Volver al buscador
Vista en detalle del documento
Titulo Artículo:
The Quantitative Methods Boot Camp: Teaching Quantitative Thinking and Computing Skills to Graduate Students in the Life Sciences
Resumen:
The past decade has seen a rapid increase in the ability of biologists to collect large amounts of data. It is therefore vital that research biologists acquire the necessary skills during their training to visualize, analyze, and interpret such data. To begin to meet this need, we have developed a “boot camp” in quantitative methods for biology graduate students at Harvard Medical School. The goal of this short, intensive course is to enable students to use computational tools to visualize and analyze data, to strengthen their computational thinking skills, and to simulate and thus extend their intuition about the behavior of complex biological systems. The boot camp teaches basic programming using biological examples from statistics, image processing, and data analysis. This integrative approach to teaching programming and quantitative reasoning motivates students’ engagement by demonstrating the relevance of these skills to their work in life science laboratories. Students also have the opportunity to analyze their own data or explore a topic of interest in more detail. The class is taught with a mixture of short lectures, Socratic discussion, and in-class exercises. Students spend approximately 40% of their class time working through both short and long problems. A high instructor-to-student ratio allows students to get assistance or additional challenges when needed, thus enhancing the experience for students at all levels of mastery. Data collected from end-of-course surveys from the last five offerings of the course (between 2012 and 2014) show that students report high learning gains and feel that the course prepares them for solving quantitative and computational problems they will encounter in their research. We outline our course here which, together with the course materials freely available online under a Creative Commons License, should help to facilitate similar efforts by others.
Fecha de publicación:
2015.
Autores :
,Johanna L. Gutlerner;
Richard T. Born;
Michael Springer ;
Melanie I. Stefan;
Autor corporativo:
PLOS Computational Biology,
Editores:
Biblioteca Virtual en Salud(BVS) ;
Signatura Topográfica:
4
Idioma:
Inglés
Páginas:
1
ISBN:
1544-9173
Existencias:
12
Palabras claves:
Teaching Quantitative
Computing Skills
Campo de entrenamiento
Público objetivo:
Docentes
Investigadores
Educadores Medicos
Otros profesionales de la salud
Titulo Artículo:
The Quantitative Methods Boot Camp: Teaching Quantitative Thinking and Computing Skills to Graduate Students in the Life Sciences
Resumen:
The past decade has seen a rapid increase in the ability of biologists to collect large amounts of data. It is therefore vital that research biologists acquire the necessary skills during their training to visualize, analyze, and interpret such data. To begin to meet this need, we have developed a “boot camp” in quantitative methods for biology graduate students at Harvard Medical School. The goal of this short, intensive course is to enable students to use computational tools to visualize and analyze data, to strengthen their computational thinking skills, and to simulate and thus extend their intuition about the behavior of complex biological systems. The boot camp teaches basic programming using biological examples from statistics, image processing, and data analysis. This integrative approach to teaching programming and quantitative reasoning motivates students’ engagement by demonstrating the relevance of these skills to their work in life science laboratories. Students also have the opportunity to analyze their own data or explore a topic of interest in more detail. The class is taught with a mixture of short lectures, Socratic discussion, and in-class exercises. Students spend approximately 40% of their class time working through both short and long problems. A high instructor-to-student ratio allows students to get assistance or additional challenges when needed, thus enhancing the experience for students at all levels of mastery. Data collected from end-of-course surveys from the last five offerings of the course (between 2012 and 2014) show that students report high learning gains and feel that the course prepares them for solving quantitative and computational problems they will encounter in their research. We outline our course here which, together with the course materials freely available online under a Creative Commons License, should help to facilitate similar efforts by others.
Fecha de publicación:
2015.
Autores :
,Johanna L. Gutlerner;
Richard T. Born;
Michael Springer ;
Melanie I. Stefan;
Autor corporativo:
PLOS Computational Biology,
Editores:
Biblioteca Virtual en Salud(BVS) ;
Signatura Topográfica:
4
Idioma:
Inglés
Páginas:
1
Existencias:
12
Palabras claves:
Teaching Quantitative
Computing Skills
Campo de entrenamiento
Público objetivo:
Docentes
Investigadores
Educadores Medicos
Otros profesionales de la salud
Titulo Artículo:
The Quantitative Methods Boot Camp: Teaching Quantitative Thinking and Computing Skills to Graduate Students in the Life Sciences
Resumen:
The past decade has seen a rapid increase in the ability of biologists to collect large amounts of data. It is therefore vital that research biologists acquire the necessary skills during their training to visualize, analyze, and interpret such data. To begin to meet this need, we have developed a “boot camp” in quantitative methods for biology graduate students at Harvard Medical School. The goal of this short, intensive course is to enable students to use computational tools to visualize and analyze data, to strengthen their computational thinking skills, and to simulate and thus extend their intuition about the behavior of complex biological systems. The boot camp teaches basic programming using biological examples from statistics, image processing, and data analysis. This integrative approach to teaching programming and quantitative reasoning motivates students’ engagement by demonstrating the relevance of these skills to their work in life science laboratories. Students also have the opportunity to analyze their own data or explore a topic of interest in more detail. The class is taught with a mixture of short lectures, Socratic discussion, and in-class exercises. Students spend approximately 40% of their class time working through both short and long problems. A high instructor-to-student ratio allows students to get assistance or additional challenges when needed, thus enhancing the experience for students at all levels of mastery. Data collected from end-of-course surveys from the last five offerings of the course (between 2012 and 2014) show that students report high learning gains and feel that the course prepares them for solving quantitative and computational problems they will encounter in their research. We outline our course here which, together with the course materials freely available online under a Creative Commons License, should help to facilitate similar efforts by others.
Autores:
,Johanna L. Gutlerner
,
Richard T. Born
,
Michael Springer
,
Melanie I. Stefan
,
.
Titulo Revista:
PLOS Computational Biology,
.
Numero:
4
Volumen:
11
Fecha de publicación:
2015.
Base de Datos Bibliográfica:
Biblioteca Virtual en Salud(BVS) ,
.
Suplemento:
Idioma:
Inglés
Página Inicial:
1
Página Final:
12
ISBN:
1544-9173
Palabras claves:
Teaching Quantitative
Computing Skills
Campo de entrenamiento
Público objetivo:
Docentes
Investigadores
Educadores Medicos
Otros profesionales de la salud
Título Biblioteca Virtual en Salud(BVS) :
The Quantitative Methods Boot Camp: Teaching Quantitative Thinking and Computing Skills to Graduate Students in the Life Sciences
Resumen:
The past decade has seen a rapid increase in the ability of biologists to collect large amounts of data. It is therefore vital that research biologists acquire the necessary skills during their training to visualize, analyze, and interpret such data. To begin to meet this need, we have developed a “boot camp” in quantitative methods for biology graduate students at Harvard Medical School. The goal of this short, intensive course is to enable students to use computational tools to visualize and analyze data, to strengthen their computational thinking skills, and to simulate and thus extend their intuition about the behavior of complex biological systems. The boot camp teaches basic programming using biological examples from statistics, image processing, and data analysis. This integrative approach to teaching programming and quantitative reasoning motivates students’ engagement by demonstrating the relevance of these skills to their work in life science laboratories. Students also have the opportunity to analyze their own data or explore a topic of interest in more detail. The class is taught with a mixture of short lectures, Socratic discussion, and in-class exercises. Students spend approximately 40% of their class time working through both short and long problems. A high instructor-to-student ratio allows students to get assistance or additional challenges when needed, thus enhancing the experience for students at all levels of mastery. Data collected from end-of-course surveys from the last five offerings of the course (between 2012 and 2014) show that students report high learning gains and feel that the course prepares them for solving quantitative and computational problems they will encounter in their research. We outline our course here which, together with the course materials freely available online under a Creative Commons License, should help to facilitate similar efforts by others.
Autores :
,Johanna L. Gutlerner;
Richard T. Born;
Michael Springer ;
Melanie I. Stefan;
Autor corporativo:
PLOS Computational Biology,
Fecha de publicación:
2015.
Tipo :
Biblioteca Virtual en Salud(BVS) .
Idioma:
Inglés
Palabras claves:
Teaching Quantitative
Computing Skills
Campo de entrenamiento
Público objetivo:
Docentes
Investigadores
Educadores Medicos
Otros profesionales de la salud
Título Biblioteca Virtual en Salud(BVS) :
The Quantitative Methods Boot Camp: Teaching Quantitative Thinking and Computing Skills to Graduate Students in the Life Sciences
Resumen:
The past decade has seen a rapid increase in the ability of biologists to collect large amounts of data. It is therefore vital that research biologists acquire the necessary skills during their training to visualize, analyze, and interpret such data. To begin to meet this need, we have developed a “boot camp” in quantitative methods for biology graduate students at Harvard Medical School. The goal of this short, intensive course is to enable students to use computational tools to visualize and analyze data, to strengthen their computational thinking skills, and to simulate and thus extend their intuition about the behavior of complex biological systems. The boot camp teaches basic programming using biological examples from statistics, image processing, and data analysis. This integrative approach to teaching programming and quantitative reasoning motivates students’ engagement by demonstrating the relevance of these skills to their work in life science laboratories. Students also have the opportunity to analyze their own data or explore a topic of interest in more detail. The class is taught with a mixture of short lectures, Socratic discussion, and in-class exercises. Students spend approximately 40% of their class time working through both short and long problems. A high instructor-to-student ratio allows students to get assistance or additional challenges when needed, thus enhancing the experience for students at all levels of mastery. Data collected from end-of-course surveys from the last five offerings of the course (between 2012 and 2014) show that students report high learning gains and feel that the course prepares them for solving quantitative and computational problems they will encounter in their research. We outline our course here which, together with the course materials freely available online under a Creative Commons License, should help to facilitate similar efforts by others.
Autores :
,Johanna L. Gutlerner;
Richard T. Born;
Michael Springer ;
Melanie I. Stefan;
Autor corporativo:
PLOS Computational Biology,
Fecha de publicación:
2015.
Paginas:
1.
ISBN:
1544-9173.
Idioma:
Inglés
Palabras claves:
Teaching Quantitative
Computing Skills
Campo de entrenamiento
Público objetivo:
Docentes
Investigadores
Educadores Medicos
Otros profesionales de la salud
Titulo Artículo:
The Quantitative Methods Boot Camp: Teaching Quantitative Thinking and Computing Skills to Graduate Students in the Life Sciences
Resumen:
The past decade has seen a rapid increase in the ability of biologists to collect large amounts of data. It is therefore vital that research biologists acquire the necessary skills during their training to visualize, analyze, and interpret such data. To begin to meet this need, we have developed a “boot camp” in quantitative methods for biology graduate students at Harvard Medical School. The goal of this short, intensive course is to enable students to use computational tools to visualize and analyze data, to strengthen their computational thinking skills, and to simulate and thus extend their intuition about the behavior of complex biological systems. The boot camp teaches basic programming using biological examples from statistics, image processing, and data analysis. This integrative approach to teaching programming and quantitative reasoning motivates students’ engagement by demonstrating the relevance of these skills to their work in life science laboratories. Students also have the opportunity to analyze their own data or explore a topic of interest in more detail. The class is taught with a mixture of short lectures, Socratic discussion, and in-class exercises. Students spend approximately 40% of their class time working through both short and long problems. A high instructor-to-student ratio allows students to get assistance or additional challenges when needed, thus enhancing the experience for students at all levels of mastery. Data collected from end-of-course surveys from the last five offerings of the course (between 2012 and 2014) show that students report high learning gains and feel that the course prepares them for solving quantitative and computational problems they will encounter in their research. We outline our course here which, together with the course materials freely available online under a Creative Commons License, should help to facilitate similar efforts by others.
Fecha de publicación:
2015.
Autor corporativo:
PLOS Computational Biology,
.
Idioma:
Inglés
Palabras claves:
Teaching Quantitative
Computing Skills
Campo de entrenamiento
Público objetivo:
Docentes
Investigadores
Educadores Medicos
Otros profesionales de la salud
Citar
Enviar por correo electrónico
Imprimir
Guardar
Consultar
INGRESE LOS SIGUIENTES DATOS
PARA ENVIAR EL CORREO
Sus nombres:
Sus apellidos:
Su correo electrónico:
Se necesita un valor.
Formato no válido.
Inscribirme al e-boletin de ASCOFAME
Correo electrónico destino:
Se necesita un valor.
Formato no válido.
Hola, encontré este documento en la biblioteca especializada en Educación Médica de ASCOFAME :,Johanna L. Gutlerner; The Quantitative Methods Boot Camp: Teaching Quantitative Thinking and Computing Skills to Graduate Students in the Life Sciences(2015). Podras consultarlo en el Siguiente link: https://ascofame.org.co/biblioteca/detalle_documento.php?id=1734
INGRESE LOS SIGUIENTES DATOS
PARA RESERVA EN SALA
Sus nombres:
Sus apellidos:
Correo electrónico:
Se necesita un valor.
Formato no válido.
Inscribirme al e-boletin de ASCOFAME
Programar la fecha de su visita:
Programar la hora de su visita:
7:00 AM
8:00 AM
9:00 AM
10:00 AM
11:00 AM
12:00 M
1:00 PM
2:00 PM
3:00 PM
¿Cómo citar este documento?
Seleccionar y copiar el texto.
,Johanna L. Gutlerner Richard T. Born Michael Springer Melanie I. Stefan ,Johanna L. Gutlerner Richard T. Born Michael Springer Melanie I. Stefan The Quantitative Methods Boot Camp: Teaching Quantitative Thinking and Computing Skills to Graduate Students in the Life Sciences. 2015; 11Ed. 1.
