Problem based learning in a Biostatistics course
Autor(a) principal: | |
---|---|
Data de Publicação: | 2019 |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10773/26967 |
Resumo: | We have introduced statistical problems, to be solved using the R software, into a Biostatistics course, in order to increase motivation for the field that requires a certain level of mathematical knowledge when most students are not always inspired for it. Our traditional class style used to be based only on slide presentations followed by pen and paper exercises with a calculator. Our aim was to complement this method with the use of software as a professional tool creating a active learning environment. Students came from Biology degree, Teaching of Geology and Biology degree and Marine Sciences degree. Each of the 200 students were presented with a total of four problems, during the semester, in the topics of Descriptive Statistics, Inference in One Variable, ANOVA and Simple Linear Regression. Students were requested to solve them at home and answer them in a form available in the “Moodle Inquiry” tool. Each student has his own different sample and also, questions were parameterized. For example, questions about Confidence Intervals were posed with different confidence levels (90%, 95% or 99%). Each students sees a different problem. Each of these has more than ten parameterized questions related to the same dataset exposed in the beginning of the text. Moodle doesn’t do this type of deliver different composed problems to each student so a small Python library was used to generate different problems and evaluate each individual student answer (numerical, textual or multiple choice types). To evaluate our methodology, we request students to “Share ideas, thoughts and constructive judgments about the Problems and also about the course” while students were working in the third Problem and also after the First Written Evaluation. The last and fourth Problem has been answered in class and students were requested to grade sentences in a five item Likert scale. Questions were about effort, time, help from other students and help from teacher. The analysis of answers suggest that the methodology of Problem Solving should be used again, with improvements, given the motivation and enthusiasm it promotes. |
id |
RCAP_901662bef96eb7def2991c2fb24ef06f |
---|---|
oai_identifier_str |
oai:ria.ua.pt:10773/26967 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Problem based learning in a Biostatistics courseProblem based learningStatisticsWe have introduced statistical problems, to be solved using the R software, into a Biostatistics course, in order to increase motivation for the field that requires a certain level of mathematical knowledge when most students are not always inspired for it. Our traditional class style used to be based only on slide presentations followed by pen and paper exercises with a calculator. Our aim was to complement this method with the use of software as a professional tool creating a active learning environment. Students came from Biology degree, Teaching of Geology and Biology degree and Marine Sciences degree. Each of the 200 students were presented with a total of four problems, during the semester, in the topics of Descriptive Statistics, Inference in One Variable, ANOVA and Simple Linear Regression. Students were requested to solve them at home and answer them in a form available in the “Moodle Inquiry” tool. Each student has his own different sample and also, questions were parameterized. For example, questions about Confidence Intervals were posed with different confidence levels (90%, 95% or 99%). Each students sees a different problem. Each of these has more than ten parameterized questions related to the same dataset exposed in the beginning of the text. Moodle doesn’t do this type of deliver different composed problems to each student so a small Python library was used to generate different problems and evaluate each individual student answer (numerical, textual or multiple choice types). To evaluate our methodology, we request students to “Share ideas, thoughts and constructive judgments about the Problems and also about the course” while students were working in the third Problem and also after the First Written Evaluation. The last and fourth Problem has been answered in class and students were requested to grade sentences in a five item Likert scale. Questions were about effort, time, help from other students and help from teacher. The analysis of answers suggest that the methodology of Problem Solving should be used again, with improvements, given the motivation and enthusiasm it promotes.IATED2019-11-15T18:14:22Z2019-01-01T00:00:00Z2019conference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10773/26967eng978-84-09-14755-72340-109510.21125/iceri.2019.2330Cruz, J. P.info: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:RCAAP2024-05-06T04:22:22Zoai:ria.ua.pt:10773/26967Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-05-06T04:22:22Repositório 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 |
Problem based learning in a Biostatistics course |
title |
Problem based learning in a Biostatistics course |
spellingShingle |
Problem based learning in a Biostatistics course Cruz, J. P. Problem based learning Statistics |
title_short |
Problem based learning in a Biostatistics course |
title_full |
Problem based learning in a Biostatistics course |
title_fullStr |
Problem based learning in a Biostatistics course |
title_full_unstemmed |
Problem based learning in a Biostatistics course |
title_sort |
Problem based learning in a Biostatistics course |
author |
Cruz, J. P. |
author_facet |
Cruz, J. P. |
author_role |
author |
dc.contributor.author.fl_str_mv |
Cruz, J. P. |
dc.subject.por.fl_str_mv |
Problem based learning Statistics |
topic |
Problem based learning Statistics |
description |
We have introduced statistical problems, to be solved using the R software, into a Biostatistics course, in order to increase motivation for the field that requires a certain level of mathematical knowledge when most students are not always inspired for it. Our traditional class style used to be based only on slide presentations followed by pen and paper exercises with a calculator. Our aim was to complement this method with the use of software as a professional tool creating a active learning environment. Students came from Biology degree, Teaching of Geology and Biology degree and Marine Sciences degree. Each of the 200 students were presented with a total of four problems, during the semester, in the topics of Descriptive Statistics, Inference in One Variable, ANOVA and Simple Linear Regression. Students were requested to solve them at home and answer them in a form available in the “Moodle Inquiry” tool. Each student has his own different sample and also, questions were parameterized. For example, questions about Confidence Intervals were posed with different confidence levels (90%, 95% or 99%). Each students sees a different problem. Each of these has more than ten parameterized questions related to the same dataset exposed in the beginning of the text. Moodle doesn’t do this type of deliver different composed problems to each student so a small Python library was used to generate different problems and evaluate each individual student answer (numerical, textual or multiple choice types). To evaluate our methodology, we request students to “Share ideas, thoughts and constructive judgments about the Problems and also about the course” while students were working in the third Problem and also after the First Written Evaluation. The last and fourth Problem has been answered in class and students were requested to grade sentences in a five item Likert scale. Questions were about effort, time, help from other students and help from teacher. The analysis of answers suggest that the methodology of Problem Solving should be used again, with improvements, given the motivation and enthusiasm it promotes. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-11-15T18:14:22Z 2019-01-01T00:00:00Z 2019 |
dc.type.driver.fl_str_mv |
conference object |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10773/26967 |
url |
http://hdl.handle.net/10773/26967 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
978-84-09-14755-7 2340-1095 10.21125/iceri.2019.2330 |
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.publisher.none.fl_str_mv |
IATED |
publisher.none.fl_str_mv |
IATED |
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 |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
mluisa.alvim@gmail.com |
_version_ |
1817543722684907520 |