Pedagosko i psiholosko testiranje i procjenjivanje spadaju među najvažnije doprinose znanosti o ponasanju nasem drustvu i pružaju temeljna i znacajna poboljsanja u odnosu na ranije postupke. Iako se ne može ustvrditi da su svi testovi dovoljno usavrseni niti da su sva testiranja razborita i korisna, postoji velika kolicina informacija koje ukazuju na ucinkovitost kvalitetnih instrumenata u onim situacijama u kojima je njihovo koristenje potkrijepljeno validacijskim podacima. Pravilna upotreba testova može dovesti do boljih odluka o pojedincima i programima nego sto bi to bio slucaj bez njihovog koristenja, a također i ukazati na put za siri i pravedniji pristup obrazovanju i zaposljavanju. Međutim, losa upotreba testova može dovesti do zamjetne stete nanesene ispitanicima i drugim sudionicima u procesu donosenja odluka na temelju testovnih podataka. Cilj Standarda je promoviranje kvalitetne i eticne upotrebe testova te uspostavljanje osnovice za ocjenu kvalitete postupaka testiranja. Svrha objavljivanja Standarda je uspostavljanje kriterija za evaluaciju testova, provedbe testiranja i posljedica upotrebe testova. Iako bi evaluacija prikladnosti testa ili njegove primjene trebala ovisiti prvenstveno o strucnim misljenjima, Standardi pružaju okvir koji osigurava obuhvacanje svih relevantnih pitanja. Bilo bi poželjno da svi autori, sponzori, nakladnici i korisnici profesionalnih testova usvoje Standarde te da poticu druge da ih također prihvate.

Standards for educational and psychological testing

Distributions of Earth’s species are changing at accelerating rates, increasingly driven by human-mediated climate change. Such changes are already altering the composition of ecological communities, but beyond conservation of natural systems, how and why does this matter? We review evidence that climate-driven species redistribution at regional to global scales affects ecosystem functioning, human well-being, and the dynamics of climate change itself. Production of natural resources required for food security, patterns of disease transmission, and processes of carbon sequestration are all altered by changes in species distribution. Consideration of these effects of biodiversity redistribution is critical yet lacking in most mitigation and adaptation strategies, including the United Nation’s Sustainable Development Goals.

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Biodiversity redistribution under climate change: impacts on ecosystems and human well-being

Current predictions of extinction risks from climate change vary widely depending on the specific assumptions and geographic and taxonomic focus of each study. I synthesized published studies in order to estimate a global mean extinction rate and determine which factors contribute the greatest uncertainty to climate change–induced extinction risks. Results suggest that extinction risks will accelerate with future global temperatures, threatening up to one in six species under current policies. Extinction risks were highest in South America, Australia, and New Zealand, and risks did not vary by taxonomic group. Realistic assumptions about extinction debt and dispersal capacity substantially increased extinction risks. We urgently need to adopt strategies that limit further climate change if we are to avoid an acceleration of global extinctions.

Accelerating extinction risk from climate change

Most ecological processes now show responses to anthropogenic climate change. In terrestrial, freshwater, and marine ecosystems, species are changing genetically, physiologically, morphologically, and phenologically and are shifting their distributions, which affects food webs and results in new interactions. Disruptions scale from the gene to the ecosystem and have documented consequences for people, including unpredictable fisheries and crop yields, loss of genetic diversity in wild crop varieties, and increasing impacts of pests and diseases. In addition to the more easily observed changes, such as shifts in flowering phenology, we argue that many hidden dynamics, such as genetic changes, are also taking place. Understanding shifts in ecological processes can guide human adaptation strategies. In addition to reducing greenhouse gases, climate action and policy must therefore focus equally on strategies that safeguard biodiversity and ecosystems.

https://science.sciencemag.org/content/sci/354/6313/aaf7671.full.pdf

The broad footprint of climate change from genes to biomes to people

BACKGROUND As global climate change accelerates, one of the most urgent tasks for the coming decades is to develop accurate predictions about biological responses to guide the effective protection of biodiversity. Predictive models in biology provide a means for scientists to project changes to species and ecosystems in response to disturbances such as climate change. Most current predictive models, however, exclude important biological mechanisms such as demography, dispersal, evolution, and species interactions. These biological mechanisms have been shown to be important in mediating past and present responses to climate change. Thus, current modeling efforts do not provide sufficiently accurate predictions. Despite the many complexities involved, biologists are rapidly developing tools that include the key biological processes needed to improve predictive accuracy. The biggest obstacle to applying these more realistic models is that the data needed to inform them are almost always missing. We suggest ways to fill this growing gap between model sophistication and information to predict and prevent the most damaging aspects of climate change for life on Earth. ADVANCES On the basis of empirical and theoretical evidence, we identify six biological mechanisms that commonly shape responses to climate change yet are too often missing from current predictive models: physiology; demography, life history, and phenology; species interactions; evolutionary potential and population differentiation; dispersal, colonization, and range dynamics; and responses to environmental variation. We prioritize the types of information needed to inform each of these mechanisms and suggest proxies for data that are missing or difficult to collect. We show that even for well-studied species, we often lack critical information that would be necessary to apply more realistic, mechanistic models. Consequently, data limitations likely override the potential gains in accuracy of more realistic models. Given the enormous challenge of collecting this detailed information on millions of species around the world, we highlight practical methods that promote the greatest gains in predictive accuracy. Trait-based approaches leverage sparse data to make more general inferences about unstudied species. Targeting species with high climate sensitivity and disproportionate ecological impact can yield important insights about future ecosystem change. Adaptive modeling schemes provide a means to target the most important data while simultaneously improving predictive accuracy. OUTLOOK Strategic collections of essential biological information will allow us to build generalizable insights that inform our broader ability to anticipate species’ responses to climate change and other human-caused disturbances. By increasing accuracy and making uncertainties explicit, scientists can deliver improved projections for biodiversity under climate change together with characterizations of uncertainty to support more informed decisions by policymakers and land managers. Toward this end, a globally coordinated effort to fill data gaps in advance of the growing climate-fueled biodiversity crisis offers substantial advantages in efficiency, coverage, and accuracy. Biologists can take advantage of the lessons learned from the Intergovernmental Panel on Climate Change’s development, coordination, and integration of climate change projections. Climate and weather projections were greatly improved by incorporating important mechanisms and testing predictions against global weather station data. Biology can do the same. We need to adopt this meteorological approach to predicting biological responses to climate change to enhance our ability to mitigate future changes to global biodiversity and the services it provides to humans.

http://science.sciencemag.org/content/sci/353/6304/aad8466.full.pdf

Improving the forecast for biodiversity under climate change

Anthropogenic climate change is predicted to be a major cause of species extinctions in the next 100 years. But what will actually cause these extinctions? For example, will it be limited physiological tolerance to high temperatures, changing biotic interactions or other factors? Here, we systematically review the proximate causes of climate-change related extinctions and their empirical support. We find 136 case studies of climatic impacts that are potentially relevant to this topic. However, only seven identified proximate causes of demonstrated local extinctions due to anthropogenic climate change. Among these seven studies, the proximate causes vary widely. Surprisingly, none show a straightforward relationship between local extinction and limited tolerances to high temperature. Instead, many studies implicate species interactions as an important proximate cause, especially decreases in food availability. We find very similar patterns in studies showing decreases in abundance associated with climate change, and in those studies showing impacts of climatic oscillations. Collectively, these results highlight our disturbingly limited knowledge of this crucial issue but also support the idea that changing species interactions are an important cause of documented population declines and extinctions related to climate change. Finally, we briefly outline general research strategies for identifying these proximate causes in future studies.

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How does climate change cause extinction

Aim The factors that set species range limits underlie many patterns in ecology, evolution, biogeography and conservation. These factors have been the subject of several reviews, but there has been no systematic review of the causes of warm-edge limits (low elevations and latitudes). Understanding these causes is urgent, given that the factors that set these limits might also drive extinction at warm edges as global climate changes. Many authors have suggested that warm-edge limits are set by biotic factors (particularly competition) whereas others have stressed abiotic factors (particularly temperature). We synthesize the known causes of species’ warm-edge range limits, with emphasis on the underlying mechanisms (proximate causes).

/pdf/causes-of-warm-edge-range-limits-systematic-review-proximate-1n4sbdy2s1.pdf

Causes of warm-edge range limits: Systematic review, proximate factors and implications for climate change

Do You See What I-SEA? A Rasch Analysis of the Psychometric Properties of the Inventory of Student Evolution Acceptance.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/tea.21547

How strongly does statistical reasoning influence knowledge and acceptance of evolution

Increasing the retention of STEM (science, technology, engineering, and mathematics) majors has recently emerged as a national priority in undergraduate education. Since poor performance in large introductory science and math courses is one significant factor in STEM dropout, early detection of struggling students is needed. Technology-supported “early warning systems” (EWSs) are being developed to meet these needs. Our study explores the utility of two commonly collected data sources—pre-course concept inventory scores and longitudinal clicker scores—for use in EWS, specifically, in determining the time points at which robust predictions of student success can first be established. The pre-course diagnostic assessments, administered to 287 students, included two concept inventories and one attitude assessment. Clicker question scores were also obtained for each of the 37 class sessions. Additionally, student characteristics (sex, ethnicity, and English facility) were gathered in a survey. Our analyses revealed that all variables were predictive of final grades. The correlation of the first 3 weeks of clicker scores with final grades was 0.53, suggesting that this set of variables could be used in an EWS starting at the third week. We also used group-based trajectory models to assess whether trajectory patterns were homogeneous in the class. The trajectory analysis identified three distinct clicker performance patterns that were also significant predictors of final grade. Trajectory analyses of clicker scores, student characteristics, and pre-course diagnostic assessment appear to be valuable data sources for EWS, although further studies in a diversity of instructional contexts are warranted.

Gena C. Sbeglia

Papers

How does climate change cause extinction

Causes of warm-edge range limits: Systematic review, proximate factors and implications for climate change

Do You See What I-SEA? A Rasch Analysis of the Psychometric Properties of the Inventory of Student Evolution Acceptance.

How strongly does statistical reasoning influence knowledge and acceptance of evolution

Clicker Score Trajectories and Concept Inventory Scores as Predictors for Early Warning Systems for Large STEM Classes