Harvest

Harvest Project

Harvest project aims to make learning visible to educators and decision makers. Within the context of the Sugar Learning Platform, this can be achieved by collecting reliable metadata from the Journal. This project proposes a simple and continuous mechanism to obtain metadata from Journal entries, incrementally over time. Metadata can stored in a central repository for further statistical analysis.

What it is collecting?

Harvest collects most of the non-sensible journal entry metadata, but also collects anonymous information about the user.

Concepts

• Activities refers to the sugar applications that are being used.
• Learners refers to the sugar users.
• Instances refers to the different sessions an particular activity.
• Launches refers to the different times the same session is started.

Meta-data

Data
Concept	Attribute	Description	Type
Learners	serial_number	Laptop identifier	String
	birthdate	Aproximate birthdate of the user	Unix time
	gender	Gender of the user	String
Activities	bundle_id	Activity identifier	String
Instances	object_id	Entry identifier	String
	filesize	Size in bytes of the content associated to the entry	Integer
	creation_time	Entry creation time	Unix time
	timestamp	Entry last modification time	Unix time
	buddies	Number of user's associated to the entry	Integer
	spent_time	Just a place holder for now. Still not supported in Sugar	Integer
	shared_scope	If entry was exposed through the collaboration service	Boolean
	title_set_by_user	If user has set a custom message to the entry	Boolean
	keep	If the entry has been explicitly kept in the journal	Boolean
	serial_number	Identifier of the entry owner	String
	bundle_id	Identifier of the activity	String
Launches	timestamp	Launch time for an particular entry	Unix time
	object_id	Entry identifier	String
	serial_number	Identifier of the particular entry	String

Observation: All the meta-data names, matches the original names of the journal meta-data.

How does it work?

The project comprises two pieces of software: a harvest server that can be localed anywhere in the cloud, and a harvest client that runs in the learners machine. The harvest server exposes a service, accessible from the Internet, for metadata storage. The harvest clients collect metadata from the Journal and sends it to server.

When does it collect?

• Data is collected when Sugar starts and when Sugar successfully connects to a network.
• Once it has successfully collected data, it won't sent another report until the next collecting period, weekly or monthly.
• In order to avoid service peaks, Harvest applies a random (1/7) chance for executing the collection process.

What are the advantages?

• Doesn't require OS customizations, it based on Sugar's web service framework.
• Doesn't depend on school server presence, either on backup files.

What is implemented so far?

Harvest server

• Back-end service for storage.
• SSL data encryption.
• API Key authorization.

Harvest client

• Journal entries collection.
• Web service extension.
• Extension controls from the web service control panel.
• Random selection.
• Exclusive log for debugging.
• RPM packages.

Code

• https://github.com/tchx84/harvest-client
• https://github.com/tchx84/harvest-server

TODO

• Server maintenance scripts.
• Server packaging.
• Server-side data visualization
• Client-side (Sugar) modifications to collect run-times