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Showing posts from 2019

Simulating Education Data based on the R Wakefield Package

Unlike point-and-click or GUI based statistical programs, the R language requires practice so that programming skills continue to get developed and committed to human memory. Programming skills directly relate to R as a language, and computing languages work when humans use them to solve problems. However, in the process of conducting research, a solo researcher needs to call upon several skills, of which statistical computing is only one. When a solo author pulls together an entire project and begins analyzing data, some skills will be donned and doffed at particular moments in the process, such as statistical computing. Therefore, since programming skills will inevitably be put down and picked back up during the research process, computing practice is essential to refresh the suite of human ability to call upon the R language. At its simplest, R can be thought of as a language of nouns and verbs, with respective activities belonging to each class of language component (Wickham &

Creating Examination Question Banks for ESL Civics Students based on U.S. Form M-638

R and Latex Code in the Service of Exam Questions   The following webpage is under development and will grow with more information. The author abides by the GPL (>= 2) license provided by the "ProfessR" package by showing basic code, but not altering it. The code that is provided here is governed by the MIT license, copyright 2018, while respecting the GPL (>=2) license. Rationale Apart from the limited choices of open sourced, online curriculum building for adult ESL students (viz., there is a current need to create open-sourced assessments for various levels of student understandings of the English language. While the U.S. Citizenship and Immigration Services ( has valuable lessons for beginning and intermediate ESL civics learners, there exists a need to provide more robust assessments, especially for individuals repeating ESL-based civics courses. This is because the risks and efforts involved in applying for U

Digital Humanities Methods in Educational Research

Digital Humanities based education Research This is a backpost from 2017. During that year, I presented my latest work at the 2017  SERA conference in Division II (Instruction, Cognition, and Learning). The title of my paper was "A Return to the Pahl (1978) School Leavers Study: A Distanced Reading Analysis." There are several motivations behind this study, including Cheon et al. (2013) from my alma mater .   This paper accomplished two objectives. First, I engaged previous claims made about the United States' equivalent of high school graduates on the Isle of Sheppey, UK, in the late 1970s. Second, I used emerging digital methods to arrive at conclusions about relationships between unemployment, participants' feelings about their  (then) current selves, their possible selves, and their  educational accomplishm ents. I n the image to the left I show a Ward Hierarchical Cluster reflecting the stylometrics of 153 essay

The 'jstor_ocr' function in the 'r7283' package for concatenating ocr and metadata from JSTOR's Data for Research

Digital Text Investigations The digital humanities continues to change the ways in which we draw conclusions about social phenomena. This condition starts from the understanding that for the first time in history, humans can potentially scale the totality of a social phenomenon's appearing. This continuous evolution of study provides new ways to examine data. A key idea in this evolution is the ability to pull together unstructured data and their accompanying metadata as a rejoinder to older forms of content analysis and its related approaches. The JSTOR Data for Research (DfR) arrangement presents such a unique development to work with unstructured data. Subscribers can request large, carefully delineated, corpora for academic investigations. At time of writing there are two options for data requests. The first option allows the subscriber to create search terms, and without a signed contract, scale down the results, and download n-grams (roughly 1-3 combinations are available

The Matrix Literature Review and the 'rectangulate' Function from the r7283 Package

Matrices and Literature Reviews Pulling together a strong literature review continues to be the very foundation of  positioning an education researcher's novel contribution to the field. Yet, reviewing literature can be daunting at the outset. This is because organizing the literature review results requires itemizing, tagging, and keeping track of the relevant articles. Organizing 100 + articles takes time, commitment, and can ultimately distract from the task at hand, which is getting a grip on the state of knowledge. To make the task of organizing the literature more straightforward, I have created a computational function that helps lift some of the burden of organizing literature.  It takes an exported bibliographic research file (.bib) exported from EBSCO and widens it into a matrix. Transposing the .bib file into a matrix allows the researcher to jump right into the matrix literature review style of reading articles. A matrix literature function for education researche

Text mining, unruly text, XML, TEI, and R: Go with conventional architecture, or make your own?

Many educational researchers will inevitably work with text as data. It is unavoidable, as reflective practice (almost universally required by teacher preparation programs) requires conveying meaning through words, and retaining a corpus of reflections throughout a semester, or even a year. Finding patterns in teaching strategies will inevitably require text parsing. Student writing assessment naturally lends itself to text analytics, so educational researchers can gain data on student learning through reading student responses to writing prompts. Further still, professional educational researchers stand to gain much by taking in large amounts of text, searching for patterns, and reporting on their findings. The more skill at working with text, the greater the opportunities abound for educational researchers. Working with text requires effort and copious patience, mostly because text is, relative to numbers, messy. The Curse of Messiness Messiness is essentially the observation th