Last update: 2025-01-03
This is the space where I put together my notes and shared ideas about technology, education, and research.
Getting started with academic writing in R Markdown is a quick start guide for researchers who want to spend their time on writing the manuscript rather than formatting and citations.
R is a popular choice for data science and research, with R packages offering powerful tools for data analysis and visualisation. For example, I can perform a quick tweet analysis for ASCILITE 2022 conference.
For easy reference to all 657 built-in colours for plots and visualisations in R, I generated an R color table.
I use computational methods to process the large volumes of data collected from social media, and here is my implementation of LIWC2015 (Linguistic Inquiry and Word Count) program for computerised text analysis.
I write articles about technology and education, such as some important concepts about current AI technology like ChatGPT.
I also like to find and test interesting things that can be embedded and shown in a webpage for teaching and learning, e.g., online 3D models viewers, useful HTML & CSS effects, and online code editors.
These ideas and resources do not require any technical knowledge or coding skills (e.g., just copy-and-paste the given HTML code to embed and show the objects in a website or LMS). Here is my playground for quick testing and demonstration.
This is a GitHub Flavoured Markdown converted from an R Markdown, which can embed R code chunks (blocks of runnable code) within the document. Just a simple code testing:
x <- "Let's break this sample text into words so that the text can be analysed"
strsplit(x, split=" +") # split at whitespace
## [[1]]
## [1] "Let's" "break" "this" "sample" "text" "into"
## [7] "words" "so" "that" "the" "text" "can"
## [13] "be" "analysed"
words <- unlist(strsplit(x, split=" +")) # can use unlist() to convert the resulting list to a vector for further processing
print(words)
## [1] "Let's" "break" "this" "sample" "text" "into"
## [7] "words" "so" "that" "the" "text" "can"
## [13] "be" "analysed"
Using Markdown makes it easy to show the code chunks and their output.
I knit my R Markdown with output: github_document in the YAML header
and then push this to
my github.io public repository - free and easy.
Visit
GitHub Pages to
learn how to host a webpage or blog on GitHub.
This page is created from an R Markdown written by @CoCoLabErica.