When students learn a new strategy, how do they determine when to apply it? We examined whether the labels givento strategies and problems may help guide generalization of the strategies. Participants read a worked example thatdemonstrated two different strategies for solving algebraic word problems. Participants then solved a set of four posttestitems. The labels given to the posttest items matched either the label given to strategy A in the lesson or the label given tostrategy B in the lesson. When solving the posttest problems, participants used the strategy whose label matched the labelthey saw on the posttest items more often than the alternative strategy, whose label did not match the posttest label. Thus,learners use labels to guide generalization of problem-solving strategies. These findings suggest that the ways teachersrefer to strategies and problem types may influence students performance.

The effects of feedback often depend on individual learnercharacteristics. In the current study, we experimentally testedwhether an individual’s task expectations influence learningfrom feedback on mathematics problems. Specifically, wemanipulated undergraduate students’ beliefs about thedifficulty of the task to influence their expectations forsuccess. Students (N = 160) were randomly assigned to one offour learning conditions based on a crossing of two factors:task expectations (easy or hard) and feedback during problemsolving (yes or no). On a final transfer test, feedback led tohigher scores than no feedback for those who expected thetask to be easy. But, feedback led to marginally lower scoresfor those who expected the task to be hard. Results suggestthat expecting the task to be hard and to experience failurecan lead to a self-fulfilling prophecy. When learning fromfeedback, students should set their expectations for success.

The dusky-footed woodrat (Neotoma fuscipes) is an endemic North American rodent belonging to the family Cricetidae. We present here the first complete mitogenome within the Neotoma genus. The mitogenome is 16,199 bp in length, and has a structure and gene organization similar to other rodent species (e.g. Mus musculus, Peromyscus maniculatus and Microtus fortis calamorum). The overall base composition is A (35.2%), C (25.5%), G (12.3%), T (27.0%), with a GC content of 37.8%, similar to other rodents. This mitogenome serves as a foundation for future phylogenetic, phylogeographic and population genetic studies.

Why do people change their strategies for solving problems? In this research, we tested whether negative feedback and the context in which learners encounter a strategy influence their likelihood of adopting that strategy. In particular, we examined whether strategy adoption varied when learners were exposed to a target strategy in isolation, in conjunction with their own current strategy, and in conjunction with another novel strategy. We also investigated the roles of individual differences, including learners need for cognition and their confidence in their current strategies. In Study 1, undergraduate participants who encountered a target strategy in isolation were more likely to adopt it than participants who encountered it in the context of their own current strategy. Negative feedback, low confidence, and high need for cognition also predicted greater adoption. In Study 2, we examined whether rates of strategy adoption depended on the target strategy itself. Indeed, participants were more likely to adopt one strategy than the other, and the effects of feedback also varied across strategies. Individual differences-need for cognition and confidence-also influenced patterns of strategy adoption. These results suggest that strategy adoption depends on the confluence of many factors, including the context in which a target strategy is introduced, characteristics of the learner, and characteristics of the strategy itself.

Why do people shift their strategies for solving problems? Past work has focused on the roles of contextual and individual factors in explaining whether people adopt new strategies when they are exposed to them. In this study, we examined a factor not considered in prior work: people's evaluations of the strategies themselves. We presented undergraduate participants from a moderately selective university (N = 252; 64.8% women, 65.6% White, 67.6% who had taken calculus) with two strategies for solving algebraic word problems and asked them to rate these strategies and their own strategy on a variety of dimensions. Participants' ratings loaded onto two factors, which we label quality and difficulty. Participants' initial evaluations of the quality of the strategies were associated with whether they used the strategies at posttest, and this effect held even when controlling for individual and contextual factors. However, people's evaluations of the difficulty of the strategies were not consistently associated with their later adoption of those strategies. We also examined individual and contextual predictors of strategy ratings and strategy adoption. Participants' need for cognition and their spatial visualization ability were associated with their strategy evaluations, and the framing of the story problems was associated with their strategy adoption. The findings highlight that strategy adoption depends on multiple interacting factors, and that to understand strategy change, it is critical to examine how people evaluate strategies.

What factors affect whether learners adopt a new problem-solving strategy? Potential factors include learners’evaluations of alternative strategies and the degree of similaritybetween their existing strategy and the alternatives. A first stepin answering this question is investigating how people evaluatestrategies. This exploratory study investigated how peopleevaluate strategies for solving algebraic word problems, andhow these evaluations vary as function of individualdifferences. Undergraduates rated three strategies on sixdimensions and judged each pair of strategies for similarity.Factor analysis showed that evaluations could be reduced totwo constructs: efficiency and intuitiveness. We calculatedfactor scores for each participant for each strategy. Efficiencydid not predict similarity ratings on its own, but it did interactwith Need for Cognition. These results suggest stable learnercharacteristics and moment-to-moment evaluations ofstrategies influence judgments about strategy similarity.

Understanding how species have responded to past climate change may help refine projections of how species and biotic communities will respond to future change. Here, we integrate estimates of genome-wide genetic variation with demographic and niche modeling to investigate the historical biogeography of an important ecological engineer: the dusky-footed woodrat, Neotoma fuscipes. We use RADseq to generate a genome-wide dataset for 71 individuals from across the geographic distribution of the species in California. We estimate population structure using several model-based methods and infer the demographic history of regional populations using a site frequency spectrum-based approach. Additionally, we use ecological niche modeling to infer current and past (Last Glacial Maximum) environmental suitability across the species' distribution. Finally, we estimate the directionality and possible spatial origins of regional population expansions. Our analyses indicate this species is subdivided into three regionally distinct populations, with the deepest divergence occurring ~1.7 million years ago across the modern-day San Francisco-Bay Delta region; a common biogeographic barrier for the flora and fauna of California. Our models of environmental suitability through time coincide with our estimates of population expansion, with relative long-term stability in the southern portion of the range, and more recent expansion into the northern end of the range. Our study illustrates how the integration of genome-wide data with spatial and demographic modeling can reveal the timing and spatial extent of historic events that determine patterns of biotic diversity and may help predict biotic response to future change.

Feedstock blending as a strategy to mitigate risks in the supply of lignocellulosic biomass to commercial scale biorefineries across various geographical areas in the United States. Machine learning predictive models estimate sugar yields from feedstock blends expected to be available in Florida and Kansas. Performance of each model was assessed based on feature selection along with two-stack ensembles applied in both linear and nonlinear algorithms. Linear-weighted ensemble and nonlinear stochastic gradient boosting model ensembled with four base learners exhibited similar predictions as previously developed linear regression models when predicting glucose yields in the higher range. The ensemble models achieved a 10–50 % improvement in the root mean squared error with feature selection compared to models with full features from validation. Machine learning has the potential to predict sugar yields at high confidence for a given feedstock blend ratio and pretreatment conditions.

It is increasingly common for apex predators to face a multitude of complex conservation issues. In Australia, dingoes are the mainland apex predator and play an important role in ecological functioning. Currently, however, they are threatened by hybridization with modern domestic dogs in the wild. As a consequence, we explore how increasing our understanding of the evolutionary history of dingoes can inform management and conservation decisions. Previous research on whole mitochondrial genome and nuclear data from five geographical populations showed evidence of two distinct lineages of dingo. Here, we present data from a broader survey of dingoes around Australia using both mitochondrial and Y chromosome markers and investigate the timing of demographic expansions. Biogeographic data corroborate the presence of at least two geographically subdivided genetic populations, southeastern and northwestern. Demographic modeling suggests that dingoes have undergone population expansion in the last 5,000 years. It is not clear whether this stems from expansion into vacant niches after the extinction of thylacines on the mainland or indicates the arrival date of dingoes. Male dispersal is much more common than female, evidenced by more diffuse Y haplogroup distributions. There is also evidence of likely historical male biased introgression from domestic dogs into dingoes, predominately within southeastern Australia. These findings have critical practical implications for the management and conservation of dingoes in Australia; particularly a focus must be placed upon the threatened southeastern dingo population.