SHS3 Geography · Semester 1 Week 18: Geospatial Data Collection, Representation and Interpretation

Lesson notes

Learning Objectives

Indicator: 3.2.2.LI.2 - Analyse and interpret geospatial data using flow charts

By the end of the lesson, learners can:

Define a flow chart and explain its purpose in representing geospatial data.
Construct a flow chart from a given dataset showing movement or flow between two or more locations.
Analyse a flow chart to describe the direction, volume and pattern of movement shown.
Interpret relationships between variables (such as production and migration) using flow charts and draw reasoned conclusions.
Evaluate the strengths and limitations of flow charts as a tool for representing geospatial data.

Sign in with your phone number to read the full note and download the GES plan - free.

Sign in with phone number

Curriculum details

Strand: Navigating Our Environment (Strand 2)
Sub-strand: Geospatial Data Collection, Representation and Interpretation (2.2)
Content standard: 3.2.2.CS.1 - 3.2.2.CS.1 Demonstrate skills in basic geospatial data representation and interpretation using diagrams 3.2.2.LO.1 Represent geospatial data using dot maps and flow charts
Indicator: 3.2.2.LI.2 - Analyse and interpret geospatial data using flow charts
Suggested placement: Semester 1, Week 18 (Week 18 of the year)
Our suggestion, laid out in curriculum order across three terms of twelve weeks. NaCCA does not fix the week, so follow your school's scheme of learning.
Curriculum reference: NaCCA curriculum document, p. 108

Exemplars (from the NaCCA curriculum)

Activity-Based Learning: In a GESI-responsive classroom, analyse and interpret geospatial data using flow charts. Learners should create an environment in which others believe that their thoughts and opinions are valued.

Assessment (3.2.2.AS.2). The document marks these depth-of-knowledge levels for this indicator: Level 4 Extended critical thinking and reasoning.

Teaching and Learning Resources:
- Geospatial datasets e.g. national, regional, district and local agricultural production such as maize and groundnuts in tonnes
- Geospatial datasets e.g. regional and district migration, trade or agricultural production (in tonnes)