人工智能、认知卸载及其对教育的影响2026

Artificialintelligence,cognitiveoffloadingandimplicationsforeducation

March2026

NetworkforQualityDigitalEducation|Artificialintelligence,cognitiveoffloadingandeducation 1

ProfJasonM.LodgeandProfLeslieLobleAM

ThisreportformspartoftheworkprogramsupportingtheAustralianNetworkforQualityDigitalEducation.TheNetworkbringstogetherleadersfromacrosseducation,industry,socialpurpose

andphilanthropicorganisations,governmentandresearch,inthecommonpurposeofensuringthatallAustralianstudentsbenefitfromthebesteducationaltechnology(edtech),andthebenefitsofedtechareleveragedtotacklethepersistentlearningdivide.

MembersoftheNetworkhaveprovidedvaluableengagement,inputandfeedbackaspartofthereport’sdevelopment,thoughthereportdoesnotrepresentaconsensusorendorsedNetworkview.

TheNetworkischairedbyLeslieLobleAM,whoisIndustryProfessorattheUTSCentreforSocialJusticeandInclusion(.au).

ProfessorJasonM.LodgeisProfessorofEducationalPsychologyandDirectoroftheLearning,

Instruction,andTechnologyLabintheSchoolofEducation,TheUniversityofQueensland.

Howtocitethisreport

LodgeJ.M.andLobleL(2026).Artificialintelligence,cognitiveoffloadingandimplicationsforeducation,UniversityofTechnologySydney,doi:10.71741/4pyxmbnjaq.31302475.

Copyrightinformation

ThisreportispublishedbytheUniversityofTechnologySydney©UniversityofTechnologySydney2026.

WiththeexceptionoftheUTSbranding,contentprovidedbythirdparties,andanymaterialprotectedbyatrademark,allmaterialpresentedinthispublicationislicensedunderaCreativeCommonsAttribution—NonCommercial,DerivativeWorks4.0(CCBY-NC-ND4.0)licence.Thefulllicencetermsareavailableat:/licenses/by-nc-nd/4.0.

Anyenquiriesaboutorcommentonthispublicationshouldbedirectedto

edtechnetwork@.au.

Accessibility

ThisreportispartiallyconformantwithWCAG2.1levelAA.Knownlimitationsandalternativesarelistedbelow:

¦Imagedescriptions—imagesandgraphsdonothavelongimagedescriptionsbecausewehaveretrofittedaccessibilityrequirementsontoanexistingtemplateandlayout.

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Acknowledgements

TheauthorsaregratefulthattheAustralianNetworkforQualityDigitalEducationishostedbythe

UTSCentreforSocialJusticeandInclusion,andsupportedbythePaulRamsayFoundation.TheauthorsappreciatethevaluableexpertiseandguidanceoftheNetworkmembersandothers,whichhasenhancedthereport.

WeacknowledgetheTraditionalOwnersofCountrythroughoutAustraliaandpayourrespectstoElderspastandpresent.

PaulRamsayFoundation

262LiverpoolSt,DarlinghurstNSW2010.au

PRFisaphilanthropicfoundation.ThelatePaulRamsayAOestablishedtheFoundationinhisnamein2006and,afterhisdeathin2014,leftmostofhisestatetocontinuehisphilanthropyforgenerationstocome.

AtPRF,weworkforafuturewherepeopleandplaceshavewhattheyneedtothrive.Withorganisationsandcommunities,weinvestin,build,andinfluencetheconditionsneededtostopdisadvantageinAustralia.

ThisresearchwasfundedbyPRF(grantnumber5040).

Anyopinions,findings,orconclusionsexpressedinthisreportarethoseoftheauthorsanddonotnecessarilyreflecttheviewsoftheFoundation.

NetworkforQualityDigitalEducation|Artificialintelligence,cognitiveoffloadingandimplicationsforeducation

TableofContents

TableofContents

Preface 3

Respondingtothechallenge 5

Executivesummary 7

Glossaryofkeyterms 8

Introduction 13

Theenduringprimacyofknowledge 15

Humancognitivearchitectureandthegoal-drivenlearner 17

Beneficialvs.detrimentalcognitiveoffloading 19

Beneficialcognitiveoffloading 19

Detrimentalcognitiveoffloading(outsourcing) 19

The“performanceparadox”inlearningwithAI 21

Unpackingtheparadox:Bypassing“desirabledifficulties” 22

Metacognitivelazinessandtheillusionofcompetence 23

Thepedagogicalsolution:Fromcognitiveatrophytoaugmentation 24

Implicationsforcurriculum,practice,andequity 27

Anewmetacognitiveequitygap 27

Augmentingtheteachertoscaleexpertise 28

Conclusion 29

References 30

Appendix:Annotatedbibliography 35

ThisreportinvestigatesaprofoundnewchallengedrivenbyAI’spowertorapidlyaccessinformationandprovideasemblanceofthinking:theriskthatstudentswilloutsourcetoomuchofthecognitiveworkthatiscrucialtoestablishingtheknowledge,skilland

‘thinkinginfrastructure’thatenablesbothschoolingsuccessandlifelongcapacityforongoinglearning,understanding,reflection,creativityandachievement.

Preface

Artificialintelligence(AI)andespeciallygenerativeAIarepropellinganewdynamicforAustralianeducation,simultaneouslyunlockingcompellingopportunitiesandsubstantialchallengesforteachingandlearning.

TeachersandstudentsfindthemselvesonthefrontlineofthisparadoxastheynavigateinrealtimequestionsofhowtobestuseAIforlearningandknowledgegain.

Preface

Today,inAustralia,nearly80percentofstudentsreportusingartificialintelligence(Thomasetal.2025),andtwo-thirdsofearlysecondaryteachers

—fourthhighestusageintheOECD(OECD2025)—merelythreeyearssinceChatGPTburstthrough.

AsAIbecomesanear-universalfeatureofAustralianeducation,wecannotdisentanglediscussionsof

AIfromdiscussionsofwhatwillmakeAustralianeducationmosteffectiveandequitable.Yettheeducationsectoroftenfeelslikeit’sthetailwhileothershavethewhiphand.JustasitgetsontopofoneaspectofAI,significantnewdimensionsemerge.

Forteachersandforpolicymakers,allofthiscansometimesfeeloverwhelming,especiallywhenthereissuchlimitedresearchorevenconsistentexperiencewithatechnologythatisintentionallydesignedtokeepchanging,fromprompttoprompt,versiontoversion,yeartoyear.Retainingagencyoverthedesign,useandgovernance

ofAIthusbecomesanessentialcomponentofsuccessfulintegrationofAIineducation.

TheAIdynamicisnuancedandcomplexineducation.Itcanbothcounteract—orcompound

—non-technologicalfactorsthatpropellearninggapsandeducationaloutcomes,fromteachershortagestounevendistributionofresourcesandconcentrationsofdisadvantage.Theimpact

dependsondecisionsregardinganAItool’squality,accessibilityand,aboveall,effectivepedagogicaluse.

Onthepositivesideoftheledger,someofthestrongestavailableevidencepointstosustainedlearninggainsfromAI-enabledadaptivetutoringsystems(Loble&Hawcroft2022).Educationtechnology(edtech)alsocanassiststudentswithdisability(OECD2026),whonowcompriseaquarterofAustralianschoolclassrooms(ACARA2024).

AIreducesteacherworkloads,freeingtimeformorevaluableeducationalinteractions(NSW2024).Andbyprovidingqualityteachingresources,well-designeddigitaltoolscanhelpsupportconsistentaccesstohigh-quality,content-richcurriculum,akeyfactorinsecuringeducationalequity(Jensenetal.2023).

Preface

Securingthebenefitsofthistechnologyreliesonaccesstoqualityresources,digitalinclusion,skillsandunderstanding,andteacherexpertiseinhowtoeffectivelyincorporateAIformaximalstudent

learninggain.Withoutthesefoundationalelements,theriskrisesbothforunevendistributionofAI’sbenefitsandforchallengesinobtainingpositiveeducationaloutcomes(Loble&Stephens2024).

Thisreportinvestigatesarelated,andprofound,newchallengethatwefacewithAI’spowertorapidlyaccessinformationandprovideasemblanceofthinking:theriskthatstudentswilloutsource

toomuchofthecognitiveworkthatiscrucialtoestablishingtheknowledge,skilland‘thinkinginfrastructure’thatenablesbothschoolingsuccessandlifelongcapacityforongoinglearning,

understanding,reflection,creativityandachievement.

ThereisagrowingbodyofevidencethatusingAIcanshort-circuitthecognitiveeffortrequiredforsustainable,deeplearning,thuscreating“falsemastery”withpotentiallylong-termconsequences(OECD2026).ThiscognitiveoffloadingfromhumantoAIisespeciallyriskyforschoolstudents(‘novice’

learnerswhoarebuildingfoundationalknowledgeandskills)whentheyturntoAIasatemptingsubstitute,notanamplifier,increasetheirdependencyon

thetoolandloseaccesstodeeperlearning.

Cognitiveoutsourcingalsointroducesextraequityrisks.ResearchsuggeststhatstudentswhopossesshighlevelsofcontentknowledgeandstrongmetacognitiveskillsarebetterabletoleverageAI

toaccelerateanddeepentheirlearningandcriticalthinking(Hongetal.2025).Conversely,studentslackingsuchskills,oftenthosealreadyexperiencingdisadvantage,arepotentiallymoresusceptible

toharmfuloffloadingandmissingthelearningtheyneed.TheunstructureduseofAIrisksevenwiderequitydivides(Loble&Stephens2024).

ThegoodnewsisthatresearchstudiesalsosuggesttheseharmfuleffectscanbecounteractedthroughpurposefulteachingandlearningstrategiesandeffectivedesignofAIeducationtechnology.

Thesestrategiesreinforcetheimportanceofqualityteaching,withAIinasubsidiary,supportingposition.

So,whiletheextentandscaletowhichstudentsshifttheirknowledgeandskillacquisitiontoAIraisesfundamentalquestionsforteachingandlearning—

questionsthatcannotbeansweredsolelybyteachingAIliteracy—italsobringsanimportantopportunitytovalidateandbolstertheroleofteachers.

Thisdoesnotmeantacklingharmfulcognitiveoutsourcingissolelytheresponsibilityofteachers,however.Theecosystemthatsupportseffectiveteachingandlearning(includingqualitycurriculum)mustrespond,too,andhowwenavigatethenuanceofpositiveandnegativecognitiveoutsourcingwithAIwilldependongooddecisionsacrossschoolingandpublicpolicy.

PartofempoweringteachersalsomeansensuringwedirectthedesignofAItoolssoteachershavetrustworthyresourcestouse.Alargeproportionofeducationaltechnologycontainslittleexplicitlearningcontent,norgroundinginevidence-basedpedagogy(UNESCO2023),especiallygeneral-purposeAIchatbotslackingeducationalguidanceorreliableevidencebasis.TheworktaskedbyEducationMinistersfordevelopment

ofedtechnationalstandardsandqualityassuranceproceduresisessentialandurgent.

Preface

Respondingtothechallenge

TheAustralianNetworkforQualityDigitalEducationhasbroughttogetherleadersacrosseducation,government,industry,socialpurpose,researchandphilanthropycommittedtoharnessingedtech’spotentialtoimprovelearningoutcomes,especiallyforthosestudentsexperiencingdisadvantage,whilecounteringrisksthatunderminepositiveimpact.

Atarecentforum,theNetworkconsideredthechallengeofAIandharmfulcognitiveoffloading.Twocriticalleveragepointsemerged:

strategiestohelpteachersmosteffectivelydeployAI,drawingonthesubstantialevidenceofwhatalreadyisknowntoworkbestinteachingandlearningandbyexplicitlystructuringandscaffoldingthestudentuseofAI;and

educationaldesignofAItoolssothattheyamplifyteacherexpertisetobuild,notrelinquish,thestudentcognitiveeffortrequiredforlastingknowledge.

Thisreportoutlinesspecificpromisingpathways,backedbyevidence,thatalignwiththesepriorities,including:

¦usingexplicitteachingstrategiesthathelpstudentstooffloadlower-ordertaskswhilebuildingself-regulatedlearningcapabilityandcriticalthinking

¦bringingclearmetacognitivepromptsintothelearningprocesstoencouragedeeperinquiryandreflectionandhelpstudentsbecome

self-regulatingandmotivatedlearners

¦teachingexplicitlyandwithindomainknowledgethecriticalthinkingcapabilitiesthatwillhelpstudentsunderstand,evaluateandconsidercomplexcontent

¦ensuringteachersretainthenecessaryagencytohelpshapeandselectAItoolsthatwillsupporteffectivepedagogicalapproaches

¦acceleratingadoptionofthedraftnationaleducationdesignstandardsforAItools,toensuretheyaredesignedtobolsterstudents’learningeffort,masteryandcognitiveagency

ThepotentialoutsourcingoflearningtoAIintroduceshighstakesforstudents’successfulattainment

ofessentialbedrockknowledge,capabilitiesandcognitiveprocesses(seeOakleyetal.2025).Twodecadesago,therewasearlyevidenceofdigitaltechnologies’cognitiveimpact(Fogg,B.J.2003),aprecursoroftoday’sconcernsandAustralianactiononsocialmedia.Now,thereisincreasinglystrongevidencethatAIusedinschoolingmustalsobecloselygovernedanddirected,notonlyforsafetybuttoensurewehaveconfidenceintheAItoolsthemselvesandthatteachersarewell-supportedwitheffectivepedagogicalstrategies.ThisreportoutlinesthatwhileAImaybeanewtechnologicalvectorforeducation,thestrategiesforitssuccessfulintegrationrequireastrongpedagogicalresponse:enhancingthecentralroleofteachers;drawinguponwell-researchedapproachesforqualityteachingandlearning;andensuringcloseattentiontoequity.

WhileAImaybeanewtechnologicalvectorforeducation,thestrategiesforitssuccessfulintegrationrequireastrongpedagogicalresponse:enhancingthecentralroleofteachers;drawinguponwell-researchedapproachesforqualityteachingandlearning;andensuring

closeattentiontoequity.

Executivesummary

TherapidadoptionofAI(particularlygenerativeAI)presentsanovelchallengetoK-12education.Ithasthecapacitytofunctionasaninteractivecognitivepartner,bringingtheconceptofcognitiveoffloading(outsourcingmentalwork)totheforefront.

Thisreportanalysesthisphenomenonthroughthelensofhumancognitivearchitecture(CognitiveLoadTheory),framingthecentralproblemasaconflict:thecapacityofAItobypassthecognitiveeffortrequiredtobuildthedeep,long-termknowledge

thatunderpinsexpertiseandcriticalthinking.

Thereport’scentralfindingisacriticaldistinctionbetweentwoformsofoffloading:

+BeneficialoffloadingoccurswhenAIisusedtomanageextraneouscognitiveload(e.g.,checkinggrammar),freeingalearner’slimitedworkingmemorytofocusonessential,intrinsictasks.

+Detrimentaloffloading(outsourcing)occurswhenalearnerusesAItobypassthisintrinsiccognitiveeffort(thedesirabledifficulties)requiredtobuildlong-termknowledgeschemas.Thisoffloadingalsoseemstoextendtovitalmetacognitiveandself-regulatedlearningcapabilities,compoundingthenegative

impactofoutsourcingonlearning.

EmergingdatasupporttheobservationthatunstructuredAIusetrendstowarddetrimentaloffloading,creatingaperformanceparadox:students’short-termperformanceontasksimproves,whiletheirdurable,long-termlearningisharmed.

ThistrendappearstobedrivenbythefluencyofAI-generatedoutput,whichcreatesanillusionofcompetenceandencouragesmetacognitive

laziness,leadinglearnerstoabdicatethegenerativeeffortrequiredtobuilddeepknowledge.

TheimpactofAIisnotprimarilytechnologicallydeterministic;itispedagogical.Whileunstructureduseriskscognitiveatrophy,thereportfindsthatpedagogicallystructuredinterventions,suchasexplicitteaching,LoadReductionInstruction(LRI),andintegratedmetacognitiveprompts,cansuccessfullyfostertheself-regulatedlearning,criticalthinking

andthedeepengagementrequiredforlearning.

Executivesummary

NetworkforQualityDigitalEducation|Artificialintelligence,cognitiveoffloadingandimplicationsforeducation 7

Glossaryofkeyterms

Glossaryofkeyterms

Artificialintelligence

Abroadtermthatreferstoarangeofemergingandevolvingtechnologies.Whileacknowledgingthisdiversity,thereportuses“AI”asacollectivetermtoreferprimarilytogenerativeAI(likelargelanguagemodels)andautomateddecision-makingsystems(whicharesometimesreferredtoas‘AIagents’or‘agenticAI’).

AIagents(or‘agenticAI’)

Automateddecision-makingsystems.

Beneficialcognitiveoffloading

Occurswhenalearnerusesatool(likeAI)tooutsourceextraneousload(e.g.,checkinggrammar).Thisactionfreesuplimitedworkingmemoryresourcestofocusontheintrinsicworkoflearning(e.g.,structuringanargument,synthesisingsources).

CognitiveLoadTheory(CLT)

Aninstructionaltheorybasedonthestructureofhumanmemory.Itprovidesaframeworkfordesigningteachingthatrespectstheseverelimitsofworkingmemorytooptimisetheconstructionofschemasinlong-termmemory.

Cognitivemirror

ApedagogicalstrategywhereanAIisdesignedtoactasateachablenovice.TheAIfeignsconfusionandasksclarifyingquestions,whichforcesthehumanlearnertoengageintheeffortfulactofexplanationandreflection(knownastheProtégéeffect).

Cognitiveoffloading

Theformaldefinitionistheuseofphysicalactiontoaltertheinformationprocessingrequirementsofatasktoreducecognitivedemand.Itmeansoutsourcingmentalworktoanexternalresource.Whilewritingato-dolistisasimpleexample,AIallowsforoffloadingcomplextaskslikeanalysis,synthesis,andcreation.

Cognitivepartner

AtermusedtodescribeAIasaninteractive,fluent,andresponsivetool.

Unlikeasimplecalculator,anAIpartnercanbepromptedtoperformtheverycognitivetasks(likesummarising,analysing,andcreating)thataretraditionallyassociatedwiththeprocessoflearning.

Desirabledifficulties

Theconceptthatdurable,long-termlearningisnotmeanttobeeffortlessandrequiresadegreeofcognitiveeffortorchallenge.TheriskofAIisthatitmayencouragestudentstobypassthisessentialcognitivestruggle,whichharmstheirlong-termlearning.

Detrimentalcognitiveoffloading(outsourcing)

Occurswhenalearneroutsourcestheintrinsiccognitiveworkitself.Thisisanattempttobypasstheworkoflearning.AnexampleisaskingAIto“writemeanessay,”whichbypassestheentireschema-constructionprocess(generation,retrieval,analysis,synthesis).

Glossaryofkeyterms

Domain-specificknowledge

Thedeep,well-organisedfoundationofknowledgewithinaspecificfield

(e.g.,ascientist’sknowledgeofexperimentaldesignorahistorian’sknowledgeofsocialcontext).Thepaperarguesthatthisknowledge,storedinlong-termmemory,isthenecessaryfoundationforcriticalthinkinginmostcases.

Evaluativejudgement

Thecapabilitytomakedecisionsaboutthequalityofworkofoneselfandothers.AsdefinedbyTaietal.(2017),developingthiscapabilityisaproposedgoalofeducationtoenablestudentstoimprovetheirworkandmeetfuturelearningneeds.Itinvolvestwokeycomponents:understandingwhatconstitutesqualityandapplyingthisunderstandingtoappraisework.

Extraneousload

AconceptfromCognitiveLoadTheory,thisistheunnecessaryornon-essentialcognitiveloadimposedbyhowinformationispresented,ortheactivitieslearnersareaskedtodo(e.g.,confusinginstructions,distractinglayouts).Effectiveteachingaimstominimisethisload.

Fluency(inlearning)

Referstotheeaseofprocessinglearningmaterials,suchaswatchingahigh-qualityvideo.AIisdescribedas“fluencyondemand”becauseitsoutput

iscoherent,confident,andarticulate.Thisisdangerousasitcancreate

anillusionofcompetence,wherelearnersmistaketheeaseofprocessingforthedepthoflearning.

Generationeffect

Acognitiveprincipledemonstratingthatwhenstudentsareforcedtogenerateananswerfromacue(adesirabledifficulty),theyhave

significantlybetterlong-termvocabularyretentionthanstudentswhosimplyreviewthewordpassively.

Humancognitivearchitecture

Theunderlyingstructureofthemind’sinformation-processingsystems.Forthepurposesofteaching,itisunderstoodtohavetwokeyinteractingcomponents:workingmemoryandlong-termmemory.

Illusionofcompetence

Acognitivebiaswherelearnersgreatlyoverestimatehowmuchtheyhavelearned.ThefluencyofAI-generatedtextormultimediacancreatethisillusion,actingasamisleadingcuethatsignalstothelearnerthatdeepcognitiveengagementisnolongernecessary.

Intrinsicload

AconceptfromCognitiveLoadTheory,thisistheinherent,unavoidablecomplexityofthelearningmaterialitself.Thisisthe“good”loadassociatedwiththecoreconceptsandtheeffortfulprocessofbuildingschemas(thatcan,nonetheless,alsoleadtooverloadifthereistoomuch).

Glossaryofkeyterms

Learntheconceptgoal

Alearner’smotivationthatiscontrastedwithataskcompletiongoal.LearnerswiththisgoalaremorelikelytoactivelymodifyAI-generatedtext,whichleadstosignificantimprovementsintheirwork.

LoadReductionInstruction(LRI)

ApedagogicalframeworkthatadaptsexplicitinstructionprinciplesthatwasnotspecificallydevelopedforbuthasutilityforAI.ItinvolvesusingAItoprovidescaffolding,structuredpractice,andfeedbacktomanagethecognitiveburdenonthelearnerandenableprogressiveindependence.

Long-termmemory

Acorecomponentofhumancognitivearchitecture.Itisthevast,organisedstoreofallacquiredknowledge,experiences,andprocedures,anditscapacityisconsideredunlimited.Learningisdefinedastheprocessofintegratingnewinformationintolong-termmemorybybuildingschemas.

MatthewEffect(withAI)

AtermusedtodescribeaworryingmetacognitiveequitygapinanAI-mediatedworld.StudentswhoalreadyhavehighdomainknowledgeandstrongmetacognitionwilluseAItoacceleratetheirlearning.Incontrast,studentswithouttheseskillswillfallpreytodetrimentaloffloadingandfallfurtherbehind.

Metacognition

Theprocessofthinkingaboutone’sownthinking.Thisincludesessentialself-regulatedlearningprocesseslikeplanning,monitoring,andrevision.

Metacognitiveequitygap

Asignificantandnovelequityriskidentifiedinthisreport.ThisgaparisesbecausethecognitiverisksofAI(likemetacognitivelazinessandtheillusionofcompetence)disproportionatelyaffectnovicesandthosewithweakerself-regulationskills,thuspotentiallywideningexistingequitydivides.

Metacognitivelaziness

AtermcoinedbyFanetal.(2024)todescribehowtheconvenienceofAIcanunderminelearners’engagementinessentialself-regulatoryprocesses.Thelearner,ineffect,abdicatestheirmetacognitiveresponsibilitiestothetool,deprivingthemselvesoftheopportunitytodeveloptheseskills.

Metacognitiveprompts

Apedagogicalintervention,oftenintegratedintoanAIenvironment,designedtocountermetacognitivelazinessbyexplicitlydemandingandscaffolding

alearner’sself-regulatedlearning.Thesepromptsaredesignedtomakeuserspause,reflect,andassesstheirunderstanding,leadingtomoreactiveengagement,enhancedself-regulatedlearning,andimprovedmetacognitiveknowledge.

Outsourcing

Acommonlyusedtermdescribingdetrimentaloffloading.

Glossaryofkeyterms

Performanceparadox

AperformanceparadoxisidentifiedwhereAIcanboostastudent’sperformanceonanimmediatetaskwhilesimultaneouslydiminishingthedurablelearningthatisthegoalofeducation.Forexample,studentsusingAImaysolveproblemseffectively,buttheirlearningsuffersoncetheAIistakenawaybecausethescaffoldedperformancedidnottranslateintodurableknowledge.

Protégéeffect

Alearningbenefitthatoccurswhenapersonisforcedintotheeffortful,generativeactofexplanationandreflection.Thisisthemechanismtriggeredbythecognitivemirrorpedagogy.

Schemas

Complexknowledgestructuresinlong-termmemorythatorganiseinformationaccordingtohowitwillbeused.Learningistheprocessofbuildingtheseschemas.Anexpertissomeonewhohasbuiltvastandcomplexschemasintheirlong-termmemoryandknowswhenandhowtoapplythem.

Self-regulatedlearning(SRL)

Theabilitytomanageone’sownlearning.Thisinvolvesprocesseslikeplanning,monitoring,andrevision.ThereportnotesthatengaginginSRLitselfcreatesacognitiveload,whichiswhystudents,seekingefficiency,maybetemptedtooffloadtheseprocessestoAI.

Taskcompletiongoal

Alearner’smotivation,oftendrivenbyadesireforefficiency,thatcontrastswithalearntheconceptgoal.LearnerswiththisgoalaremorelikelytopassivelyacceptAI-generatedtext,whichcanleadtoadecreaseinthequalityoftheirwork.

Verificationpartner

ApedagogicalmodelthatreframesAI’sroleawayfrombeinganansweroracle.Inthismodel,thehumanlearnermaintainsprimarycognitiveagencyandisresponsibleforcontinuouslyevaluatingandcorrectingtheAI’soutput,therebyadoptingaverificationmindset.

Workingmemory

Acorecomponentofhumancognitivearchitecture.Itistheconsciouspartofthemindthatactivelyprocessesnewinformation(e.g.,holdingaphonenumberwhiledialling).Itsdefiningfeatureisthatitisseverelylimitedandcanonlyprocessaminimalnumberofnewinformationelementsatonetime.Exceedingthislimitcausescognitiveoverload,whichinhibitslearning.

ThetrueeducationalriskofAIisnotsimplythatstudentswilluseittocheatonanessay.ThefarmoreprofoundriskisthatAImayfundamentallyinterferewiththecognitiveprocessesofknowledgeconstructionandverification,theveryprocessesthatbuildthelongtermmemorystoresandsubsequentskillsuponwhich

themajorityofcriticalthinkingdepends.

Introduction

EvenbeforetheglobalimpactoftheCOVID-19pandemiconeducation,acleartrendwasemergingacrosseducationsystemsworldwidetowardtheincreaseduseofdigitallearningenvironmentsandtools.

Introduction

Thesetrendsextendbackmorethan30yearstowhenthefirstdigitaltechnologiessystematicallyimpactededucation.Theforcedmovetoonlinelearningduringthepandemicacceleratedthistrend,demonstratingwhatwaspossible,evenwithlittlepreparation.However,aswiththose

technologies,theflexibilityandengagementgrantedbynewdigitaltoolsoftencomewithacognitivecost(Lodge2023).Thatcostisbecomingprogressiv