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Content from Introduction

Last updated on 2026-04-22 | Edit this page

Overview

Questions

  • Why might a paper be retracted?
  • How do paper retractions relate to integrity?
  • What do we mean by research integrity?

Objectives

  • Describe factors contributing to paper retractions
  • Describe components of research integrity
  • Explain how lack of integrity could lead to a paper retraction

Risks of retraction

Episode content goes here…

Pre-activity: The MMR vaccine retratction -> why was it retracted, and the ongoing impact of that research. What were the key issues, and how it relates to journal guidance.

Challenge

What are the risks?

Which of the following could result in a paper being retracted?

  1. Hallucinated citations
  2. Conflict of interest
  3. Falsified data
  4. Misleading conclusions

All of these problems could/should require the paper to be retracted.

Research Integrity

Episode content goes here..

Pre activity: Have learners explore the UKRIO guidance or the EU guidelines

Discussion

Tell Your neighbour: What does research integrity mean to you?

  1. Spend 2 minutes thinking about what research integrity means to you
  2. Share your understanding of research integrity with your neighbour
  3. Was anything different, or unexpected in their understanding?

Integrity and retractions

Preactivity: revisit MMR example, what were the integrity issues. Do they overlap with retraction scenarios

Discussion

Minute Paper: Integrity and retractions

Write for 1 minute on the topic of how a lack of integrity could lead to a paper retraction.

Key Points
  • Papers may be retracted by an author or the journal’s editorial team.
  • Integrity concerns may be a factor in retraction.
  • There are multiple dimensions to integrity.

Content from Rigour

Last updated on 2026-04-22 | Edit this page

Overview

Questions

  • How do you write a lesson using Markdown and sandpaper?

Objectives

  • describe how rigour could help avoid paper retraction
  • Awareness of reproducibility concerns re: genAI outputs
  • awareness of limitations of explainable AI
  • awareness of business models and how these impact behaviours
  • describe how genAI use can impact disciplinary norms

What is rigour

Pre-learning: what are the things that influence rigour, what does it mean in the research process. this could include pre-registration.

Discussion

Describe how rigour could help avoid paper retraction

Read:

  • what were the issues,
  • what were the rigour components that contributed to retraction

Explainable AI

Definition of explainable AI: ….

Defintion of open source AI ….

Discussion

Think, Pair, Share

Read the definition of open source AI.

How much does it reduce blackbox and aid explainability?

Spend 2 minutes thinking about your response.

Take it in turns to share your thoughts with your neighbours.

The need for explainability

Pre-learning: introduce concept of attention economy, and how this relates to follow-up questions. Relate to pre-registration concept

Challenge

Challenge: Task review

Read the aim of the task:

Read the chat transcript:

Answer the questions:

  • the prepared plan was adhered to
  • if the original objective was met
Key Points
  • Use .md files for episodes when you want static content
  • Use .Rmd files for episodes when you need to generate output
  • Run sandpaper::check_lesson() to identify any issues with your lesson
  • Run sandpaper::build_lesson() to preview your lesson locally

Content from Using Markdown

Last updated on 2026-02-05 | Edit this page

Overview

Questions

  • How do you write a lesson using Markdown and sandpaper?

Objectives

  • Explain how to use markdown with The Carpentries Workbench
  • Demonstrate how to include pieces of code, figures, and nested challenge blocks

Introduction

This is a lesson created via The Carpentries Workbench. It is written in Pandoc-flavored Markdown for static files and R Markdown for dynamic files that can render code into output. Please refer to the Introduction to The Carpentries Workbench for full documentation.

What you need to know is that there are three sections required for a valid Carpentries lesson:

  1. questions are displayed at the beginning of the episode to prime the learner for the content.
  2. objectives are the learning objectives for an episode displayed with the questions.
  3. keypoints are displayed at the end of the episode to reinforce the objectives.
Challenge

Challenge 1: Can you do it?

What is the output of this command?

R 

paste("This", "new", "lesson", "looks", "good")

OUTPUT 

[1] "This new lesson looks good"
Challenge

Challenge 2: how do you nest solutions within challenge blocks?

You can add a line with at least three colons and a solution tag.

Figures

You can use standard markdown for static figures with the following syntax:

![optional caption that appears below the figure](figure url){alt='alt text for accessibility purposes'}

Blue Carpentries hex person logo with no text.
You belong in The Carpentries!
Callout

Callout sections can highlight information.

They are sometimes used to emphasise particularly important points but are also used in some lessons to present “asides”: content that is not central to the narrative of the lesson, e.g. by providing the answer to a commonly-asked question.

Math

One of our episodes contains \(\LaTeX\) equations when describing how to create dynamic reports with {knitr}, so we now use mathjax to describe this:

$\alpha = \dfrac{1}{(1 - \beta)^2}$ becomes: \(\alpha = \dfrac{1}{(1 - \beta)^2}\)

Cool, right?

Key Points
  • Use .md files for episodes when you want static content
  • Use .Rmd files for episodes when you need to generate output
  • Run sandpaper::check_lesson() to identify any issues with your lesson
  • Run sandpaper::build_lesson() to preview your lesson locally

Content from Respect and Accountability

Last updated on 2026-02-05 | Edit this page

Overview

Questions

  • How do you write a lesson using Markdown and sandpaper?

Objectives

  • Describe key environmental concerns relating to GenAI and machine learning
  • State key issues relating to data workers and workers rights
  • Awareness of embedded values in the tools
  • Describe current legal and ethical debates relating to data acquisition for training

Introduction

This is a lesson created via The Carpentries Workbench. It is written in Pandoc-flavored Markdown for static files and R Markdown for dynamic files that can render code into output. Please refer to the Introduction to The Carpentries Workbench for full documentation.

What you need to know is that there are three sections required for a valid Carpentries lesson:

  1. questions are displayed at the beginning of the episode to prime the learner for the content.
  2. objectives are the learning objectives for an episode displayed with the questions.
  3. keypoints are displayed at the end of the episode to reinforce the objectives.
Challenge

Challenge 1: Can you do it?

What is the output of this command?

R 

paste("This", "new", "lesson", "looks", "good")

OUTPUT 

[1] "This new lesson looks good"
Challenge

Challenge 2: how do you nest solutions within challenge blocks?

You can add a line with at least three colons and a solution tag.

Figures

You can use standard markdown for static figures with the following syntax:

![optional caption that appears below the figure](figure url){alt='alt text for accessibility purposes'}

Blue Carpentries hex person logo with no text.
You belong in The Carpentries!
Callout

Callout sections can highlight information.

They are sometimes used to emphasise particularly important points but are also used in some lessons to present “asides”: content that is not central to the narrative of the lesson, e.g. by providing the answer to a commonly-asked question.

Math

One of our episodes contains \(\LaTeX\) equations when describing how to create dynamic reports with {knitr}, so we now use mathjax to describe this:

$\alpha = \dfrac{1}{(1 - \beta)^2}$ becomes: \(\alpha = \dfrac{1}{(1 - \beta)^2}\)

Cool, right?

Key Points
  • Use .md files for episodes when you want static content
  • Use .Rmd files for episodes when you need to generate output
  • Run sandpaper::check_lesson() to identify any issues with your lesson
  • Run sandpaper::build_lesson() to preview your lesson locally

Content from Transparency

Last updated on 2026-02-05 | Edit this page

Overview

Questions

  • How do you write a lesson using Markdown and sandpaper?

Objectives

  • Awareness of different journal approached to GenAI
  • Describe reputational impact resulting from lack of transparency around use
  • Awareness of differing legislation around IP and copyright relating to GenAI outputs

Introduction

This is a lesson created via The Carpentries Workbench. It is written in Pandoc-flavored Markdown for static files and R Markdown for dynamic files that can render code into output. Please refer to the Introduction to The Carpentries Workbench for full documentation.

What you need to know is that there are three sections required for a valid Carpentries lesson:

  1. questions are displayed at the beginning of the episode to prime the learner for the content.
  2. objectives are the learning objectives for an episode displayed with the questions.
  3. keypoints are displayed at the end of the episode to reinforce the objectives.
Challenge

Challenge 1: Can you do it?

What is the output of this command?

R 

paste("This", "new", "lesson", "looks", "good")

OUTPUT 

[1] "This new lesson looks good"
Challenge

Challenge 2: how do you nest solutions within challenge blocks?

You can add a line with at least three colons and a solution tag.

Figures

You can use standard markdown for static figures with the following syntax:

![optional caption that appears below the figure](figure url){alt='alt text for accessibility purposes'}

Blue Carpentries hex person logo with no text.
You belong in The Carpentries!
Callout

Callout sections can highlight information.

They are sometimes used to emphasise particularly important points but are also used in some lessons to present “asides”: content that is not central to the narrative of the lesson, e.g. by providing the answer to a commonly-asked question.

Math

One of our episodes contains \(\LaTeX\) equations when describing how to create dynamic reports with {knitr}, so we now use mathjax to describe this:

$\alpha = \dfrac{1}{(1 - \beta)^2}$ becomes: \(\alpha = \dfrac{1}{(1 - \beta)^2}\)

Cool, right?

Key Points
  • Use .md files for episodes when you want static content
  • Use .Rmd files for episodes when you need to generate output
  • Run sandpaper::check_lesson() to identify any issues with your lesson
  • Run sandpaper::build_lesson() to preview your lesson locally