Digital Humanities Resources for the School Year
We've gathered many helpful links and tools in one place, to support instructors who are planning, building, and delivering Digital Humanities curricula in the classroom.
Topics include:
Read more here: https://review.gale.com/2024/09/24/digital-humanities-resources/
The Learning Center within the Lab contains Curriculum Materials like:
Recorded webinar: Pedagogy and Classroom Examples (27 minutes)
The Learning Center within Gale Digital Scholar Lab includes three Python Notebooks for use by researchers, instructors, and students.
Our Python Notebooks are script packages which can be imported to Jupyter or Colab Notebooks, as a further tool for text analysis. The Notebook environment provides full contextual detail and step-by-step instructions to support those who are new to coding. Researchers with prior experience of working with Python have the flexibility to adapt the code to suit their research and analysis goals. Each Python Notebook can be used with the built-in curated datasets found within the Lab, or they can be run on researchers' own collected data.
The Python Notebooks available for download are:
If you are interested in learning or refreshing your Python skills, Python Humanities is a great place to start. The free online course focuses specifically on how humanities scholars use Python to further their scholarship.
Within the Lab, users can use the Projects framework to present the results of research they've carried out.
The Project building pages provide options for structuring the research project using headers, sections, subsections, and the inclusion of images and links.
Once completed, users can export their Project as a PDF to submit to their instructor or to others. Projects built within the Lab can also be easily submitted for editorial review and inclusion in Gale Research Showcase, an open-access repository of student-written digital scholarship.
Learn more about Projects at the Learning Center.
Three ready-to-use Sample Projects provide students, instructors, and librarians with completed project models that are situated within the context of a narrative format. Users can be facilitated through the research process while also being provided with expanded information to deepen user understanding of each phase of the research process.
The Sample Projects are designed to promote the importance of Inquiry-Based learning for best digital humanities and research pedagogical practices. As a result, instructors are equipped with guided models of the Gale Digital Scholar Lab research project workflow, as well as a parallel Critical Thinking supplement to provide discussion around higher-order thinking objectives for each project. Instructors may use each project as a model individually and break down each phase, reviewing the process, and discussion the outcomes as products of specific topics and/or archives. The expandable text within each Sample Project allows instructors to take a deeper dive with students in each phase of the workflow, provoking thought around important questions to be asked, alternative research questions, and additional steps in the process that might be useful to advancing the project.
Since no Gale Digital Scholar Lab project is the same, instructors can also use these Sample Projects together to compare and contrast differences across content, research questions, clean configurations, tool setup, and visualizations. The Critical Thinking supplements can be used to help facilitate these contrasts and illuminate the stickiness that is often involved within the research process. With that said, the Sample Projects can be used as content supplements with corresponding syllabi units and be broken down within each unit, and then be reviewed as a whole culmination project to piece together all each of your Lab learning objectives.
Twelve datasets are provided for exploration, education, and experimentation. Gathering sufficient data of a high-enough quality for text mining is one of the major challenges of this type of research methodology. The goal in providing these datasets is to provide packages of material in support of computationally inflected research and teaching. The sample datasets provided have not been cleaned. Download the datasets from the Learning Center.
