20 Peer Review Writing

TODAY’S GOALS

Practice giving and getting feedback on writing

Refine your data story through the revision process

For more on this topic

Read:

Communicating with Data (Nolan and Stoudt)

WHERE ARE WE?!? Data Storytelling

Data Storytelling is the process of creating a narrative around a dataset. This narrative can be used to inform, persuade, or entertain. It is a way to communicate the insights we’ve gained from our data to others.

20.1 Warm-up

20.2 Exercises

Share your Google Doc file with them (give them editing privileges).

20.2.1 Exercise 1 - READ

Read through the entire document first without stopping to comment to get a sense of the story and the goal of the writing.

20.2.2 Exercise 2 - FEEDBACK

Go back to the top of the document and re-read sections as they relate to the content/structure below. Give feedback (see the ACTION comments).

20.2.2.1 Part a

Introduction: Read just the title/headline and the first sentence. Do they hook you? Do you want to keep reading? Why or why not?

ACTION: Add a comment in the document giving constructive feedback on the first sentence and title (e.g. what is working well, what might be changed to improve it).

20.2.2.2 Part b

Background/Context: Do the introductory paragraphs provide a sense of motivation (why is this important or worth considering)? Do they give a sense of the larger problem that will be addressed?

ACTION: Add a comment in the document giving constructive feedback on the background/context (e.g. what is working well, what might be changed to improve it).

20.2.2.3 Part c

Story: What is the story? Locate it in the rough draft: is it clearly stated? Help the author decide if it is too broad, too narrow, or just right. Work on rewording if necessary.

ACTION: Add a comment in the document giving constructive feedback on the story (e.g. what is clear, what might be changed to improve it).

20.2.2.4 Part d

Sentences: Read the rest of the piece, paying close attention to each sentence and to the flow of one sentence into the next. Are there mistakes in grammar, usage, spelling, or typing?

ACTION: Mark them on the draft with a comment or change to “giving suggestions” mode.

Do the sentences flow nicely, or do some of them feel as if they need reworking?

ACTION: Choose two sentences that you feel may need work, highlight them on the rough draft, and add a comment to make suggestions for possible revisions.

20.2.2.5 Part e

Evidence: Is there adequate evidence in the piece to support the author’s argument? Are there too many digits? Does the author leave out any evidence that seems particularly obvious or helpful to you? Glance through the data operations. Do the numbers and conclusions drawn by the author appear appropriate? Can you spot any obvious mistakes? In particular, pay attention to the “compared to what” problem– is the author comparing apples to apples?

ACTION: Add a comment in the document giving constructive feedback on the numerical evidence (e.g. what is working well, what might be changed to improve it).

20.2.3 Exercise 2 - DISCUSS

Once everyone has read through the documents and given written feedback. Discuss as a group.

Focus on lifting up the effective aspects of their writing and sharing ideas of how to make it a more interesting and effective story.

# Peer Review Writing ```{r setup, echo = FALSE, warning = FALSE} knitr::opts_chunk$set(collapse = TRUE, warning = FALSE, message = FALSE, fig.height = 2.75, fig.width = 4.25, fig.env='figure', fig.pos = 'h', fig.align = 'center') ``` ```{r, echo=FALSE, results="hide", warning=FALSE, message=FALSE} # Load packages library(tidyverse) library(tint) library(mosaic) question_num <- 0 NextQ <- function() { question_num <<- question_num + 1 return (question_num) } library(conflicted) conflict_prefer("rename", winner = "dplyr") conflict_prefer("filter", winner = "dplyr") conflict_prefer("smiths", winner = "tidyr") conflict_prefer("melt", winner = "reshape2") conflict_prefer("count", winner = "dplyr") conflict_prefer("group_by", winner = "dplyr") conflicts_prefer(ggthemes::theme_map) conflicts_prefer(base::sum) conflicts_prefer(base::min) conflicts_prefer(base::max) conflicts_prefer(base::mean) ``` <div class='content-hidden'> **SETTLING IN** Sit with someone else in the class that is not in your project group (you can have a group of 3, if we have an odd number). Introduce yourself. Just share what's at the top of mind today. \ \ \ \ \ \ \ \ </div> > **TODAY'S GOALS** > > - Practice giving and getting feedback on writing > - Refine your data story through the revision process \ \ \ \ > **For more on this topic** > > Read: > > - [Communicating with Data](https://global.oup.com/academic/product/communicating-with-data-9780198862758?cc=us&lang=en&) (Nolan and Stoudt) \ \ \ \ **WHERE ARE WE?!? Data Storytelling** - **Data Storytelling** is the process of creating a narrative around a dataset. This narrative can be used to inform, persuade, or entertain. It is a way to communicate the insights we've gained from our data to others. \ \ \ \ ## Warm-up ## Exercises Share your Google Doc file with them (give them editing privileges). ### Exercise 1 - READ Read through the entire document first without stopping to comment to get a sense of the story and the goal of the writing. ### Exercise 2 - FEEDBACK Go back to the top of the document and re-read sections as they relate to the content/structure below. Give feedback (see the ACTION comments). #### Part a Introduction: Read just the title/headline and the first sentence. Do they hook you? Do you want to keep reading? Why or why not? > ACTION: Add a comment in the document giving constructive feedback on the first sentence and title (e.g. what is working well, what might be changed to improve it). #### Part b Background/Context: Do the introductory paragraphs provide a sense of motivation (why is this important or worth considering)? Do they give a sense of the larger problem that will be addressed? > ACTION: Add a comment in the document giving constructive feedback on the background/context (e.g. what is working well, what might be changed to improve it). #### Part c Story: What is the story? Locate it in the rough draft: is it clearly stated? Help the author decide if it is too broad, too narrow, or just right. Work on rewording if necessary. > ACTION: Add a comment in the document giving constructive feedback on the story (e.g. what is clear, what might be changed to improve it). #### Part d Sentences: Read the rest of the piece, paying close attention to each sentence and to the flow of one sentence into the next. Are there mistakes in grammar, usage, spelling, or typing? > ACTION: Mark them on the draft with a comment or change to "giving suggestions" mode. Do the sentences flow nicely, or do some of them feel as if they need reworking? > ACTION: Choose two sentences that you feel may need work, highlight them on the rough draft, and add a comment to make suggestions for possible revisions. #### Part e Evidence: Is there adequate evidence in the piece to support the author’s argument? Are there too many digits? Does the author leave out any evidence that seems particularly obvious or helpful to you? Glance through the data operations. Do the numbers and conclusions drawn by the author appear appropriate? Can you spot any obvious mistakes? In particular, pay attention to the “compared to what” problem– is the author comparing apples to apples? > ACTION: Add a comment in the document giving constructive feedback on the numerical evidence (e.g. what is working well, what might be changed to improve it). ### Exercise 2 - DISCUSS Once everyone has read through the documents and given written feedback. Discuss as a group. Focus on lifting up the effective aspects of their writing and sharing ideas of how to make it a more interesting and effective story. \ \ \ \ <div class='content-hidden'> ## Wrap-up - Upcoming due dates </div>