Course Project

Author

Shipeng Sun

Presentation

Create and submit a presentation file (PowerPoint or PDF converted from PowerPoint), with which you will present your project to the class.

  • The presentation should not be longer than 5 minutes.

    • We will be strict on the time limit.
    • It is strongly recommended to pre-record a five-minute presentation video and play it during the presentation time.
    • I apologize in advance if you will have been stopped before you finish your presentation.
    • Upload your presentation file to the Discussion Forum so that we can read it.

  • Briefly introduce the background, data source, data processing, code organization, and key findings/results.

  • Do NOT directly use your paper, poster, WebGIS, or Webpage as your presentation file, although you can refer to those for details.

  • Leave some time for Q/A, where we may ask questions about the implementation details.

Final Course Project Deliverable or “Report”

As we explained in the guideline, the format could be a regular research paper, a poster, a WebGIS, or a Webpage with maps (like ArcGIS.com Story Maps).

Regardless of the format of the final deliverable, it should generally contain the following components. This structure is typical for research works using quantitative methods.

  • Title: with author and institution information
  • Abstract: 250 words or less summarizing the research background, research questions, data and methodology, and main findings. Note Abstract is generally not applicable to posters due to space limit.
  • Keywords: 3 to 5 keywords to categorize the topic of your paper. This is not applicable to posters, either.
  • Main text:
    • Introduction: background, significance, goals and objectives, specific research questions, possible contribution of the research, structure of the paper
    • Literature Review: history, development, latest progress on the research topic, what others have done regarding theories, opinions, data, methods, and findings.
      • Give a good synthesis of the relevant knowledge.
      • Do NOT list and summarize publications one by one. Develop a conceptual framework from the literature and fill in specific papers to each part in the framework.
      • It is very challenging to write a good review. NEVER underestimate the difficulty of writing this section.
      • In some fields, this part can be integrated with Introduction.
    • Data and Methodology: describe the data sources and main methods used to address the question. Clearly lay out the main steps of the data processing and analysis, so other people can replicate the analysis if they are interested in the work. Do NOT explain well-known methods in details. For example, there is no need to elaborate buffer or shortest path analysis. It is good enough to mention their names.
    • Results: Present the results, explain the resultant statistics, maps, figures, and/or tables. Do NOT leave the interpretation work to the readers. Just showing the tables, figures, and maps is not enough. EXPLAIN the results and interpret them.
    • Discussion: discuss the implications of the results and how the results answer your research questions. You can also relate your results to the bigger context in terms of how your results support existing findings, shed new lights, or make contrast to known theories. This part could also include limitations and caveats.
    • Conclusion: main findings, take-home points, future works It is also widely accepted that the Discussion and Conclusion sections are integrated into a single “Discussion and Conclusion” section.
  • References: papers, publications, books, data, and websites cited in the paper. All references should be prepared in APA or other academic styles. No matter what style the project paper uses, it must be consistent, i.e., all citations and references have the exactly same style.
  • Data Sources, Credits, and Disclaimers: particularly useful for posters and web-based content.
  • Acknowledgements (optional): if extra help was received from other people or organizations for funding, technical support, data, or in other aspects, they could be acknowledged in this section.
  • Appendix (optional): if extra materials do not fit in the main text, they can be presented in the appendix section.

Rubrics for evaluation

Other than the general writing rubrics explained in the Course Project Guideline document, there are a few specific ones for this course.

  • Data Sources: Multiple data sources are expected. A single data layer, or feature class, is generally not enough for the inputs.

  • Model or Tool: A ModelBuilder Model or Tool is expected for all projects.

    • A figure output from the tool should be included in your report to ilustrate the key data processing and/or analysis steps.

    • Such a tool with iterators (loops) will be favorable.

    • Programming with Python, R, or other languages is even better, but a flowchart showing the processing/analysis logic is required.

  • Final Map Layout: Do NOT violate the basic cartography principles.

    • Font choice, color choice, hierarchy

    • Pretty numbers for the scale bar and legend

    • Meaningful and human-readable titles, labels, and other texts on the map

    • No redundancy, no irrelevant information, no unnecessary map elements

    • Layout design, box/element alignment/arrangement, eye movement

    • Balance of sophistication, not too simple, not too complicated

  • Content: Be academic, use reliable sources.

    • The final report must have complete paragraphs and sentences. One or two lists of bullet points are welcome, but do not use them for all sections of the entire report.

    • Bullet points are good for presentations and teaching materials, not for your entire final report.

    • Figure captions are below figures, but table captions are above tables.

    • References must be from academic sources such as journal papers, books, and formal research reports. Do NOT cite webpages with unknown authors that were returned by a search engine.

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