Classification and trends
Analyse recorded Demerit, Merit, Reward and Consequence entries across populated reporting periods.
From school-level patterns to individual learner context
DataSolv Learner Behaviour Analytics helps authorised school users investigate recorded behaviour activity without treating every entry as an independent incident. Analysis can move from headline counts and trends to detailed entries and Student 360.
What the reporting includes
Grade and behaviour type
Compare patterns by historical grade and behaviour type, including Top 5 behaviour types for the selected context.
Detail workflow
Move from LBM Analysis to a detailed table showing learner, event date, grade, classification, behaviour type, Points and reporting period.
Student 360
Drill through to the selected learner and view recorded behaviour entries alongside academic, attendance and ECA context.
Points are shown in a user-friendly direction
The source data keeps nonnegative point magnitudes. In the reporting experience, Demerit points are displayed as negative while Merit points are positive; Reward and Consequence values retain their source magnitude. This display convention does not alter the underlying source values.
Internal Notes stay outside business reporting
Ed-admin learner Notes are treated as an internal note facility. They can remain preserved in the canonical data layer but are excluded from Learner Behaviour Analysis, Detail, classification filtering and Student 360 behaviour reporting.
Recorded entries — not a behaviour coverage claim
Historical behaviour recording completeness can vary between schools. DataSolv therefore focuses on recorded behaviour entries and does not claim a Behaviour Rate, identify “learners with no behaviour”, or infer a severity score from Points.
See it safely: The public DataSolv demo uses a fully synthetic school dataset and includes Learner Behaviour Analysis, Detail and Student 360 integration without exposing any real learner information.