Publications by Chris Elvin
A corpus study of a full year of one Japanese university class's academic listening assignments
Comment: The corpus consists of weekly classwork and homework assignments set in the academic year 2020 for twenty-three sophomore students of a Japanese university. Set the location of the working directory. Load libraries into R. library(tidyverse) library(readtext) library(quanteda) library(quanteda.textstats) Read the homework assignments ...
3480 sym R (14401 sym/39 pcs)
Whole Class Feedback Script Example I - Academic Listening
Load Libraries library(tidyverse) ## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ── ## ✓ ggplot2 3.3.3 ✓ purrr 0.3.4 ## ✓ tibble 3.1.1 ✓ dplyr 1.0.6 ## ✓ tidyr 1.1.3 ✓ stringr 1.4.0 ## ✓ readr ...
752 sym R (73974 sym/32 pcs) 2 img
Whole Class Feedback Script Example IV - Presentation
library(quanteda) library(quanteda.textstats) library(readtext) library(tidyverse) library(lubridate) x <- list.files() %>% readtext %>% corpus Some Common Words x %>% tokens() %>% dfm(remove_punct=T) %>% dfm_remove(stopwords("en")) %>% textstat_frequency()%>% filter(frequency>5) %>% summarise(word = feature, frequency) word...
257 sym R (25393 sym/16 pcs) 2 img
Whole Class Feedback Script Example II - Writing
Load libraries. library(readtext) library(tidyverse) library(quanteda) library(quanteda.textstats) Create corpus of students’ essays. x <- list.files(pattern = "docx") %>% readtext(ignore_missing_files = T) %>% corpus() Common Words x %>% dfm(remove_punct=T, remove_numbers=T, remove=stopwords("en")) %>% textstat_freque...
348 sym R (15015 sym/19 pcs) 1 img
Whole Class Feedback Script Example III - Grammar
Load libraries. library(tidyverse) library(quanteda) require(quanteda.textstats) library(readtext) Build a corpus of the texts. x <- list.files(pattern = "(pdf|docx)$") %>% readtext(ignore_missing_files = T) %>% texts What regular past tense verbs did you use? x <- tolower(x) kwic(x, phrase("*ed$"), window=10) %>% summarise(keyword) %>% dist...
363 sym R (27425 sym/15 pcs) 1 img
Whole Class Feedback Script Example V - Graded Reader Book Report
Load libraries. library(readtext) library(tidyverse) library(quanteda) library(quanteda.textstats) Build a corpus of the students’ book reports. x <- list.files() %>% readtext %>% corpus Check the format of the in-text citations with the students. kwic(x, pattern = phrase("\\( . , \\d{4} \\)"), valuetype="regex") %>% summarise(intext_c...
527 sym R (20194 sym/21 pcs) 2 img
Whole Class Feedback Script Example VI - Discussion
library(tidyverse) library(lubridate) Read files into R. feedback <- read.csv("feedback.csv") today <- read.csv('today.csv') Plot boxplots. feedback <- feedback %>% filter(Timestamp == as_date("2021-06-17")) feedback %>% ggplot(aes(x=Who.was.your.discussion.leader., y=Score)) + geom_boxplot() + theme(axis.title.x = element_blank(), ...
283 sym R (8060 sym/17 pcs) 1 img
Calibration of EFL Learners' Summaries Against a Standard Similarity Scale
Load libraries. library(tidyverse) library(readtext) library(quanteda) library(quanteda.textstats) library(caTools) Build a corpus of the texts. x <- list.files(pattern = "html", recursive = T) %>% readtext(ignore_missing_files = T) %>% texts %>% corpus Extract family and given names from doc names. family_names <- docnames(x) %>% word(2) fa...
7773 sym R (66346 sym/137 pcs) 10 img
Calibration of EFL Learners' Summaries Against a Standard Similarity Scale
Load libraries. library(tidyverse) library(readtext) library(quanteda) library(quanteda.textstats) library(caTools) Build a corpus of the texts. x <- list.files(pattern = "html", recursive = T) %>% readtext(ignore_missing_files = T) %>% texts %>% corpus Extract family and given names from doc names. family_names <- docnames(x) %>% word(2) fa...
7773 sym R (66346 sym/137 pcs) 10 img
Fantasy Premier League - Free Hit Team Selection Using Linear Optimization
How can linear optimization be used to select a points-rich fantasy premier league staring eleven given a fixed budget of current squad value? First, choose a team formation and extract the cheapest bench possible. (This can be done manually as well, of course). Then run linear optimization to find the eleven players with the most points this s...
1550 sym R (4297 sym/31 pcs)