IsArtificialIntelligenceGood orBadforEducation?
Artificialintelligence(AI) isnolongerafuturisticideaconfinedtosciencefiction. Inrecentyears,AIhasmovedrapidlyintoclassrooms,lecturehalls,andonline learningplatforms (source: https://education.illinois.edu/about/newsevents/news/article/2024/10/24/ai-in-schools--pros-and-cons). From personalizedtutoringsystemsandgradingassistantstoautomatedplagiarism detectionandAI-drivenchatbots,educationisundergoingaprofound transformation.Butwiththeseopportunitiescomesignificantchallenges.As schools,universities,andpolicymakersgrapplewiththistechnologicalshift,the debateintensifies:Isartificialintelligencegoodorbadforeducation?
Manyoftheprioritiesforbetteringteachingandlearningarestillunfulfilled today.Teacherslookforsafe,efficient,andscalabletechnology-enhanced methodstoachievetheseneeds.Teachersnaturallyquestionwhetherthequick changesintechnologyindailylifecouldbebeneficial.Intheirdailylives, educatorsutilizeAI-poweredserviceslikevoiceassistantsintheirhomes,tools thatcancreateessays,correctgrammar,andcompletesentences,andautomated travelplanningontheirphones,justlikeeveryoneelse.SinceAItoolshavejust beenmadeavailabletothegeneralpublic,manyinstructorsareactively
investigatingthem.Teachersseepotentialtoexpandthesupportprovidedto kidswithdisabilities,multilinguallearners,andotherswhocanbenefitfrommore adaptabilityandpersonalizationindigitallearningtoolsbyutilizingAI-powered featureslikespeechrecognition.TheyareinvestigatinghowAImayhelpthem writeorenhancelessons,aswellashowtheylocate,choose,andmodifycontent fortheirclasses.
Teachersarealsoconsciousofemergingdangers.Powerful,helpfulfeaturesmay alsocomewithadditionalsecurityandprivacydangers.Teachersareawarethat AIiscapableofautomaticallygeneratingincorrectorimproperoutput.Theyare concernedthatunintendedbiasesmaybeamplifiedbytheassociationsor automationsproducedbyAI.Theyhaveobservedfreshwaysinwhichpupils couldpassoffotherpeople'sworkastheirown.Theyarefullyawareof pedagogicaltechniquesand"teachablemoments"thatahumanteachercan addressbutthatAImodelsmissormisinterpret.Theyareconcernedaboutthe fairnessofalgorithmicrecommendations.Theworriesofeducatorsare numerous.Itisthedutyofeveryoneinvolvedineducationtousethepositive aspectsofAIintegrationinedtechtoforwardeducationalgoalswhile simultaneouslyguardingagainstpotentialrisks.
ThreeargumentsforaddressingAIimmediatelyweremadebyparticipantsinthe listeningsessions:
First,AIcouldmakeitpossibletoaccomplisheducationalgoalsmoreeffectively, morecheaply,andatalargerscale (source: https://www.faulkner.edu/news/the-future-of-learning-positive-applicationsof-ai-in-education/). AImayincreasetheadaptabilityoflearningresourcesto students'needsandstrengths.Addressingthediverseincompletelearningof studentsasaresultoftheepidemicisapolicypriority.Enhancingteachingisa toppriority,andAImayhelpteachersmorebywayofautomatedassistantsor othertechnologies.Whenteachersrunoutoftime,AImightalsoallowthemto continueprovidingsupporttospecifickids.Atopconcerniscreatingresources thataresensitivetotheexperiencesandknowledgethatstudentsbringtotheir education—theirculturalandcommunityassets—andartificialintelligence(AI) maymakeitpossibletobettertailorcurriculummaterialstolocalrequirements. AIhasthepotentialtoimproveeducationalservices,asdemonstratedbyvoice assistants,navigationtools,shoppingrecommendations,essay-writing capabilities,andotherwell-knownuses.
Second,worryoverpossiblefuturethreatsandawarenessofsystem-levelrisks giverisetourgencyandimportance.Forinstance,studentsmightbemore closelywatched.Althoughthe U.S.DepartmentofEducation adamantlydenies thatAImightreplaceteachers,someeducatorsareconcernedthattheymightbe replaced.Avoicerecognitionsystemthatstruggleswithregionaldialectsoran exammonitoringsystemthatmightunjustlyflagsomestudentgroupsfor disciplinaryactionaretwoexamplesofalgorithmicbias-baseddiscriminationthat thepublicisawareof.SomeapplicationsofAImightbeopaqueand infrastructural,raisingquestionsabouttrustandtransparency.AIfrequently appearsinnovelapplicationswithasenseofenchantment,buteducatorsand procurementregulationsdemandthatedtechdemonstrateeffectiveness. Artificialintelligence(AI)mayproduceinformationthatseemstruebutis erroneousorunfoundedinreality.Aboveall,AIposesnewrisksbeyondthewellknownonesrelatedtodatasecurityandprivacy,likethepotentialforpattern detectorsandautomationstoscaleandcause"algorithmicdiscrimination"(i.e., systematicunfairnessintheresourcesorlearningopportunitiesrecommendedto certainstudentpopulations).
Third,themagnitudeofpotentialunforeseenorunintentionalrepercussions createsurgency.TeachersmayfindunintendedrepercussionswhenAIallowsfor thelarge-scaleautomationofeducationaldecisions.Asabasicillustration, achievementinequalitiesmayincreaseifAIadjustsbyacceleratingthecurriculum forsomestudentsandslowingitforothers(basedoninsufficientinformation, subparideas,orskewedpresumptionsaboutlearning).Thequalityofthedata thatisnowaccessiblecanoccasionallyleadtosurprisingoutcomes.AnAIpoweredteacherhiringsystem,forinstance,wouldbethoughttobemore impartialthanonethatscoresresumesbyhand.However,theAIsystemmay deprioritizeapplicantswhocouldprovidebothtalentanddiversitytoaschool's teachingstaffifitisdependentonpastdataoflowquality.
Inconclusion,inordertotakeadvantageofimportantpotential,avoidandreduce emerginghazards,anddealwithunforeseenconsequences,AIineducationmust beaddressedimmediately.
Accordingtothe StanfordInstituteforHuman-CenteredAI's2025AIIndex Report (source: https://hai.stanford.edu/ai-index/2025-ai-index-report), there hasbeenanoticeableuptickinbothAIinvestmentandethicalresearch,including studiesonfairnessandtransparency.
TopTakeaways:
-Newbenchmarksintroducedin2023(MMMU,GPQA,SWE-bench)sawlarge performancegainsinoneyear(e.g.+18.8,+48.9,+67.3percentagepoints respectively).
-AIsystemsareincreasinglycapableatvideogenerationandprogrammingunder timeconstraints,occasionallyoutperforminghumansinrestrictedsettings.
-Inhealthcare,the FDA approved223AI-enabledmedicaldevicesin2023(versus just6in2015).
-Self-drivingandroboticmobilitysolutionsarescaling:e.g.Waymogiving 150,000autonomousridesweekly;Baidu’sApolloGorobotaxideployedacross Chinesecities.
-In2024,U.S.privateAIinvestmentreached$109.1billion—farexceeding China’s$9.3BandtheU.K.’s$4.5B.
-GenerativeAIalonedrew$33.9billionglobally,anincreaseof18.7%over2023.
-78%oforganizationsreportedusingAIby2024,upfrom55%in2023.
-U.S.institutionsproduced40“notable”AImodelsin2024,comparedto15in Chinaand3inEurope.
-U.S.federalagenciesproposed59AI-relatedregulationsin2024—morethan twicethenumberin2023.
-IntheU.S.,computingbachelor’sdegreeshavegrown22%overthepastdecade.
-AmongU.S.K–12CSteachers:81%believeAIshouldbeincludedinfoundational CSeducation,butlessthanhalffeelpreparedtoteachit.
-90%of“notable”AImodelsin2024originatedfromindustry(versus60%in 2023).
-Academiastillleadsinhighlycitedresearch.
-Scalecontinuestogrow:trainingcomputedoublesevery5months,datasets every8months,poweruseannually.
-Two NobelPrizes acknowledgeddeeplearningfoundations(physics)and applications(proteinfoldinginchemistry).
-The TuringAward alsohonoredadvancesinreinforcementlearning.
-WhileAImodelsperformwellonmanytasks(e.g.Olympiadmathproblems), theystrugglewithlogicandprecisereasoningbenchmarks(e.g.PlanBench).
-Thislimitationisespeciallyrelevantinhigh-stakesdomainswhereerror toleranceislow.
AIdevelopmentsarenotjustoccurringinresearchlabs;theyarealsogarnering attentionfromthegeneralpublicandpublicationsdevotedtoeducation.
AvarietyofideasandframeworksforethicalAI,aswellasforassociatedideas likehuman-centered,egalitarian,andresponsibleAI,havebeendevelopedby researchers.Participantsinthelisteningsessioncalledforexpandingonthese ideasandframeworkswhileacknowledgingtheneedtogofurther.Theypointed outthat,giventhespeedatwhichAIisbeingincorporatedintomainstream technologies,thereisanurgentneedforrulesandregulationsthatensurethe safeuseofAIadvancementsineducation.Together,policymakersand stakeholdersineducationmustbegindefiningtherequirements,disclosures, rules,andotherframeworksthatcanhelpcreateasecureandhappyfutureforall partiesinvolved,particularlykidsandteachers,aspolicycreationtakestime.
We'vehighlightedhowadaptivityisimpactedbyAIadvancements,butwe'vealso highlightedhowadaptivityisconstrainedbytheintrinsicqualitiesofthemodel. Wepointedoutthattheterm"personalized"wasemployeddifferentlyina previouswaveofedtech,andthatitwasfrequentlynecessarytodefinewhat personalizationmeantforacertaingoodorservice.Therefore,ourmain suggestionistoidentifytheadvantagesanddisadvantagesofAImodelsin upcomingedtechproductsandconcentrateonAImodelsthatcloselymatch desiredlearningvisions.Sinceartificialintelligenceisnowdevelopingquickly,we needdistinguishbetweenproductswithbasicAI-likecapabilitiesandthosewith morecomplexAImodels.
Thereisanoticeablepushandeffortbeingmadetoovercometheserestrictions whenwelookatwhatisoccurringinresearchanddevelopment.Wepointedout thatsincethereisnosuchthingasgenericartificialintelligence,decisionmakers shouldexercisecautionwhenchoosingAImodelsthatcouldlimittheircapacity forlearning.
Furthermore,wemustcontinueusingsystemsthinking,whichinvolvespeoplein theloopandtakesintoaccounttheadvantagesanddisadvantagesofthe particulareducationalsystem,asAImodelswillalwaysbemorelimitedthanrealworldexperience.Wemaintainthatthelearningsystemasawholeismore comprehensivethanjustitsAIcomponent.
PotentialBenefitsofAIinEducation:
-PersonalizedLearning:AIcantailoreducationalcontenttoeachstudent's individualpace,style,andneeds,leadingtodeeperengagementand understanding.
-IncreasedEfficiency:AItoolscanautomatetaskslikegradingandadministrative duties,freeingupeducators'timetofocusonteachingandstudentsupport.
-EnhancedAccessibility:AIcanprovideaccessto high-qualityeducational resources andvirtualtutoring,potentiallybridginggapsfordiverselearners.
-ImprovedFeedback:Studentscanreceivereal-time,detailedfeedbackontheir work,whichhelpsthemidentifystrengthsandweaknessesandimproveslearning outcomes.
-Data-DrivenInsights:AIcanprovideeducatorswithvaluabledataonstudent performance,helpingthemtoidentifytrendsandareasforinstructional improvement.
PotentialDownsidesofAIinEducation:
-PrivacyandSecurityRisks:AIsystemscollectandprocesssensitivestudentdata, raisingconcernsaboutdataprivacyandthepotentialformisuse (source: https://www.eschoolnews.com/digital-learning/2024/02/05/what-is-theimpact-of-artificial-intelligence-on-students/).
-AlgorithmicBias:AImodelscanperpetuateandevenamplifybiasespresentin thedatatheyaretrainedon,leadingtounfairorinequitableoutcomesin assessments.
-Over-RelianceonTechnology:StudentsmaybecometoodependentonAItools, whichcouldhinderthedevelopmentofessentialnon-cognitiveskillsandcreative problem-solving.
-ReducedHumanInteraction:Anoveremphasisontechnologymightleadtoless face-to-faceinteraction,impactingstudents'socialandemotionaldevelopment.
-ImplementationCostsandSkills:TheinitialcostofimplementingAIsystemscan behigh,andteachersmaylackthenecessaryskillsorresourcestousethesetools effectively.
Teachershaveafamouslydifficultprofessionbecausetheyhavetomake thousandsofjudgmentseveryday.Teacherstakepartin classroom operations, interactionswithstudentsoutsideoftheclassroom,collaborationwithother educators,andadministrativeduties.Theyarerequiredtoengagewithfamilies andcaregiversbecausetheyarealsomembersoftheircommunities.
Weconsiderhowmuchsimplersomedailychoreshavegotten.Weareableto sendandreceiveeventalertsandnotifications.Evenwithdigitalmusic,choosing themusicwewanttolistentousedtorequireanumberofsteps.However,these days,wecansimplysaythenameofasongwewanttohear,anditwillstart playing.Similartohowmappingarouteusedtoinvolvealaboriousstudyof maps,cellphonesnowallowustoselectfromavarietyofmodesof transportationinordertogettoourdestination.Whycan'teducatorsbegiven thetoolstheyneedtoimplementatechnology-richlessonplanandtheassistance theyneedtorecognizetheevolvingrequirementsoftheirstudents?Whyisitso difficultforthemtoarrangethelearningpathsoftheirstudents?Sinceclassroom dynamicsarecontinuallychanging,whydon'ttheresourcesavailableto instructorshelpthemquicklyadjusttotheneedsandskillsoftheirstudents?
Theloopthatdecideswhichresourcesareavailableandwhattheydointhe classroomisthemostcomprehensiveoneinwhichteachersshouldparticipate. Teachersarealreadyinvolvedinthedesignandselectionoftechnologies nowadays.Teacherscancommentonpracticalityandusability.Teacherslookat
efficacydataandreportbacktootherschooladministratorsontheirresults. Teachersalreadyexchangeideasabouthowtoeffectivelyusetechnology.
Theseworrieswillpersist,butAIwillalsogiverisetonewones.Theseworriesgo beyonddatasecurityandprivacy;theydrawattentiontothewaysinwhich technologymayunjustlyrestrictorguidesomekids'educationalopportunities. Oneimportantlessontobelearnedfromthisisthatinstructorswillrequiretime andassistancetostayuptodateonboththemorerecentandwell-known challengesthatareemerging,aswellastofullyengageinrisk-reductiondesign, selection,andevaluationprocesses.
Usingtheteacher'sknowledgeoftheneedsandstrengthsofeachstudent,AI couldassisteducatorsinpersonalizingandtailoringresourcesfortheirstudents. Customizingcurriculummaterialstakesalotofeffort,andeducatorsarealready lookingathowAIchatbotsmayassistthemincreatingnewmaterialsfortheir students.Anelementaryschoolteachercouldreceivestrongsupportforaltering astorybook'sillustrationstoexcitetheirkids,changingvocabularythatdoesn'tfit localspeechpatterns,orevenrewritingnarrativestoincludeadditional educationalcomponents.WepointedoutthatAImightbeusefulindetermining alearner'scapabilities.Whenastudentisinanotherteacher'sphysicsclass,for instance,amathteachermightnotbeawareofhowtheyareunderstanding graphsandtablesregardingmotions,andtheymightnotseethatutilizing comparablegraphsaboutmotioncouldaidintheirlessononlinearfunctions.By developingormodifyingeducationalmaterials,AImayassisteducatorsin identifyingandutilizingstudents'abilities.However,thefourpillarswe previouslydescribed—humanintheloop,equity,safetyandefficacy,and evaluationofAImodels—mustbeusedtoaddressthewideequityconcernsof preventingalgorithmicprejudicewhileenhancingcommunityandcultural responsiveness.
WenowaddanotherlayertoourcriteriaforgoodAImodelsbasedontheneeds ofteachers(aswellasstudentsandtheirfamilies/caregivers): explainability. SomeAImodelsareabletoidentifypatternsintheworldandtakethe appropriateaction,buttheyareunabletoprovideanexplanationfortheiractions (e.g.,howtheycametotheconnectionbetweenthepatternandtheaction). TeacherswillneedtounderstandhowanAImodelevaluatedastudent'swork andwhythemodelsuggestedaspecifictutorial,resource,ornextsteptothe student.Thislackofexplainabilitywon'tbeenoughforinstruction.
Therefore,ateacher'scapacitytoevaluateanAIsystem'sconclusiondependson howexplainableitis.Teacherscancreateappropriatelevelsofconfidenceand distrustinAIwiththeaidofexplainabilityAI,especiallywhenitcomesto identifyingareaswheretheAImodeltendstomakebaddecisions.Explainability isalsoessentialforteacherstobeabletospotinstancesinwhichanAIsystem canbeactingunfairlybasedonincorrectinformation.
Theconceptofexplainabilityrevolvesaroundtherequirementthateducatorsbe abletoexaminetheactionsofanAImodel.Forinstance,whichpupilsare receivingwhatkindsofinstructionalrecommendations?Inanever-endingcycle, whichkidsarereceivingremedialassignments?Whichareadvancing? Dashboardsinexistingproductsshowsomeofthisdata,butwithAI,educators mightwanttolearnmoreaboutwhichdecisionsarebeingmade,forwhom,and whatstudent-specificfactorsanAImodelhadaccessto(andperhapswhich factorshadanimpactonagivendecision).Someoftheadaptiveclassroomtools availabletoday,forinstance,uselimitedrecommendationmodelsthatonlytake intoaccountastudent'sperformanceonthelastthreemathproblems;they ignoreotherfactorsthatateacherwouldbeawaretotakeintoaccount,like whetherakidhasan IndividualizedEducationProgram(IEP) orotherneeds.
InformationabouthowdiscriminatorybiasmaymanifestinspecificAIsystems andwhatdevelopershavedonetoovercomeitisnecessarytosupportourplea forequalityissuestobetakenintoaccountwhenevaluatingAImodels.Thiscan onlybeaccomplishedbybeingtransparentabouthowthetoolsemploydatasets toachieveresultsandwhatdatatheyhaveonhandorthatateachermayuseto makedecisionsbutthatthesystemdoesnothaveaccessto(theexampleabove usesIEPstatus).
Additionally,teacherswillneedtobeabletoobserveandjudgeautomated judgments,likewhichsetofarithmeticproblemsastudentshouldworkonnext, forthemselves.Whentheydisagreewiththereasoningbehindaninstructional advice,theymusthavetheabilitytostepinandoverridedecisions.46When teachersexercisehumanjudgmentoveranAIsystem'schoice,theymustbe protectedfromunfavorableconsequences.
FormativeassessmentsmaybestrengthenedbyAImodelsandAI-enabled technologies.Forinstance,AIalgorithmscanbeusedtoassessaquestiontype thatasksstudentstodrawagraphorconstructamodel,andthencombine comparablestudentmodelsfortheteachertointerpret.Teachersmaybeableto
respondmoreeffectivelytostudents'comprehensionofatopiclike"rateof change"inacomplicated,real-worldscenarioiftheyuseenhancedformative assessment.Additionally,AImayprovidefeedbacktostudentsondifficultskills likespeakinga foreignlanguage orlearningAmericanSignLanguage,aswellasin otherpracticescenarioswherenohumanisavailabletoofferpromptinput.
Ingeneral,teachersmayfindthatanAIhelpercanlightentheirworkloadby evaluatingeasierpartsofstudentresponses,freeinguptheirspecialized judgmenttoconcentrateoncrucialelementsofalengthyessayorintricate project.Withaccessibility,wemightalsobeabletogivecommentsmore effectively.Withoutrequiringthestudenttoviewascreenortypeatakeyboard, anAI-enabledlearningtoolmight,forinstance,beabletospeakwiththemabout howtheyrespondedtoanessaypromptandgivethemquestionsthathelpthem toclarifytheirposition.
Asdemonstratedbytheexamplespresentedearlier,artificialintelligence(AI)can beintegratedintothelearningprocesstoprovidestudentsfeedbackwhilethey areworkingonaproblemratherthanaftertheyhavearrivedatanincorrect solution.Moreintegrationofformativeassessmentcanenhancelearning,and promptfeedbackisessential.
EventhoughtherearemanysimilaritiesbetweenAIandformativeassessments, ourlisteningsessionsalsoshowedthatparticipantswantedtoaddresssomeof theformativeassessment'scurrentdrawbacks,suchashowtime-consumingand occasionallyburdensometests,quizzes,andotherassessmentsare,aswellas howlittleteachersandstudentsvaluethefeedbackloop.
AfewAI-poweredtoolsandsystemsaimtoresolvethispossiblecontradiction. OneAI-enabledreadingtutor,forinstance,listenstostudentsreadaloudand offersimmediatefeedbacktohelpthemreadbetter.Studentsindicatedthat readingaloudwasenjoyable,andthemethodworked.Inordertoallowstudents todemonstratetheirmasteryof Newtonianphysics astheyprogressthrough increasinglychallenginggamelevels,researchershavealsoincorporated formativeassessmentsintogames.Ifstudentscanmorereadilyaskforand receiveassistancewhentheyarefeelingconfusedorfrustrated,itcanbea positivething.Todemonstratetheirlearning,studentsmustfeelsecure,certain, andtrustingofthefeedbackproducedbytheseAI-enabledtoolsandsystems.It isbesttoconcentrateonlearningprogressandgains(withoutunfavorable outcomesorahigh-stakessetting).
AI-enhancedformativeexamscouldpotentiallyfreeupteachers'time(suchas timespentgrading)sotheycandevotemoretimetostudentassistance. Teachersmayalsogainfromenhancedassessmentsiftheyoffercomprehensive insightsintostudents'needsorstrengthsthataren'talwaysapparentandifthey encourageinstructionalmodificationordevelopmentbyofferingalimited numberofrecommendationsbasedonresearchtoassiststudentsgraspthe material.Ifthesetestscangivefeedbackwhentheteacherisnotthere,such whenstudentsaredoingtheirhomeworkorrehearsingatopicduringstudyhall, theymightalsobeusefuloutsideoftheclassroom.Aswecoveredinthe Teachingsection,puttinginstructorsattheheartofsystemdesigniscrucialto implementingAI-basedformativeassessment.
Adoptiondecisionsarealsoheavilyinfluencedbyeducators,students,andtheir families/caregivers.WheneducatorschallengeoroverruleanAImodelbasedon theirprofessionaljudgment,parentsandleadersmuststandbythem. Technologydevelopersmustbeopenaboutthemodelstheyemploy,and legislatorsmayneedtoestablishtransparencystandardssothatthemarketmay operatebasedonknowledgeaboutAImodelsratherthanjustassertionsoftheir advantages.
Manykeyideas,suchashowtoarrangelearningactivitiesandprovidestudents withfeedbackwereincorporated.However,thefundamentalideawasfrequently deficit-based.Thealgorithmselectedpre-existinglearningmaterialsthatwould addressthestudent'sweaknessbyconcentratingonwhatwaswrongwiththem. WeneedtouseAI'scapacitytoidentifyandcapitalizeonlearnerstrengthsgoing future.Wealsoknowthatlearningisstronglysocialandthatpeopleare inherentlysocial,despitetheindividualistictechniquesofthelastyears (source: https://ijisae.org/index.php/IJISAE/article/view/5928/4680). Inthefuture,we mustdevelopAIcapabilitiesthatalignwithsocialandcollaborativelearning conceptsandvaluestudents'entirehumanskillset,notjusttheircognitiveability. Inthefuture,wemustalsoworktodevelopAIsystemsthatarebothculturally sensitiveandculturallysustaining,takingadvantageoftheexpandingbodyof documentedmethodsforthispurpose.Additionally,themajorityofearlyAI systemsofferedlimitedassistanceforEnglishlanguagelearnersandpupilswith disabilities.Inthefuture,weneedtomakesurethatlearningmaterialspowered byAIarepurposefullyinclusiveofthesepupils.Edtechthatenhanceseach student'scapacityfordecision-makingandself-controlinprogressively complicatedsituationshasnotyetbeendevelopedbythefield.Wemustcreate
educationaltechnologythatenhancesstudents'capacityforcreativelearningas wellastheircapacityfordiscussion,writing,leadership,andpresentation.
Additionally,weurgeeducatorstorejectAIapplicationsthatrelyonlyonmachine learningfromdata,withoutincorporatingknowledgefromexperienceand learningtheory.Ittakesmorethanjustprocessing"bigdata"tocreateequitable andsuccessfuleducationalsystems,andwhilewewanttousedatatogain insights,humaninterpretationofdataisalsocrucial.Weopposetechnological determinism,whichholdsthatdatapatternsalonedictateourcourseofaction. AIapplicationsineducationmustbebasedonwell-established,contemporary learningtheories,theknowledgeofeducationalprofessionals,andtheknowledge oftheeducationalassessmentcommunityonbiasdetectionandequity enhancement.
So,isAIgoodorbadforeducation?Theanswerisnotsimple.
AIoffersenormouspotentialtopersonalizelearning,improveaccess,andsupport teachers (source: https://www.nea.org/resource-library/artificial-intelligenceeducation). Itcanreduceadministrativeburdensandprovidevaluableinsights intostudentperformance.Atthesametime,itraisespressingconcernsabout privacy,ethics,inequality,andtheerosionofcriticalthinking.Ultimately,AIin educationisneitherinherentlygoodnorbad—itisatool.Likeanytool,itsimpact dependsonhowweuseit.Ifintegratedthoughtfully,withsafeguardsforethics andequity,AIcouldtransformeducationforthebetter.Ifadoptedrecklessly,it risksunderminingtheverygoalsoflearning.Thekeyliesinbalance:embracing innovationwhilepreservingthehumanheartofeducation.Teachers,students, andpolicymakersmustworktogethertoshapeafuturewhereAIempowers ratherthanreplaces,complementsratherthandominates.
Teachershavealreadyrisentothetaskofdevelopingbroadstandards,comingup withtargetedapplicationsfortheAI-enabledtoolsandsystemsthatarecurrently accessible,andidentifyingissues.However,itisimpossibletopredicthow educatorswillaffectAI-enabledgoodsinthefuture;instead,stakeholdersrequire policiesthatsupportthis.Woulditbepossibletoestablishanationalcorpsoftop educatorsfromeachstateandareatoserveasleaders?Couldwemakea commitmenttocreatingthesupportsforprofessionaldevelopmentthatare required?Canwefigureouthowtopayteacherssotheycanplayakeyrolein shapingeducation'sfuture?Teachersshouldbeallowedtoactivelyparticipatein thedevelopmentofAI-enablededucationalsystemsthankstothenewpolicies.
JeffPalmer isateacher,successcoach,trainer,CertifiedMasterofWeb Copywritingandfounderof https://EbookACE.com.Jeffisaprolificwriter,Senior ResearchAssociateandInfopreneurhavingwrittenmanyeBooks,articlesand specialreports.
Source: https://ebookace.com/is-artificial-intelligence-good-or-bad-foreducation/