Learning biophysics by building models: is it possible?
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.21/8562 |
Resumo: | The curricula of higher education courses in the area of Health usually place the curricular units of Basic Sciences in the first years of the course. This knowledge, supposedly, is ‘stored’ by the students in order to be applied in later curricular units. One of the major disadvantages of this structure is that knowledge and skills will have to be acquired in the long term. In this way, it is necessary to use teaching methodologies that guarantee retention of the acquired knowledge in the long term, so that students take the knowledge as if it were their own so that it can be correlated with the new knowledge. But on the other side, this kind of structure is not very well accepted by the students because the importance of the learning the fundamentals sciences is not immediately understood by them. This implies that the motivation for this kind of basic science disciplines is very low. The building of numerical models of biophysical phenomena, such as the mechanics of breathing, or blood circulation, has the potential for student motivation as well as long-term learning. Our theory is that by building well known numerical models of physiological phenomena in a spreadsheet, students have the opportunity to change their perceptions about the relevance of the contents addressed, simultaneously improving their learning in the topics covered and increasing their motivation in the discipline. The option for the use of a spreadsheet is justified because it does not require prior knowledge of programming languages, or about complex mathematical software, which would an obstacle to the biophysics learning. There is also the side effect of learning how to use a spreadsheet that is a plus in itself. After the development time of the model, the students have an individual oral assessment, which includes a final assessment of the developed model. Following this, the student delivers a written report. It is in this report that the students show the tests they have done to the model, as well as a reflection on the model they used, its limitations, some possible applications, and some considerations about possible future developments. It is intended to recognize the challenges that students face when building the models, and also know the evolution of the learning and to know the students' perception about the importance of the construction of models in biophysics and in the learning of biophysics. At this moment we have done already two complete cycles. At the end of each cycle, there is an evaluation which is used to develop the next cycle, the third one at this moment. In the very near future, we will try to apply this learning methodology to other disciplines, using different models according to each discipline. In this way, we would be able to compare results of different implementations of this new learning methodology. |
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Learning biophysics by building models: is it possible?PhysicsModel based learningSpreadsheetBiophysicsThe curricula of higher education courses in the area of Health usually place the curricular units of Basic Sciences in the first years of the course. This knowledge, supposedly, is ‘stored’ by the students in order to be applied in later curricular units. One of the major disadvantages of this structure is that knowledge and skills will have to be acquired in the long term. In this way, it is necessary to use teaching methodologies that guarantee retention of the acquired knowledge in the long term, so that students take the knowledge as if it were their own so that it can be correlated with the new knowledge. But on the other side, this kind of structure is not very well accepted by the students because the importance of the learning the fundamentals sciences is not immediately understood by them. This implies that the motivation for this kind of basic science disciplines is very low. The building of numerical models of biophysical phenomena, such as the mechanics of breathing, or blood circulation, has the potential for student motivation as well as long-term learning. Our theory is that by building well known numerical models of physiological phenomena in a spreadsheet, students have the opportunity to change their perceptions about the relevance of the contents addressed, simultaneously improving their learning in the topics covered and increasing their motivation in the discipline. The option for the use of a spreadsheet is justified because it does not require prior knowledge of programming languages, or about complex mathematical software, which would an obstacle to the biophysics learning. There is also the side effect of learning how to use a spreadsheet that is a plus in itself. After the development time of the model, the students have an individual oral assessment, which includes a final assessment of the developed model. Following this, the student delivers a written report. It is in this report that the students show the tests they have done to the model, as well as a reflection on the model they used, its limitations, some possible applications, and some considerations about possible future developments. It is intended to recognize the challenges that students face when building the models, and also know the evolution of the learning and to know the students' perception about the importance of the construction of models in biophysics and in the learning of biophysics. At this moment we have done already two complete cycles. At the end of each cycle, there is an evaluation which is used to develop the next cycle, the third one at this moment. In the very near future, we will try to apply this learning methodology to other disciplines, using different models according to each discipline. In this way, we would be able to compare results of different implementations of this new learning methodology.RCIPLMachado, NunoBaptista, Mónica2018-06-05T11:49:47Z2017-112017-11-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.21/8562engMachado N, Baptista M. Learning biophysics by building models: is it possible? In: ICERI2017 Proceedings Papers – 10th Annual International Conference of Education, Research and Innovation. Seville (Spain), November 16-18, 2017. p. 6286-91.978-84-697-6957-710.21125/iceri.2017.1627info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-08-03T09:56:08Zoai:repositorio.ipl.pt:10400.21/8562Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:17:18.270950Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Learning biophysics by building models: is it possible? |
title |
Learning biophysics by building models: is it possible? |
spellingShingle |
Learning biophysics by building models: is it possible? Machado, Nuno Physics Model based learning Spreadsheet Biophysics |
title_short |
Learning biophysics by building models: is it possible? |
title_full |
Learning biophysics by building models: is it possible? |
title_fullStr |
Learning biophysics by building models: is it possible? |
title_full_unstemmed |
Learning biophysics by building models: is it possible? |
title_sort |
Learning biophysics by building models: is it possible? |
author |
Machado, Nuno |
author_facet |
Machado, Nuno Baptista, Mónica |
author_role |
author |
author2 |
Baptista, Mónica |
author2_role |
author |
dc.contributor.none.fl_str_mv |
RCIPL |
dc.contributor.author.fl_str_mv |
Machado, Nuno Baptista, Mónica |
dc.subject.por.fl_str_mv |
Physics Model based learning Spreadsheet Biophysics |
topic |
Physics Model based learning Spreadsheet Biophysics |
description |
The curricula of higher education courses in the area of Health usually place the curricular units of Basic Sciences in the first years of the course. This knowledge, supposedly, is ‘stored’ by the students in order to be applied in later curricular units. One of the major disadvantages of this structure is that knowledge and skills will have to be acquired in the long term. In this way, it is necessary to use teaching methodologies that guarantee retention of the acquired knowledge in the long term, so that students take the knowledge as if it were their own so that it can be correlated with the new knowledge. But on the other side, this kind of structure is not very well accepted by the students because the importance of the learning the fundamentals sciences is not immediately understood by them. This implies that the motivation for this kind of basic science disciplines is very low. The building of numerical models of biophysical phenomena, such as the mechanics of breathing, or blood circulation, has the potential for student motivation as well as long-term learning. Our theory is that by building well known numerical models of physiological phenomena in a spreadsheet, students have the opportunity to change their perceptions about the relevance of the contents addressed, simultaneously improving their learning in the topics covered and increasing their motivation in the discipline. The option for the use of a spreadsheet is justified because it does not require prior knowledge of programming languages, or about complex mathematical software, which would an obstacle to the biophysics learning. There is also the side effect of learning how to use a spreadsheet that is a plus in itself. After the development time of the model, the students have an individual oral assessment, which includes a final assessment of the developed model. Following this, the student delivers a written report. It is in this report that the students show the tests they have done to the model, as well as a reflection on the model they used, its limitations, some possible applications, and some considerations about possible future developments. It is intended to recognize the challenges that students face when building the models, and also know the evolution of the learning and to know the students' perception about the importance of the construction of models in biophysics and in the learning of biophysics. At this moment we have done already two complete cycles. At the end of each cycle, there is an evaluation which is used to develop the next cycle, the third one at this moment. In the very near future, we will try to apply this learning methodology to other disciplines, using different models according to each discipline. In this way, we would be able to compare results of different implementations of this new learning methodology. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-11 2017-11-01T00:00:00Z 2018-06-05T11:49:47Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.21/8562 |
url |
http://hdl.handle.net/10400.21/8562 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Machado N, Baptista M. Learning biophysics by building models: is it possible? In: ICERI2017 Proceedings Papers – 10th Annual International Conference of Education, Research and Innovation. Seville (Spain), November 16-18, 2017. p. 6286-91. 978-84-697-6957-7 10.21125/iceri.2017.1627 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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