Week 5 Schedule and Activities
In Week 5, you will:
- Learn what data is, how it differs from information, and how the
data investigation cycle provides a repeatable framework for turning
raw data into meaningful conclusions.
- Explore how relational databases organize data into structured tables,
why careful design prevents costly errors, and how access controls
determine who can see what.
- Practice reading SQL queries that filter, join, and retrieve data from
one or more relations — understanding what question each query is
asking, not just how the syntax works.
- Examine data mining: what it is, how it differs from querying, the
six major techniques, and why finding a pattern does not automatically
make that pattern meaningful or safe to act on.
- Connect these ideas to your classroom and to real questions about
data privacy, algorithmic bias, and what it means for institutions
to make decisions about people using data those people never knew
was being collected.
The schedule below is a suggested pacing guide. Feel free to adjust based on
your own calendar, but try to keep the order of activities so later pieces
build on earlier ones.
Computer Science Content
(Monday - Wednesday)
-
Topic 5a - Data and Analysis
Establish the foundation: what data is, why a clear question is necessary
to turn data into information, and how the five-stage data investigation
cycle — pose, collect, clean, analyze, communicate — provides
a framework you can use and teach at any grade level.
-
Topic 5b - Database Fundamentals
Explore why relational databases exist, how they organize data into
relations with tuples and attributes, what schemas and subschemas
control, and how redundancy in a poorly designed database causes
update, deletion, and insertion problems that well-designed databases
avoid.
-
Topic 5c - Database Operations
Learn to read SQL queries: what SELECT, FROM, WHERE, and JOIN each do,
how to state in plain English the question a query is answering, and
how SQL querying connects to Stage 4 of the data investigation cycle.
-
Topic 5d - Data Mining
Understand what data mining is and how it differs from querying and
basic statistics. Work through the six major techniques — class
description, class discrimination, cluster analysis, association analysis,
outlier analysis, and sequential pattern analysis — and examine
where data mining is already operating in schools and daily life.
Beyond the Content
(Thursday - Friday)
-
Social and Ethical Considerations
Examine three scenarios that connect databases and data mining to real
consequences: a graduation risk score that may encode historical inequities,
a hospital subschema that protected data inside the system but not once
it left, and a grocery loyalty program that inferred sensitive personal
information customers never knowingly disclosed.
-
Teaching and Learning Perspectives
Reflect on how data and database concepts translate to your classroom,
what misconceptions students bring at each grade level, and how the
data investigation cycle can serve as a teaching framework across
subjects — not just in CS.
Small Group Discussion
(Thursday - Friday)
You will meet with your small group to make sense of the week and to
prepare for the Competency Demo.
Week 5 Small Group Discussion Instructions
Competency Demo
(Thursday - Sunday)
Competency Demo #5 - Databases, Data Science, and Data Mining
- Complete all Week 5 activities before attempting the Competency Demo.
- The CD addresses Competencies 13, 14, and 15. Review those learning objectives before you begin.
- Closed book, closed notes, closed resources.