Efficient empiricism: Streamlining teaching, research, and learning in empirical courses

Dvořák, Tomáš; Halliday, Simon; O’Hara, Michael; Swoboda, Aaron

doi:10.1080/00220485.2019.1618765

Cited by 11 publications

(4 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Outside classes, students can get together to help each other in solving the problems or contact their teachers. 4. After all answers in the worksheet have been fulfilled, each student uses Moodle Inquiry Tool to collect and provide answers for evaluation.…”

Section: Methodsmentioning

confidence: 99%

“…The software chosen to reshape the PBL approach was using the R language and system [2] and RStudio [3] as a powerful environment: while, as said, "R is a language and environment for statistical computing and graphics", RStudio is an open-source integrated development environment (IDE) for R with reporting capabilities, that were used in by students, and many other tools for professional statisticians and data analysts. RMarkdown [4] is an utility of RStudio to produce documents that are fully reproducible and is a form of 'literate programming' because it is easier for humans to read and understand (Knuth, 1984). It allows putting together text and code to produce reports without leaving the tool (avoiding exports and copy/paste to other tools).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Problem Based Learning in a Biostatistics Course

Cruz¹

2019

ICERI Proceedings

View full text Add to dashboard Cite

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.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Problem Based Learning in a Biostatistics Course

Cruz¹

2019

ICERI Proceedings

View full text Add to dashboard Cite

show abstract

“…Our course had no prerequisites, so we assumed no prior knowledge of the free and open source R programming language among the students and were prepared to teach them as complete novices. We chose R (R Core Team 2019) because it is widely used by archaeologists (Schmidt and Marwick 2019), and also commonly taught in undergraduate classes in social sciences and statistics (Baumer et al 2014; Cetinkaya-Rundel and Rundel 2018; Dvorak et al 2019). We were also prepared for students to have no prior experience with replication assignments.…”

Section: How To Conduct a Replication Assignment In Archaeologymentioning

confidence: 99%

How to Use Replication Assignments for Teaching Integrity in Empirical Archaeology

Marwick

Wang

Robinson

et al. 2019

Adv. archaeol. pract.

View full text Add to dashboard Cite

The value of new archaeological knowledge is strongly determined by how credible it is, and a key measure of scientific credibility is how replicable new results are. However, few archaeologists learn the skills necessary to conduct replication as part of their training. This means there is a gap between the ideals of archaeological science and the skills we teach future researchers. Here we argue for replications as a core type of class assignment in archaeology courses to close this gap and establish a culture of replication and reproducibility. We review replication assignments in other fields and describe how to implement a replication assignment suitable for many types of archaeology programs. We describe our experience with replication in an upper-level undergraduate class on stone artifact analysis. Replication assignments can help archaeology programs give students the skills that enable transparent and reproducible research.

show abstract

“…First, as scholars, the literature extensively focuses on the adoption of reproducible workflows in research including the American Statistical Associations' reproducible research recommendations (Broman et al 2017). Second, for teachers, the literature focuses on teaching reproducible practices including literate programming (Baumer et al 2014, Dvorak et al 2019, documentation (Ball & Medeiros 2012), version control (Fiksel et al 2019, Beckman et al 2021, and open science practices (Toelch & Ostwald 2018). In this paper, we propose a third dimension to reproducibility practices for teacher-scholars and consider reproducible teaching practices.…”

Section: Introductionmentioning

confidence: 99%

Tools and Recommendations for Reproducible Teaching

Dogucu¹,

Çetinkaya-Rundel²

2022

Preprint

View full text Add to dashboard Cite

It is recommended that teacher-scholars of data science adopt reproducible workflows in their research as scholars and teach reproducible workflows to their students. In this paper, we propose a third dimension to reproducibility practices and recommend that regardless of whether they teach reproducibility in their courses or not, data science instructors adopt reproducible workflows for their own teaching. We consider computational reproducibility, documentation, and openness as three pillars of reproducible teaching framework. We share tools, examples, and recommendations for the three pillars.

show abstract

Efficient empiricism: Streamlining teaching, research, and learning in empirical courses

Cited by 11 publications

References 23 publications

Problem Based Learning in a Biostatistics Course

Problem Based Learning in a Biostatistics Course

How to Use Replication Assignments for Teaching Integrity in Empirical Archaeology

Tools and Recommendations for Reproducible Teaching

Contact Info

Product

Resources

About