Teaching and learning strategies in a biostatistics course during the pandemic: Perceptions of doctoral students

Main Article Content

Jaime Andrés Gaviria-Bedoya Gaviria-Bedoya
Dra
Dr

Abstract

The study analyzes how ten public health PhD students perceive the teaching strategies implemented in a biostatistics course during the COVID-19 pandemic. The teaching strategies implemented within the course through online meetings were reading reports, critical reading of research articles and analysis of real data using specialized and free software. The sources of information were open dialogues with students at the end of the course and written evaluations regarding methodological aspects. Each student assessed the course and analyzed their learning processes and perceptions. In general, students’ perceptions of time management, class agenda, reading reports, class-by-class reviews, critical reading, and using statistical software with real data were positive. Results are consistent with previous work about students’ perceptions, and these teaching strategies positively transform students’ perception of statistics.

Downloads

Download data is not yet available.

Article Details

How to Cite
Gaviria-Bedoya , J. A. G.-B., González-Gómez , D., & Villa-Ochoa , J. A. (2023). Teaching and learning strategies in a biostatistics course during the pandemic: Perceptions of doctoral students. Ensino Em Re-Vista, 30(Contínua), e040. https://doi.org/10.14393/ER-v30a2023-40
Section
DOSSIER 1 - Statistical Education: research and contemporary perspectives

References

AL SOUB, T. F.; ALSARAYREH, R. S.; AMARIN, N. Z. Students’ satisfaction with Using E -Learning to Learn Chemistry in Light of the COVID-19 Pandemic in Jordanian Universities. International Journal of Instruction, v. 14, n. 3, p. 1011–1024. 2021. DOI: http://doi.org/10.29333/iji.2021.14359a.

ANDRADE, L.; FERNÁNDEZ, F.; ÁLVAREZ, I. Panorama de la investigación en Educación Estadística desde tesis doctorales 2000-2014. TED: Tecné, Episteme y Didaxis, v. 14, n.41, p. 87–107. 2017. DOI: https://doi.org/10.17227/01203916.6039.

BAKKER, A.; WAGNER, D. Pandemic: lessons for today and tomorrow?. Educational Studies in Mathematics, v. 104, no 1, p. 1–4. 2020. DOI: https://doi.org/10.1007/s10649-020-09946-3.

BARGAGLIOTTI, A. et al. Pre-K–12 Guidelines for Assessment and Instruction in Statistics Education II (GAISE II): A Framework for Statistics and Data Science Education. Alexandria, USA: American Statistical Association, Acesso em: 2020. ISBN: 978-1-73422-351-4.

BATANERO, C. Treinta años de investigación en educación estocástica: Reflexiones y desafíos. In: ACTAS DEL TERCER CONGRESO INTERNACIONAL VIRTUAL DE EDUCACIÓN ESTOCÁSTICA [Congreso]. Acesso em. 2019. Disponível em: https://www.ugr.es/~fqm126/civeest/ponencias/batanero_ing.pdf.

BAWANEH, A. K. The Satisfaction Level Of Undergraduate Science Students Towards Using E-Learning And Virtual Classes In Exceptional Condition Covid-19 Crisis. Turkish Online Journal of Distance Education, v. 22, no 1, p. 52–65. 2021. DOI: https://doi.org/10.17718/TOJDE.849882.

BEN-ZVI, D.; GARFIELD, J. Statistical literacy, reasoning, and thinking: goals, definitions, and challenges. In: BEN-ZVI, D.; GARFIELD, J. The Challenge of Developing Statistical Literacy, Reasoning and Thinking. Dordrecht: Springer, 2004. p. 3–15.

BEN-ZVI, D.; MAKAR, K. The Teaching and Learning of Statistics: International Perspectives. In: BEN-ZVI, D.; MAKAR, K. (Orgs.). PROCEEDINGS OF THE THIRTHIENTH INTERNATIONAL CONGRESS ON MATHEMATICAL EDUCATION ICME-12. Springer, 2015. 334 p. DOI: https://doi.org/10.1007/978-3-319-23470-0.

BEN-ZVI, D.; MAKAR, K.; GARFIELD, J. International handbook of research in statistics education. Cham, Switzerland: Springer, 2018. DOI: https://doi.org/10.1007/978-3-319-66195-7.

BUDÉ, L. et al. The effect of directive tutor guidance in problem-based learning of statistics on students’ perceptions and achievement. Higher Education, v. 57, no 1, p. 23–36, 2009. DOI: https://doi.org/10.1007/s10734-008-9130-8.

CARVER, R. et al. Guidelines for assessment and instruction in statistics education: College report. Alexandria, USA, 2016. DOI: https://doi.org/10.3928/01484834-20140325-01.

CASTRO, W. F. et al. A Mathematics Education Research Agenda in Latin America Motivated by Coronavirus Pandemic. Eurasia Journal of Mathematics, Science and Technology Education, v. 16, no 12, em1919, 2020. DOI: https://doi.org/10.29333/ejmste/9277.

CHEN, X.; LEUNG, F. K. S.; SHE, J. Dimensions of students’ views of classroom teaching and attitudes towards mathematics: A multi-group analysis between genders based on structural equation models. Studies in Educational Evaluation, v. 78, p. 101289, 2023. DOI: https://doi.org/10.1016/j.stueduc.2023.101289.

CHIPHAMBO, S. M.; MTSI, N.; MASHOLOGU, M. Student’s perceptions on how high school mathematics should be taught: a south African perspective. Ponte International Scientific Researches Journal, v. 76, no 11, 2020. DOI:

http://dx.doi.org/10.21506/j.ponte.2020.11.5.

CRESWELL, J. Research Design: Qualitative, quantitative and mixed methods approaches. Londres: SAGE, 2014.

CROTTY, M. The Foundations of Social Research: Meaning and Perspective in the Research Process. Londres: SAGE, 1998.

DAVIES, C. Online seminars in statistics for doctoral students: A case study. Journal of University Teaching & Learning Practice, v. 18, no 2, p. 1-10, 2021. DOI: https://doi.org/10.53761/1.18.2.6.

DELMAS, R. A Comparison of Mathematical and Statistical Reasoning. In: BEN-ZVI, D.; GARFIELD, J. (Orgs.). The Challenge of Developing Statistical Literacy, Reasoning and Thinking. Dordrecht: Springer Netherlands, 2004. p. 79–95. DOI: https://doi.org/10.1007/1-4020-2278-6_4.

ENGELBRECHT, J. et al. Will 2020 be remembered as the year in which education was changed? ZDM - Mathematics Education, v. 52, no 5, p. 821–824, 2020. DOI: https://doi.org/10.1007/s11858-020-01185-3.

FIORAVANTI, R.; GRECA DUFRANC, I. M.; MENESES VILLAGRA, J. A. Caminos do ensino de estatística para a área da saúde. Revista Latinoamericana de Investigacion en Matematica Educativa, v. 22, no 1, p. 67–96, 2019. Disponible en http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S1665-24362019000100067&lng=es&nrm=iso. Accedido en 21 oct. 2023. Epub 23-Abr-2021.

GARFIELD, J. The challenge of developing statistical reasoning. Journal of Statistics Education, v. 10, no 3, 2002. DOI: https://doi.org/10.1080/10691898.2002.11910676.

GARFIELD, J.; BEN-ZVI, D.; CHANCE, B.; ROSETH, C. et al. Developing students’ statistical reasoning: Connecting research and teaching practice. Dordrecht: Springer, 2008. ISBN: 978-1-4020-8382-2.

GARFIELD, J.; BEN-ZVI, D.; CHANCE, B.; MEDINA, E. et al. The discipline of Statistics education. In: GARFIELD, J.; BEN (Orgs.). Developing Students’ Statistical Reasoning: Connecting Research and Teaching Practice. 2008. p. 1–408. ISBN: 978-1-4020-8382-2, DOI: https://doi.org/10.1007/978-1-4020-8383-9.

GARFIELD, J.; BEN-ZVI, D. How students learn statistics revisited: A current review of research on teaching and learning statistics. International Statistical Review, v. 75, no 3, p. 372–396, 2007. Disponible en https://onlinelibrary.wiley.com/. DOI: https://doi.org/10.1111/j.1751-5823.2007.00029.x.

GILLHAM, B. Case study: research methods. Londres: Continuum, 2000.

GRAVESTOCK, P.; GREGOR-GREENLEAF, E. Student Course Evaluations: Research, Models and Trends. Toronto: The Higher Education Quality Council of Ontario, 2008. Disponível em: https://teaching.pitt.edu/wp-content/uploads/2018/12/OMET-Student-Course-Evaluations.pdf.

GUNDLACH, E. et al. A comparison of student attitudes, statistical reasoning, performance, and perceptions for web-augmented traditional, fully online, and flipped sections of a statistical literacy class. Journal of Statistics Education, v. 23, no 1, p. 1–33, 2015. DOI: https://doi.org/10.1080/10691898.2015.11889723.

JONES, E.; PALMER, T. A review of group-based methods for teaching statistics in higher education. Cornell University Repository. 2020. p. 1–27. DOI: https://doi.org/10.1093/teamat/hrab002.

KOPARAN, T. Difficulties in learning and teaching statistics: teacher views. International Journal of Mathematical Education in Science and Technology, v. 46, no 1, p. 94–104, 2015. DOI: https://doi.org/10.1080/0020739X.2014.941425.

KOPARAN, T. Analysis of Teaching Materials Developed by Prospective Mathematics Teachers and Their Views on Material Development. Malaysian Online Journal of Educational Technology, v. 5, no 4, p. 14–34, 2017. Disponible en: https://mojet.net/index.php/mojet/article/view/111.

LANGE, N. DE; PILLAY, G.; CHIKOKO, V. Doctoral learning: A case for a cohort model of supervision and support. South African Journal of Education, v. 31, no 1, p. 15–30, 2011. DOI: https://doi.org/10.15700/saje.v31n1a413.

LAWTON, S.; TAYLOR, L. Student Perceptions of Engagement in an Introductory Statistics Course. Journal of Statistics Education, v. 28, no 1, p. 45–55, 2020. DOI: https://doi.org/10.1080/10691898.2019.1704201.

LEDER, G.; GROOTENBOER, P. Affect and mathematics education. Mathematics Education Research Journal, v. 17, no 2, p. 1–8, 2005.

LOVETT, M. A collaborative convergence on studying reasoning processes: A case study in statistics. En: KLAHR, D.; CARVER, S. (Orgs.). Cognition and Instruction: 25 Years of Progress, p. 347–384. 2001.

MADDEN, S. R. Exploring Secondary Teacher Statistical Learning: Professional Learning in a Blended Format Statistics and Modeling Course. En: BURRIL, GAIL; BEN-ZVI, D. (Org.). Topics and Trends in Current Statistics Education Research: International Perspectives. Cham, Switzerland, p. 265–282. 2019. DOI: https://doi.org/10.1007/978-3-030-03472-6_12.

MATHEMATICS TEACHER TRAINING SCHOLARSHIP. The Importance Of Maths In The Covid-19 Pandemic. 2020. Disponível em: http://teachingmathsscholars.org/newsandevents/covid-19pandemic. Acesso em: 27/abr./21.

MILES, M.; HUBERMAN, M.; SALDAÑA, J. Qualitative Data Analysis A Methods. Arizona State University: SAGE, 2014.

OCAÑA-RIOLA, R. The Use of Statistics in Health Sciences: Situation Analysis and Perspective. Statistics in Biosciences, v. 8, no 2, p. 204–219, 2016. DOI: https://doi.org/10.1007/s12561-015-9138-4.

PERALES, O. A. et al. High School Students’ Perceptions of 1:1 CSCL Environment in a Mathematics Classroom. Computers in the Schools, p. 1–21, 2023. DOI: https://doi.org/10.1080/07380569.2023.2233953.

PFANNKUCH, M. The role of context in developing informal statistical inferential reasoning: A classroom study. Mathematical Thinking and Learning, v. 13, no 1–2, p. 27–46, 2011. DOI: https://doi.org/10.1080/10986065.2011.538302.

POPPING, R. Analyzing Open-ended Questions by Means of Text Analysis Procedures. Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, v. 128, no 1, p. 23–39, 2015. DOI: https://doi.org/10.1177/0759106315597389.

ROJAS, M.; ZAPATA, J.; GRISALES, H. Síndrome de burnout y satisfacción laboral en docentes de una institución de educación superior, Medellín, 2008. Rev. Fac. Nac. Salud Pública, v. 27, no 2, p. 198–210, 2009.

SAHAI, H.; OJEDA, M. M. Teaching biostatistics to medical students and professionals: Problems and solutions. International Journal of Mathematical Education in Science and Technology, v. 30, no 2, p. 187–196, 1999. DOI: https://doi.org/10.1080/002073999287978.

SANTABÁRBARA, J.; LÓPEZ-ANTÓN, R. Actitudes hacia la estadística en residentes de medicina que cursan un posgrado de investigación. Revista de la Fundación Educación Médica, v. 22, no 2, p. 79, 2019. Disponible en http://scielo.isciii.es/scielo.php?script=sci_arttext&pid=S2014-98322019000200005&lng=es&nrm=iso. Accedido en 22 oct. 2023. DOI: https://dx.doi.org/10.33588/fem.222.987.

SCHUESSLER, J. H. " Chunking " Semester Projects : Does it Enhance Student Learning ?. Journal of Higher Education Theory and Practice, v. 17, no June, p. 115–120, 2017.

SHAUGHNESSY, M. Research on statistics learning and reasoning. In: LESTER, F. (Org.). Second handbook of research on mathematics teaching and learning. Charlotte, NC: NCTM, 2007. p. 957–1009.

SKJOTT LINNEBERG, M.; KORSGAARD, S. Coding qualitative data: a synthesis guiding the novice. Qualitative Research Journal, v. 19, no 3, p. 259–270, 2019. DOI: https://doi.org/10.1108/QRJ-12-2018-0012.

WISKER, G. et al. From Supervisory Dialogues to Successful PhDs: Strategies supporting and enabling the learning conversations of staff and students at postgraduate level. Teaching in Higher Education, v. 8, no 3, p. 383–397, 2003. DOI: https://doi.org/10.1080/13562510309400.

ZHANG, Y. et al. Attitudes toward statistics in medical postgraduates: Measuring, evaluating and monitoring. BMC Medical Education, v. 12, no 1, 2012. DOI: https://doi.org/10.1186/1472-6920-12-117.

ZHOU, Y. Blended Teaching for Research Methods and Statistics Courses. PEOPLE: International Journal of Social Sciences, v. 3, no 3, p. 1275–1283, 2018. Disponível em: https://grdspublishing.org/index.php/people/article/view/1235. Acesso em: 21 oct. 2023. DOI: https://doi.org/10.20319/pijss.2018.33.12751283.

ZIEFFLER, A. et al. What Does Research Suggest About the Teaching and Learning of Introductory Statistics at the College Level? A Review of the Literature. Journal of Statistics Education, v. 16, no 2, p. 26, 2008. DOI: https://doi.org/10.1080/10691898.2008.11889566.