research, development and capacity building are required. The top-10 priority countries where such investments would probably have the highest return are Nigeria, Guinea, Mali, Côte d’Ivoire, Cameroon, Tanzania, Madagascar, Uganda, Sierra Leone and Burkina Faso

Accounting for variability in a teacher’s epistemology: Resources and framing

Electronic appendix to article in preparation. Consists of transcript of the 2006 "Galileo Worksheet" class discussion.National Science Foundatio

Managing for Change: Achieving Systemic Reform Through the Effective Implementation of Networks for School Improvement

In August 2018, the Bill & Melinda Gates Foundation (“the foundation”) launched its Networks for School Improvement (NSIs) initiative. To further its own continuous learning as well as the learning of its grantees and the educational field, the foundation engaged the Center for Public Research and Leadership (CPRL) to conduct a formative evaluation of the NSIs initiative during its first two years. The research questions that guided this study were: How are network hubs implementing the Network for School Improvement (NSI) strategy? What are the characteristics of effective networks and network hubs? To answer these questions, CPRL used a qualitative research design to deeply explore the work of nine networks representative of the broader pool of grantees. Selection was designed to ensure diversity with respect to the following characteristics: (a) geographic location, (b) number of schools in the network, (c) number of districts in the network, (d) grade band targeted, and (e) problem of practice. The findings presented in this paper emerge from an analysis of data collected from these networks across two years. In total, CPRL conducted over 160 interviews, observed 22 network convenings, and analyzed nearly 1,000 artifacts and documents

Intestine-to-neuronal signaling alters risk-taking behaviors in food-deprived Caenorhabditis elegans.

Animals integrate changes in external and internal environments to generate behavior. While neural circuits detecting external cues have been mapped, less is known about how internal states like hunger are integrated into behavioral outputs. Here, we use the nematode C. elegans to examine how changes in internal nutritional status affect chemosensory behaviors. We show that acute food deprivation leads to a reversible decline in repellent, but not attractant, sensitivity. This behavioral change requires two conserved transcription factors MML-1 (MondoA) and HLH-30 (TFEB), both of which translocate from the intestinal nuclei to the cytoplasm during food deprivation. Next, we identify the insulin-like peptide INS-31 as a candidate ligand relaying food-status signals from the intestine to other tissues. Further, we show that neurons likely use the DAF-2 insulin receptor and AGE-1/PI-3 Kinase, but not DAF-16/FOXO to integrate these intestine-released peptides. Altogether, our study shows how internal food status signals are integrated by transcription factors and intestine-neuron signaling to generate flexible behaviors via the gut-brain axis