Solving problems in genetics

Aznar, Mercedes Martínez; Orcajo, Teresa Ibáñez

doi:10.1080/09500690410001673801

Cited by 18 publications

(9 citation statements)

References 32 publications

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“…Such a problem is common in genetics studies in high school and is anchored in the learners' prior knowledge. The problem requires that students work from effect (phenotype) to cause (the possible genotype), as scientists do (Aznar and Orcajo 2005;Johnson and Stewart 1990;Stewart 1988). The genetic character in question is unique in that it becomes evident at a relatively advanced age and therefore, the only way to determine whether an offspring will become deaf in adulthood is to identify the gene that is involved in deafness in the family.…”

Section: The Unique Features Of the Research Simulationmentioning

confidence: 99%

The Impact of a Web-Based Research Simulation in Bioinformatics on Students’ Understanding of Genetics

2008

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Providing learners with opportunities to engage in activities similar to those carried out by scientists was addressed in a web-based research simulation in genetics developed for high school biology students. The research simulation enables learners to apply their genetics knowledge while giving them an opportunity to participate in an authentic genetics study using bioinformatics tools. The main purpose of the study outlined here is to examine how learning using this research simulation influences students' understanding of genetics, and how students' approaches to learning using the simulation influence their learning outcomes. Using both quantitative and qualitative procedures, we were able to show that while learning using the simulation students expanded their understanding of the relationships between molecular mechanisms and phenotype, and refined their understanding of certain genetic concepts. Two types of learners, researchoriented and task-oriented, were identified on the basis of the differences in the ways they seized opportunities to recognize the research practices, which in turn influenced their learning outcomes. The research-oriented learners expanded their genetics knowledge more than the task-oriented learners. The learning approach taken by the research-oriented learners enabled them to recognize the epistemology that underlies authentic genetic research, while the task-oriented learners referred to the research simulation as a set of simple procedural tasks. Thus, task-oriented learners should be encouraged by their teachers to cope with the scientists' steps, while learning genetics through the simulation in a class setting.

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Section: The Unique Features Of the Research Simulationmentioning

confidence: 99%

The Impact of a Web-Based Research Simulation in Bioinformatics on Students’ Understanding of Genetics

2008

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“…With sustained commitment, task performers reach to the goal they expected. Efficacy that one gained from the performance success reinforces the confidence on one' s ability and strategy (Aznar & Orcajo, 2005). Likewise, when students complete tasks, their confidence about strategies are refined with task knowledge and domain-specific understanding (Butler & Winne, 1995).…”

Section: Self Confidencementioning

confidence: 97%

Development of An Inventory to Classify Task Commitment Type in Science Learning and Its Application to Classify Students' Types

Kim¹,

Byeon²,

Kwon³

2013

Journal of The Korean Association For Research In Science Educa

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The purpose of this study is to develop an inventory to classify task commitment types of science learning and to classify highschool students' task commitment types. Firstly, inventory questions were designed following the literature analysis on the task commitment components which involve self confidence, high goal setting, and focused attention. Prototype inventory underwent the content validity test, pilot test, and reliability test. Through these steps, final inventory was input to 462 high school students and underwent the factor analysis and cluster analysis. Factor analysis confirmed three components of task commitment as the three factors of inventory questions. In order to find how many clusters exist, factors of developed inventory became new variables. Each factor's factor mean was calculated and served as the new variable of the cluster analysis. Cluster analysis extracted five clusters as task commitment types. The 5 clusters were suggested by the agglomarative schedule and dendrogram gained from a hierarchical cluster analysis with the setting of the Ward algorithm and Squared Euclidean distance. Based on the factor mean score, traits of each cluster could be drawn out. Inventory developed by this study is expected to be used to identify student commitment types and assess the effectiveness of task commitment enhancement programs.

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“…La dc 2 va íntimamente asociada con la dc 1 (Reyes, 1991) al estar condicionada por el marco teórico. No obstante, en un contexto biológico sí es posible que la dc 2 sea superior a la dc 1, como sucede en la situación problemática 3, debido a que son contextos más próximos al conocimiento de los estudiantes y que no requieren del dominio del marco teórico para plantear sus hipótesis (Martínez Aznar e Ibáñez, 2005). Finalmente, la sp 4 obtiene un valor medio superior a 2,5 pero inferior al resto de dc.…”

Section: Primera Pregunta De Investigaciónunclassified

“…Sus niveles medios en torno a 3 permiten reconocer que los grupos han desarrollado esta dc de forma aceptable. Estos resultados difieren de los obtenidos en otras investigaciones (Martínez Aznar e Ibáñez, 2005) para situaciones problemáticas de genética, donde la dc 3 obtenía valores medios finales superiores al resto. -dc 4 o resolución de la situación problemática.…”

Section: Primera Pregunta De Investigaciónunclassified

“…Los resultados inicialmente bajos respecto a la mayoría de las dc coinciden con los obtenidos para contenidos de física y química por otros autores (Varela, 1994;Bárcena, 2015), aunque en esta ocasión acaban en valores altos y similares a la dc 3 y la dc 5. Sin embargo, si se compara con experiencias en el contexto de la biología, los resultados no coinciden con los recogidos por otros investigadores (Martínez Aznar e Ibáñez, 2005), donde la dc 4 era resuelta mejor que la dc 3 por el alumnado, es decir, realizaban mejor la resolución del problema que la descripción de cómo iban a resolverlo. -dc 5 o análisis de los resultados.…”

Section: Primera Pregunta De Investigaciónunclassified

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Resolución de problemas abiertos en ecología para la ESO

Novalbos

Aznar

2019

ensciencias

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Esta investigación de tipo cuasiexperimental se basa en la metodología indagativa MRPI (metodología de resolución de problemas como investigación) para el aprendizaje de la ecología con escolares de 13-14 años (2.º de ESO). Se diseñó e implementó una unidad didáctica centrada en situaciones problemáticas abiertas contextualizadas. A partir de las resoluciones se analizaron los aprendizajes en términos competenciales para el grupo experimental y se compararon los logros conseguidos en la resolución de un ejercicio cerrado con los de un grupo control que siguió un enfoque más tradicional de enseñanza. El grupo experimental alcanzó un nivel óptimo en todas las dimensiones de la competencia científica presentes en la MRPI y afrontaron los problemas cerrados de forma más metódica y completa que el grupo control.

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Solving problems in genetics

Cited by 18 publications

References 32 publications

The Impact of a Web-Based Research Simulation in Bioinformatics on Students’ Understanding of Genetics

The Impact of a Web-Based Research Simulation in Bioinformatics on Students’ Understanding of Genetics

Development of An Inventory to Classify Task Commitment Type in Science Learning and Its Application to Classify Students' Types

Resolución de problemas abiertos en ecología para la ESO

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