Joseph Holler's Open GIScience Curriculum at Middlebury College
Sep-12 : In this lesson, we will explore the course goals and design.
Middlebury College Geography Course GEOG0361
For assistance outside of office hours, your resources include:
For private feedback on assignmnets, we will use individual Google documents in our class Google Drive folder. Feel free to add comments in response to anything in your feedback document, e.g. to notify me that you have revised an assignment or that I have overlooked something.
In this course we will study geographic information science (GIS) with open-source software and critical GIS scholarship. In labs, we will practice techniques to include: data acquisition and preparation for analysis, spatial SQL database queries, automating analysis, spatial interpolation, testing sensitivity to error and uncertainty, and data visualization. We will read and apply critical research of GIS as a subject and with GIS as a methodology. Spatial data sources for labs and independent research projects may include remote sensing, micro-data, smart cities and open government data, and volunteered geographic information (e.g. OpenStreetMap and social media).
Prerequisite: Human Geography with GIS or Mapping Global Environmental Change or Data Sciences Across the Disciplines (Geography) or approval based on other experience in geographic analysis. Programming experience is not assumed or required! You just need to be willing to learn how to translate the spatial analysis that you know from desktop GIS (QGIS, ArcGIS, etc.) into code.
The major emphasis this fall will be learning how to manage a full GIScience research workflow in an open science framework. We’’’ll achieve this through:
Open science requires researchers, universities, and publishers to change the way they value intellectual work and intellectual property, and the same goes for instructors and students. Traditional means of evaluating and grading student work that are based on individualism, competition, and secrecy are counterproductive to an open science learning environment.
Throughout this course you will develop a set of your own personal pages and repositories on GitHub, containing all of your work for the course. You will receive qualitative feedback on your GitHub portfolio work from peers and from your professor throughout the semester, and you will be given opportunities to self-evaluate as-well. My goal and expectation for your work is that through revision based on feedback, most students should develop a portfolio suitable to show potential employers or graduate schools, earning at least a B+ or A-.
We will have least two one-on-one meetings during the semester: one in the first two weeks and one at the end. Through these meetings and interim written self- and peer-evaluations, you will set goals and accrue qualitative feedback to serve as a roadmap to your personal level of achievement. At the end of the semester, you will submit a final self-evaluation and proposed grade for the course based on your personal goals and the general expectations outlined below. The instructor reserves the right to adjust the final grade determination. Some people call this an ungrading approach to assessment.
We will interpret the quality of work as follows:
| Gr | Description |
|---|---|
| A | Work is excellent and complete. Your work is ready to show to employers or graduate schools. In addition, you have contributed positively to the collective learning and knowledge base of the class.* |
| A- | Work is excellent and complete. Your work is ready to show to employers or graduate schools with very minor revisions. |
| B+ | High quality work. Your work is ready to show to parents and friends, and almost ready to show employers or graduate schools—pending minor revisions. |
| B | Good work. Your work needs a fair amount of revision to remedy errors and/or full effort to some more cursory components. You could use one more round of feedback and revision before sharing with employers. |
| B- | Decent work. There are a few significant errors and/or gaps that need addressing before you can share the work with a potential employer. |
| C’s | You have demonstrated learning and intellectual growth, but important components of your GitHub portfolio are not working or in need of complete revisions. C+ needs at least one additional round of feedback prior to sharing work with a potential employer, whereas C or C- may need more. |
| D | Work is incomplete and/or cursory |
| F | Not attempted |
* The best way to ensure a public record of your contributions is to post and reply to GitHub Issues.
In weeks in which no spatial analysis is due (roughly biweekly), please write a short blog post reflecting on new class content (readings, discussions, activities, workshops) connecting them to their significance for you, in terms of any internships, independent research, other courses, personal experience, or career aspirations you may have. You will have reminders and suggested prompts with the associated lessons.
A draft of the posts should be committed to GitHub prior to the relevant class meeting. As is the case for all of your content on GitHub, revisions are permitted until the end of the course.
Posts should include references to relevant readings by listing them at the end (similar to how I have done in this course site) and linking to their DOI, if one is available.