{"id":24767197,"url":"https://github.com/centerforassessment/ncme_2022_demonstration","last_synced_at":"2026-01-29T10:03:16.247Z","repository":{"id":143378580,"uuid":"456662891","full_name":"CenterForAssessment/NCME_2022_Demonstration","owner":"CenterForAssessment","description":"Using GitHub for Open-Source Analytics, Reporting, and Dissemination of Research","archived":false,"fork":false,"pushed_at":"2022-05-22T07:36:29.000Z","size":24568,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":4,"default_branch":"main","last_synced_at":"2026-01-12T11:18:26.516Z","etag":null,"topics":["analytics","data-science","github-pages","ncme-2022","open-science","reproducible-research","rstats"],"latest_commit_sha":null,"homepage":"https://centerforassessment.github.io/NCME_2022_Demonstration/","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/CenterForAssessment.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-02-07T20:18:25.000Z","updated_at":"2022-05-16T17:00:54.000Z","dependencies_parsed_at":"2023-09-14T02:17:22.474Z","dependency_job_id":null,"html_url":"https://github.com/CenterForAssessment/NCME_2022_Demonstration","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/CenterForAssessment/NCME_2022_Demonstration","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CenterForAssessment%2FNCME_2022_Demonstration","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CenterForAssessment%2FNCME_2022_Demonstration/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CenterForAssessment%2FNCME_2022_Demonstration/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CenterForAssessment%2FNCME_2022_Demonstration/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/CenterForAssessment","download_url":"https://codeload.github.com/CenterForAssessment/NCME_2022_Demonstration/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CenterForAssessment%2FNCME_2022_Demonstration/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28875446,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-29T09:47:23.353Z","status":"ssl_error","status_checked_at":"2026-01-29T09:47:19.357Z","response_time":59,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["analytics","data-science","github-pages","ncme-2022","open-science","reproducible-research","rstats"],"created_at":"2025-01-29T00:52:31.455Z","updated_at":"2026-01-29T10:03:16.222Z","avatar_url":"https://github.com/CenterForAssessment.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# NCME 2022 Demonstration\n\n# Using GitHub for Open-Source Analytics, Reporting, and Dissemination of Research\n\nThis GitHub repo provides source code associated with the NCME group demonstration showcasing\nnovel uses of GitHub for promoting research in educational assessment. Specifically, we present a\nseries of public GitHub repositories that researchers can easily customize for their own uses.\n\nThese repositories are structured such that researchers with a basic understanding of GitHub and R\ncan either (a) modify a set of parameters and efficiently run a comprehensive analysis, or (b)\nleverage the basic repository structure to develop and disseminate their own suite of analytic tools.\nAcross all demonstrations, we expand beyond the basics of GitHub repositories to highlight unique\napplications of the platform to educational assessment data.\n\nThe four demonstrations are described below linking to their individual repos and presentations:\n\n## Using GitHub to building and distribute R packages [@dbetebenner](https://github.com/dbetebenner)\n\nPerhaps the greatest strength of [R](https://cran.r-project.org/) is its extensibility. The ability to\ncreate packages with R has led to the development of tens of thousands of speciality software packages\nthat expand base R in innumerable ways. Although building your first R package can be a daunting task,\ndoing so is well worth the effort: An R package adds fidelity to any data-related task and greatly tames\nanalytic complexity. In this demonstration, [Damian Betebenner](https://github.com/dbetebenner) presents how to quickly build\nyour first R package from a package skeleton on GitHub. Coupling R package development with a GitHub repository\nhas many advantages, including\n\n* better code maintenance,\n* easy distribution of the package to other users, and\n* online documentation via [GitHub Pages](https://pages.github.com/)\n\nThe repo containing the package skeleton is located [here](https://github.com/dbetebenner/customizedPackageForR).\n\nThe presentation for the session is located [here](https://centerforassessment.github.io/NCME_2022_Demonstration/presentations/Building_and_Distributing_R_Packages_Using_GitHub.html#1)\n\n## Web-Based Distribution of Research using GitHub [@alliecooperman](https://github.com/alliecooperman)\n\nGitHub allows users to collate their analyses into a user-friendly, distribution-ready website.\nIn this demonstration we show how to researchers can leverage [Github Pages](https://pages.github.com/) and\nauthor-written R packages (also available through GitHub), to host vignettes, source code for\nstatistical analyses, presentations, and project updates. Furthermore, researchers can easily customize the\nwebsite layout to match a desired style. Additionally, being web-hosted, all content is\nimmediately available with source code. In the demonstration, we present an example website\ncreated during a summer internship program. We then walk through the basic set-up of a\nskeleton website within RStudio, including how to incorporate new pages and structure the\nwebpage navigation. We also discuss the benefits of developing a project website for promoting collaboration\nand reproducible research practices.\n\n## Using GitHub and RMarkdown for report generation and dissemination [@adamvi](https://github.com/adamvi)\n\nData analysts are often tasked with writing reports that\ndescribe data, analyses, and results associated with a project. Depending upon the nature of the\nproject, such reports are either completely customized or borrow heavily from other reports (e.g.,\nannual reports). GitHub repositories and associated GitHub actions can be used to coordinate the\nwriting as well as the production of final reports for dissemination. The process we demonstrate\nutilizes R, R Markdown, and several associated R packages as the base tools to construct these\nreports.\n\n## Using GitHub to consolodate the analysis and dissemination of research [@ndadey](https://github.com/ndadey)\n\nPrior presentations have focused on creating a series of vignettes or write ups via R individual \nR markdown files linked through a webpage. This demonstration illustrates how researchers can use \nthe r [bookdown](https://bookdown.org/yihui/rmarkdown/books.html) package to house more complex analyses. \nThis approach may work well for projects that involve a number of interconnected analyses that need to be\nrun regularly. For example, state educational agencies could use this approach to house a series of analyses that are \nrun and expanded on annually. Similarly, this approach could be used to house regular psychometric analyses conducted \non annual test data.\n\n---\n\n[![CC BY-SA 4.0][cc-by-sa-image]][cc-by-sa]\n\nThis work is licensed under a\n[Creative Commons Attribution-ShareAlike 4.0 International License][cc-by-sa].\n\n[cc-by-sa]: http://creativecommons.org/licenses/by-sa/4.0/\n[cc-by-sa-image]: https://licensebuttons.net/l/by-sa/4.0/88x31.png\n[cc-by-sa-shield]: https://img.shields.io/badge/License-CC%20BY--SA%204.0-lightgrey.svg\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcenterforassessment%2Fncme_2022_demonstration","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcenterforassessment%2Fncme_2022_demonstration","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcenterforassessment%2Fncme_2022_demonstration/lists"}