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Developing metacognition in students is essential for fostering critical thinking in school. One of the skills necessary to achieve this goal is the cultivation of metacognitive vigilance—a potential means to regulate some ways of thinking held by individuals. Of particular importance is essentialism, as it underlies discourses such as racism and also hinders the comprehension of various biological models. In this paper, we aim to characterize the metacognitive regulations on essentialism made by high school students from Buenos Aires, Argentina. This exploration occurred within the context of a didactic sequence on the relationship between biology and human races, designed to promote metacognitive vigilance. Employing a qualitative approach, various types of metacognitive reflections were identified. These reflections reveal that some of the students consciously identified instances of essentialism in their daily lives, assessed its legitimacy, and constructed alternative explanations by drawing from biological models. These findings underscore the importance of nurturing metacognition as a means to deconstruct hegemonic and common-sense discourses, including those rooted in racism.

BackgroundTeleology is one of the critical aspects of students’ intuitive concepts about living beings and, specifically, their evolution. This cognitive bias imposes a substantial restriction on the process of learning such content. In this work, we rely on epistemological, psychological and pedagogical analyses to substantiate an educational proposal centered on the concepts of epistemological obstacles and metacognitive vigilance.ResultsBased on Michael Ruse’s epistemological analysis, according to which teleology in biology persists because the scientific explanation of adaptation necessarily involves appeal to the metaphor of design, and on research in cognitive psychology, especially in relation to metacognition and self-regulated learning, we argue that the primary educational aim must be to encourage students to develop metacognitive skills to regulate the use of teleological reasoning. We develop our instructional proposal based on the didactic concepts of epistemological obstacles and metacognitive vigilance (consistent with epistemological and psychological analyses).ConclusionWe briefly discuss the instructional implications of our analysis and some possible relationships between our proposal and other lines of research in psychology and science education.

Existe consenso en la comunidad académica en que la metacognición influye en los aprendizajes de los sujetos, así como en su constitución como ciudadanos críticos. No obstante, al ser diversas las áreas que investigan este fenómeno es difícil tener una caracterización consensuada del mismo. El objetivo de este artículo es presentar una posible definición de este constructo que sea útil para la construcción de actividades en ciencias. Desde las investigaciones en enseñanza de las ciencias, y en particular de la biología, presentaremos ejemplos concretos relacionados con la lectura de textos científicos, la resolución de problemas y los obstáculos epistemológicos.

Recent advances in pharmacogenomics have generated a wealth of data of different types whose analysis have helped in the identification of signatures of different cellular sensitivity/resistance responses to hundreds of chemical compounds. Among the different data types, gene expression has proven to be the more successful for the inference of drug response in cancer cell lines. Although effective, the whole transcriptome can introduce noise in the predictive models, since specific mechanisms are required for different drugs and these realistically involve only part of the proteins encoded in the genome. We analyzed the pharmacogenomics data of 961 cell lines tested with 265 anti-cancer drugs and developed different machine learning approaches for dissecting the genome systematically and predict drug responses using both drug-unspecific and drug-specific genes. These methodologies reach better response predictions for the vast majority of the screened drugs using tens to few hundreds genes specific to each drug instead of the whole genome, thus allowing a better understanding and interpretation of drug-specific response mechanisms which are not necessarily restricted to the drug known targets.

In this work we propose a general framework that provides a unified convergence analysis for nonmonotone decomposition algorithms. The main motivation to embed nonmonotone strategies within a decomposition approach lies in the fact that enforcing the reduction of the objective function could be unnecessarily expensive, taking into account that groups of variables are individually updated. We define different search directions and line searches satisfying the conditions required by the presented nonmonotone decomposition framework to obtain global convergence. We employ a set of large-scale network equilibrium problems as a computational example to show the advantages of a nonmonotone algorithm over its monotone counterpart. In conclusion, a new smart implementation for decomposition methods has been derived to solve numerical issues on large-scale partially separable functions.

The generalized Nash equilibrium problem (GNEP) is often difficult to solve by Newton-type methods since the problem tends to have locally nonunique solutions. Here we take an existing trust-region method which is known to be locally fast convergent under a relatively mild error bound condition, and modify this method by a nonmonotone strategy in order to obtain a more reliable and efficient solver. The nonmonotone trust-region method inherits the nice local convergence properties of its monotone counterpart and is also shown to have the same global convergence properties. Numerical results indicate that the nonmonotone trust-region method is significantly better than the monotone version, and is at least competitive to an existing software applied to the same reformulation used within our trust-region framework. Additional tests on quasi-variational inequalities (QVI) are also presented to validate efficiency of the proposed extension.

Este artículo hace una aproximación a la naturaleza, definiciones, circunstancias y significados del concepto biotecnología, y a sus implicaciones para la enseñanza. La aproximación al surgimiento de este concepto indica la pluralidad de significados y de disciplinas que abarca, así como su complejidad. Las conclusiones hacen evidente la importancia de su investigación en la didáctica de las ciencias y la relevancia de incluir en la formación inicial de profesores de ciencias naturales aspectos filosóficos, históricos y epistemológicos de la biotecnología.

This article focuses on a particularly problematic passage from Lucretius’ De rerum natura (3, 492-3). Several editors retain the term distracta referring to uis morbi, but this choice is untenable, since the meaning of the verb does not fit with disease. Others believe that distracta refers to the soul and therefore change the nominative uis to the ablative ui; however, this solution requires either correcting animam to anima (which creates a metrical anomaly) or positing a lacuna between ll. 492 and 493. Drawing upon a conjecture made by Gilbert, I propose uis animist instead of uis morbi; this proposal, which requires a different punctuation from that generally accepted, is supported by a detailed linguistic and stylistic analysis of the passage. L’articolo tratta un passo particolarmente problematico del De rerum natura lucreziano (3, 492-3). Vari editori mantengono distracta in riferimento a uis morbi, ma ciò è difficilmente sostenibile, poiché il significato del verbo non si attaglia alla malattia. Altri credono che distracta si riferisca all’anima e, pertanto, mutano il nominativo uis all’ablativo ui; tuttavia, questa soluzione impone di correggere animam in anima (il che comporta un’anomalia metrica) oppure di postulare una lacuna tra i vv. 492-3. Prendendo spunto da una congettura di Gilbert, propongo uis animist invece di uis animi; questa soluzione, che richiede un’interpunzione diversa da quella maggiormente adottata, è suffragata da un’ampia analisi linguistica e stilistica del passo in questione.

Human beings are predisposed to think of evolution as teleological—i.e., having a purpose or directive principle—and the ways scientists talk about natural selection can feed this predisposition. This work examines the suggestion that students’ teleological thinking operates as an obstacle when the natural selection evolution model is taught. What we mean by obstacle is an established way of thinking that resists change due to its explanatory power. In light of this approach, the challenges of teaching evolution in biology education have been revised, and improved methodological strategies aimed at a better comprehension of the Darwinian evolution model are suggested.

Recent works have shown that line search methods greatly increase performance of traditional stochastic gradient descent methods on a variety of datasets and architectures [1], [2]. In this work we succeed in extending line search methods to the novel and highly popular Transformer architecture and dataset domains in natural language processing. More specifically, we combine the Armijo line search with the Adam optimizer and extend it by subdividing the networks architecture into sensible units and perform the line search separately on these local units. Our optimization method outperforms the traditional Adam optimizer and achieves significant performance improvements for small data sets or small training budgets, while performing equal or better for other tested cases. Our work is publicly available as a python package, which provides a hyperparameter-free pytorch optimizer that is compatible with arbitrary network architectures.