DescriptiveModelingofCollaborativePractices in aComputer-Based Human LearningEnvironment
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Date
2025-07
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Abstract
In anincreasinglydigitaleducationalcontext,Computer-BasedHumanLearningEnviron-
ments(CBHLEs)playacrucialroleinsupportingbothindividualandcollaborativelearn-
ing. Collaborativelearningsupportedbytheseenvironmentsoffersamajoropportunityto
strengthen learnerengagementandimprovethequalityofpeerinteractions.However,to
fully leveragethispotential,itisessentialtounderstandandassesslearningdynamicsusing
reliable indicatorsderivedfrominteractiontraceanalysis.
This thesisfocusesonthedesignandcomputationofcollaborationindicatorsinComputer-
Based HumanLearningEnvironments(CBHLEs).Itproposesamodel-drivenarchitecture
(MDA)-basedapproachtomaketheindicatorcomputationplatform-independent.
Three maincontributionsarepresented:
• First contribution:amodeltransformation-basedapproachisproposedtocompute
collaborationindicatorsindependentlyofthelearningplatform.
• Second contribution:aformalmodel(DECINModel)isintroducedtoassistteachers
in designingvalidcollaborationindicatorstailoredtotheirobservationneeds.
• Third contribution:thecomputationprocessisautomatedthroughthegenerationof
Sequences oftransformations,generatedbyaformalsystem(DECIN-AGSTSystem).
Tosupportthisapproach,aplatform-independenttracemodel(T-PIM)isproposed,
along withformalconstraintsexpressedinOCLtoensurethevalidityandconsistencyofthe
collected traces.Similarly,agenericmodelforcollaborativeindicators(CI-PIM)isdefined,
supportedbyconstraintsthatensurethequalityofthegeneratedindicators.
Finally,theautomationoftransformationsequencegenerationisachievedthroughthe
implementationoftheDECINmodelinaformalsystem(DECIN-AGST),whosevalidityhas
beenverifiedusingthemodelcheckingmethodviatheUPPAALtool,thusensuringsafety,
accessibility,andabsenceofdeadlocks.