Teaching context:
The course has 10 participants. Some students have C1 English level, but most are only up to B2. They have some knowledge concerning spatial analysis but have difficulty with quantitative methods and data analysis in general1.
Student learning objectives
Students will be able to:
- define ‘Urban Analytics’;
- relate urban problems and methodological proposals in ‘Urban Analytics’.
Assessment
Students will be evaluated on:
- 10% participation in class/forums/social networks.2
- 40% group activity in class.3
- 40% report
- 10% self-assessment
The report will be evaluated considering Likert scale4 and according the rubrics that follow:
| Criterion | Grade % |
|---|---|
| Textual organization and form | 10% |
| References and reliable data | 10% |
| Quality of data visualization elements | 10% |
| Usage of computer tools | 10% |
| Choice of methods | 20% |
| Interpretation of results | 20% |
| Cohesion | 20% |
Pre-class activity
For this lesson, students should watch these two short videos before our meeting. These videos present an urban planning paradigm that is not common sense and, therefore, introduces some reflections on the core content of the lesson (Gehl and Rogers 2013).
Schedule (total: 2 hours)
| Activity | Duration |
|---|---|
| Warm-up | 20 minutes |
| Vocabulary summary | 10 minutes |
| Mini-lecture | 20 minutes |
| Group activity | 45 minutes |
| Re-group to summarize | 25 minutes |
Warm-up (30 minutes)
Word guessing
This activity is designed to help students engage and learn vocabulary aligned with the lesson.
Progression (20 minutes)
The teacher will organize a set of terms and words that will be used throughout the lesson. The game begins with the drawing of one word from the set by each student. After that, one student presents the word to the colleagues, and, individually, pupils write the word meaning in a piece of paper (in English or Portuguese) and add an example of its usage in English. Then, the person who presented the word reads aloud all the definitions, among them the true one, taken from the dictionary. Each participant votes on the definition they believe is correct. Whoever gets the meaning right in their description gets points; and whoever has their definition pointed out as the right one by others, too. If no one gets the definition right, whoever chose the word wins that round. In the next round, someone else presents their word drawn. The points are computed until the class has explored all the words.5
Vocabulary summary (10 minutes)
The summary will be performed after the end of the game and will last 5 minutes. The students will choose one word and write down the definition and one example of usage in English and hand it in to the professor, that will provide individual feedback later.
Mini-lecture (20 minutes)
“Urban analytics is the practice of using new forms of data in combination with computational approaches to gain insight into urban processes. Increasing data availability allows us to ask new and often complex questions about cities, their economy, how they relate to the local and global environment, and much more.”6
This mini-lecture will be based on the discussion of key-topics concerning the mindmap.
Group activity (45 minutes)
Students need to submit Canvas a short and objective report (up to 800 words) answering the proposed questions. This report will be discussed in class, among students. The discussion will be oriented to let colleagues contribute with the development of a final project that stars with question 2.7
What is the difference between organic and purposeful data generation? Illustrate de discussion with examples, and consider the advantages and disadvantages of these two approaches.
Compare and contrast the use of social media versus survey data to investigate an urban issue of your groups’ choice. Remember that this is the first activity concerning the final project.
Re-group to summarize (25 minutes)
We willl discuss the course projects in light of the presentations and the mindmap that concerns the key-topics in Urban Analytics.
Bibliography
Hanson, S. The Geography of Urban Transportation. Second edition. The Guilford Press. London, 1995.
Hoyle, B.S and Knowles, R. D. Modern Transport Geography. Belhaven Press. London, 1992.
Taaffe, J. E. Geography of Transportation. Prentice-Hall. New Jersey, 1973.
Hesse, M. The City as a Teminal: The Urban Context of Logistics and Freight Transport. Ashgate e-Book. 2008.
Rodrigue. J. P.; Comtois, C.; Slack, B. The Geography of Transport Systems. Routledge. Fourth Edition. 2017
Gehl, J., and R. Rogers. 2013. Cities for People. Island Press. https://books.google.com.br/books?id=kqtwtr3QhkIC.
They are motivated to learn↩︎
Shy students get equal means to participate↩︎
the criteria are: engament, critical thinking and methodological contribution↩︎
from 1(fair) to 5 (good)↩︎
These dynamics are feasible within small classes. If the students are numerous, it might be interesting to organize working groups to define and choose the correct definition, but the game is still possible and can enhance students engagement in class.↩︎
https://carto.com/blog/urban-analytics-introduction-spatial-analytics/↩︎
The group needs to choose one student to present the achievements and another one to write the answers and submit into Canvas↩︎