2025年人工智能赋能学生参与度提升：全球新兴策略综述报告 AI for Student Engagement A Global Review of Emerging Strategies-数字教育委员会

AIforStudentEngagement

AGlobalReviewofEmergingStrategies

TableofContents

TableofContents

ExecutiveSummary3

UnpackingStudentEngagement4

TheShiftingLandscapeofStudentEngagementintheAIEra5

DeeperFaculty–StudentEngagement7

BroaderPeer-to-PeerExchange8

RicherStudent–ContentInteraction9

ResponsibleHuman-AICollaboration9

ThePracticalGuidetoAI-EnhancedStudentEngagement12

FacultyInteraction13

PeerExchange17

ContentandAssessment21

InstructionalDelivery27

ExperientialandAppliedLearning31

EnvironmentandInclusivity34

FromPracticestoImpact37

Contributors,CopyrightandContactDetails38

AIforStudentEngagement2

AIforStudentEngagement3

ExecutiveSummary

ExecutiveSummary

AIisreshapingstudentengagement,acomplexandmultifacetedfield.Yetinstitutionalefforts

remainfragmented,withlimitedclarityonhowAIcanmeaningfullyenhanceengagement.

ThisreportoffersafirstcomprehensiveglobalreviewofAIinstudentengagement.Drawingon106casestudies,itidentifies24emerging

methodologiesacrosssixengagementaspects:

·FacultyInteraction·PeerExchange

·ContentandAssessment·InstructionalDelivery

·ExperientialandAppliedLearning·EnvironmentandInclusivity

Eachmethodologyispresentedwithpractical

guidance:implementationcontexts,step-by-stepapplications,real-worldexamples,andobservedimpact.

AI’spresencehasalteredtherelationaldynamicsofengagement.Beyondintroducinganew

student–AIcollaborationitisreshapingtraditionalrelationshipsbetweenstudents,faculty,peers,

andcontent.Thisshiftrevealsfourkey

opportunities:DeeperFaculty–Student

Engagement,BroaderPeer-to-PeerExchange,

RicherStudent–ContentInteraction,ResponsibleHuman-AICollaboration

Groundedinglobalpractice,thisreportprovidesinstitutionswithapracticalguidetorethink

studentengagement,assesstheircurrentAIinitiatives,andchartaresponsiblepathforAIadoptionandinvestment.

AIforStudentEngagement4

UnpackingStudentEngagement

UnpackingStudentEngagement

AIisfundamentallychanginghowstudents

engagewithlearning.However,student

engagementisacomplexandmulti-layeredfield.TounderstandhowAIisreshapingitthisreport

focusesonsixkeyaspectsofengagement:howstudentsinteractwithfaculty,peers,andcontent,aswellashowtheyengagethroughinstructionaldelivery,appliedlearning,andthebroader

learningenvironment.

Whiletheseaspectsarehighlyinterconnectedeachcarriesitsowndistinctfocusand

characteristics.Together,theyprovidea

structuredlensthroughwhichtoanalyse

innovationinengagement.BymappingemergingusesofAIacrossthesesixareasthisreport

highlightswherepracticesarealreadymaturing,wherenewprioritiesaretakingshape,andwherenovelideasareonlybeginningtosurface.

6

Environment&Inclusivity

1

FacultyInteraction

5

Experiential

&Applied

Learning

2

Peer

Exchange

Student

Engagement

4

InstructionalDelivery

3

Content&Assessment

Figure1.SixKeyAspectsofStudentEngagement

ContextualAspectof

RelationalAspectof

StudentEngagement

StudentEngagement

FacultyInteraction

Studentrelationshipwithfaculty,includingmentorship,guidance,andfeedback.

PeerExchange

Studentscollaborate,exchangeideas,andconstructunderstandingwithoneanother.

Content&Assessment

Studentsinteractwithdisciplinaryknowledgeandstructuredlearningactivities.

InstructionalDelivery

Studentsperceiveandrespondtotheclarity,presence,andstyleofinstructionalapproaches.

Experiential&

AppliedLearning

Studentsconnectlearningtoauthentic,applied,andimmersivecontexts.

Environment&Inclusivity

Studentsfeelsupportedthroughinclusiveandaccessibleenvironments.

AIforStudentEngagement5

TheShiftingLandscapeofStudentEngagementintheAIEra

Whilethesixaspectsofengagementprovideausefulframework,theydonotplayoutinthe

samewayacrosseverylearningcontext.

Engagementlooksverydifferentdependingonthesetting,whetherstudentsareoncampusoronline,andwhetherinteractionshappen

synchronouslyorasynchronously.

Innovationsinstudentengagementarelikewisenotone-size-fits-all.Certainapproachesaremore

effectiveinparticularcontexts.Toaccountforthis,thereportrecognisesthevariedformsofengagementacrossdeliverysettingsand

analysesemerginginnovationsinrelationtothecontextswheretheyarebestsuited.

ThisbreakdownprovidesamorenuancedviewofhowengagementhappensinpracticeandwhereAImayshapeitindistinctways.

Figure2.StudentEngagementAcrossLearningSettings

Asynchronous

GuidingSelf-DirectedLearning

·Reviewinglecturerecordingsandhandouts·Completingpre-classreadingsortasks

·Independentstudy

·Projectworkandassignmentscoordinatedoutsideclass

·Asynchronouspeercollaboration

SustainingMotivation&Continuity

·Watchingrecordedlecturesatownpace·Participatinginforumsordiscussion

boards

·Completingself-pacedquizzesandinteractiveexercises

·Gamifiedprogress:badges,levels,micro-credentials

Synchronous

DeepeningHumanConnection

·Livelectures,seminars,Q&A

·Groupdiscussionandproblem-solving

·Hands-onlabs,workshops,andstudios

·Real-timeQ&Aandfeedbackfromfaculty·Informalpeer&facultyinteractions

FacilitatingActiveDigitalInteraction

·Attendinglivelecturesandwebinars·Breakoutroomgroupactivities

·Virtualmentoringsessions

·Peercollaborationthroughshareddigitalworkspaces

·Virtualnetworkingandcommunityevents

On-Campus

Online

TheShiftingLandscapeofStudentEngagementintheAIEra

PlanningAIadoptioninhighereducationrequiresinstitutionstocarefullyassessthechangesAI

introduces,identifykeyopportunities,andallocateresourcesstrategically.

Atitscore,studentengagementisrelational,

shapedbythevariousrelationshipsthatmakeup

theoverallstudentexperience.Viewedthrough

thislens,AInotonlycreatesanewdirectlinkwithstudentsbutalsoreshapesthreetraditional

relationships:studentswithfaculty,studentswithpeers,andstudentswithcontent.These

interactionsformthefocalpointofthisreport’sanalysis.

TheShiftingLandscapeofStudentEngagementintheAIEra

AIforStudentEngagement6

Figure3.ThreeDimensionsofRethinkingAssessmentintheAgeofAI

RelationsTraditionalInteractionShifttoAI

Student–Faculty

FacultyasPrimarySourceofFeedback&Guidance

·Studentsseekfeedbackfromfacultyonassignments.

·Studentsaskquestionsduringofficehoursorviaemail.

Theme:Facultyprovidevalidation,clarification,andexpertguidance

>

AIasanInstantResponder

·StudentsreceiveinstantfeedbackfromAI.

·StudentsaskAIforinstantresponsestoquestions.

Theme:AIreplacesthewaitforhumanfeedbackwithimmediacy

Student–Peers

PeersasSupport&Perspective-Sharing

·Studentsaskpeersforhelpwithcontentunderstandingand

assignments.

·Studentsexchangeideaswithpeersfordiverseperspectives.

Theme:Peersserveascollaboratorsandco-learners.

>

AIasanAlternativePerspectiveSource

·StudentsaskAIforalternativeperspectives(insteadofpeers).

·StudentsuseAIforsummariesandcontentexplanations.

Theme:AIcanprovidebreadthandmultipleviewpointsbeyondwhattextbooksorpeersmightoffer.

Student–Content

ContentasMainLearningMedium

·Studentsreadtextbooks,attendlectures,andtakenotespassively.

·Studentscompleteassignmentsindependently.

Theme:Contentconsumptionandindependentstudyarecentral.

>

AIasaProductivityTool

·StudentsuseAItosummarise,

transcribe,andtakenotesforlectures.

·StudentsuseAIforanalysisandproblem-solving.

Theme:AIhandlesmechanicaland

cognitiveload,freeingstudentsforhigher-orderthinking(orpotentiallyresultingin

over-reliance).

Withcapabilitiessuchasgeneratinginsightsanddeliveringinstantresponses,AIincreasingly

servesasthe“frontline”ofinteraction.StudentsoftenturnfirsttoAIforfeedback,explanations,andsupport,sometimesbypassingtraditional

humaninteractionswithfacultyandpeers.Thisshifthasmixedeffects:whileAIcanimprove

efficiencyandpersonaliselearning,over-reliance

mayweakencriticalengagementwithcontentanddiminishmeaningfulhumaninteraction.

Theseevolvingdynamicshighlighttheneedforintentionalpedagogicaldesign,leveragingAItostrengthen,ratherthanreplace,core

relationships.Whenintegratedthoughtfully,AIcanenrichengagementacrossalldimensionsofthestudentengagement.

TheShiftingLandscapeofStudentEngagementintheAIEra

AIforStudentEngagement7

Figure4.FourEmergingOpportunitiesinStudentEngagement

2

Broader

Peer-to-PeerExchange

AIcanexpand

collaborativelearning

opportunities,enabling

studentstoexchange

ideasbeyondimmediatepeergroupsandexposingstudentstomorediverseperspectives.

3

Richer

Student–ContentInteraction

AIcanprovideinteractiveandpersonalisedaccesstolearningmaterials,

enrichingtheengagementwithcontent.

4

Responsible

Human–AI

Collaboration

Byguidingstudentsin

effectiveandresponsibleuseofAI,institutionscanfostermeaningfulhuman–AIcollaborationwhile

developinghuman-centredskills.

1

Deeper

Faculty–StudentEngagement

AIcanfreefacultyfromroutinetasks,allowingdeeper,higher-level

interactionsand

personalisedguidance.

DeeperFaculty–StudentEngagement

AIhasthepotentialtoshiftthefaculty–student

relationshipfromoneanchoredintransactionsoflecturing,grading,andfeedbacktoonerootedinmeaningfulconnection.Byoffloadingroutine

taskstoAI,AIallowsfacultytodedicatemore

timetohigher-levelengagement—mentoring,

criticaldialogue,andauthenticrelationalbuilding.

TherealopportunityliesinusingAIasan

intelligencelayerthatrevealspatternsoflearningandengagementonceinvisibletofaculty:

·Collectingengagementdata—capture

signalsfromawiderangeoflearningactivities:

AItutorenquiries,in-classparticipation,andassessmentbehaviours.

·Integratingdatastreams—connecting

fragmentedcourse,assessment,andplatformrecordsintoaholisticlearnerprofile(“digitaltwins”).

·Generatinginsights—usingAItosurfaceactionableinsightssuchasstudents'weakpoints,suggestedteachingmaterials,

personalisedpathways,andtimelyinterventions.

Currently,manyinstitutionsonlycapture

fragmentsofthispicture.Engagementdatais

oftensiloedbycourseorassessment,limitingAI’sabilitytoprovidefacultywithaholisticview.

Figure5.StudentEngagementAcrossLearningSettings

AIasan

Intelligence

LayerBridgingStudent–FacultyEngagement

StudentLearningDataAIAnalysisActionableInsights

TheShiftingLandscapeofStudentEngagementintheAIEra

AIforStudentEngagement8

BroaderPeer-to-PeerExchange

AIcanbroadenthescopeofpeerengagementbyexposingstudentstomorediverseperspectivesandfacilitatingricherdialogue.Insteadofrelyingonlyonlimiteddiscussionself-preparationand

immediateclassmates,AIcanexpandidea

generation,widenthecircleofexchange,andhelpstudentsengagewithdifferencemore

intentionally.

ThefoundationofthisshiftrestsonthreekeyAIcapabilities:

·Providingdiverseviewpoints—AIgeneratesalternativeperspectivesandangles,ensuringstudentsengagewithawiderrangeofideas.

·Matchingacrossdifferences—AIcanconnectstudentswithpeerswhoholdcontrastingpositionsorcomplementaryexpertise,fosteringdebateandbalance.

·Guidingpeerfeedback—AIoffersstructuredpromptsandevaluationcriteria,helping

studentsreviewpeerworkwithmoredepthandfrommultipleangles.

However,AI’sabilitytogenerateinsightscanbeadouble-edgedsword:whileitbroadens

perspectives,itmayalsohinderthedevelopmentofcreativeandcriticalthinkingskills.Students

coulduseAItoolstogeneratecontentwithoutengagingincriticalthinkingoraddingtheirowninsights.This"passivecreativity"risksreducingtheoriginalityanddepthoftheirwork.

Currentpeer-to-peerlearningisstilllargely

boundedbyclassroomcohortsandlacksstrongmechanismsforsurfacingcontrastingordiverseperspectives.EarlyexperimentswithAI,suchaspeermatchingandstructuredpeerfeedback

support,showpromise,butremainexploratory.

Figure6.ThreeKeyComponentsofHowAICanBroadenPeer-to-PeerExchange

ProvidingDiverseViewpoints

AIgeneratesalternativeperspectivesand

angles,ensuringstudentsengagewitha

widerrangeofideas.

Broader

GuidingPeerFeedback

AIoffersstructuredprompts

andevaluationcriteria,helpingstudentsreviewpeerworkwithmoredepthandfrommultipleangles.

MatchingAcrossDifferences

AIcanconnectstudentswithpeerswhoholdcontrastingpositionsorcomplementaryexpertise,fosteringdebateandbalance.

Peer-to-PeerExchange

TheShiftingLandscapeofStudentEngagementintheAIEra

AIforStudentEngagement9

RicherStudent–ContentInteraction

AIisbecominganaturallayerinhowstudentsengagewithlearningmaterialsandassessment.

Institutionsmustadapttothisnewrealityby

intentionallydesigninginteractionssothatAI

enhanceslearningratherthanenablingshortcutstoavoidsuperficiallearning.

Twokeyareasofinnovationareemerging:

1.Interactiveengagementwithmaterials

·EmbeddingAI-driveninteractionpointswithinreadings,videos,andotherresources

transformspassivestudyintoactivelearning.Prompts,explanations,oradaptivequestionsensurestudentsarenotonlyconsuming

contentbutalsocriticallyengagingwithit.

2.AI-integratedassessment

·ByintentionallyembeddingAIintoassessmenttasks,institutionscancreateactivitiesthatarebothAI-resilientandskills-enhancing.StudentsareguidedtouseAI,developingstronger

disciplinaryskillswhilealsobuildingAIliteracy.

AI-IntegratedAssessment

TheNextEraofAssessment,ajointreportbytheDigitalEducationCouncilandPearson,providesthefirstcomprehensivereviewofhoweducatorsworldwideareredesigningassessmentwithAI.

Drawingon101globalcasestudies,thereportidentifies14emergingAI-integratedassessmentdesignmethodologies,whichenableglobaleducatorsinbuildingricherstudent-contentinteractionusingAI.

ResponsibleHuman-AICollaboration

AsstudentsincreasinglyturntoAIastheirfirst

pointofinteractionforstudyandproblem-solving.AccordingtotheDigitalEducationCouncilGlobalAIStudentReport2024,86%ofstudentsuseAIfortheirstudies.Institutionsmusttake

responsibilityforguidingthisemerginghuman–AIrelationship.

ResponsibleengagementwithAIrequiresmorethantechnicaltraining.StudentsmustbeguidedtouseAIeffectivelywhiledeveloping

complementaryhumancapabilitiesthatpreservedepthandoriginalityinlearning.Threeareasareparticularlycritical.

DigitalEducationCouncilGlobalAIStudentReport2024.

AIforStudentEngagement10

Figure7.KeyAIandHuman-CentricSkillsforResponsibleHuman-AICollaboration

TechnicalSkill

Human-CentricSkill

CriticalThinking

Enablestudentsto

evaluateAI-generated

content,verifysources,detectmisinformation,

identifybiases,andapplylogicalreasoningwhenengagingwithAI.

EthicalUseofAI

Human-CentricityandCreativity

UnderstandingAI

Ensurestudents

understandAIethics

principles,recognise

potentialrisks(suchasmisinformationandbias),andimplement

responsibleAIusepractices.

Emphasisethe

importanceofhuman

skillssuchascreativityandemotional

intelligence,ensuringstudentsuseAIinwaysthatcomplementratherthanreplacehuman

capabilities.

Ensurestudentsbuilda

foundational

understandingofhowAIsystemswork,the

principlesofdata

collection,processing,

andinterpretation,andtheimplicationsofAI-

generatedoutput.

Criticalthinking-longacornerstoneof

education,hasbecomeevenmoreessentialin

theageofAI.Itenablesstudentstoverifythe

qualityandaccuracyofAI-generatedoutputandassessrelevancetotheirspecificneeds.WhileAIcangeneratevaluableinsights,theabilityto

evaluate,question,andrefinetheseoutputsiswhatpreventserrors,biases,andsuperficialsolutionsfromtakinghold.

EthicaluseofAI-TheresponsibleuseofAIrequiresstudentstorecognisepotentialrisks

suchasbias,misinformation,anddiscriminatoryoutcomes.DevelopingethicalawarenessallowsstudentstointerrogateAIoutputs,contextualisethemappropriately,andapplythemresponsibly.

Human-centricskillandcreativity-AsAI

increasinglyautomatesroutinetasksand

mediatesinteractions,corehumancapabilities

suchascommunication,empathy,collaboration,andcreativitymustbereinforced.Institutions

shouldintegrateAIinwaysthatenhancethese

skills,ensuringthatstudentscontinuetopracticeandrefinethehumandimensionsoflearning.

AILiteracy

TheDigitalEducationCouncil’sAILiteracyFrameworkdefinesfivedimensionsofAILiteracy:

·UnderstandingAIanddata

·CriticalThinkingandJudgement·EthicalandResponsibleAIUse

·Human-Centricity,EmotionalIntelligence,andCreativity·DomainExpertise

Foreachdimension,theFrameworkoutlinesthreecompetencylevelsofAIliteracywithexamplecompetenciesanddetailedexampleactionsforprogression.

ThePracticalGuidetoAI-Enhanced

StudentEngagement

AIforStudentEngagement12

ThePracticalGuidetoAI-EnhancedStudentEngagement

ThePracticalGuidetoAI-EnhancedStudentEngagement

HighereducationinstitutionsareincreasinglyexploringavarietyofAIapplicationsaimedatenhancingstudentengagement.However,thesectorremainsinanearlyexperimentalphase,withnumerouspilotsandtrialsunderway.

Drawingon106globalcasestudies,thissectionidentifies24emergingmethodologiesforusingAItoenhancestudentengagement,offeringa

rangeofapproachesthatcanguideinstitutionsinoptimisingAIintegrationineducation.

Thesemethodologiesprovideasnapshotof

currentpracticesandexperimentationacross

institutions—rangingfrommature,well-

establishedapplicationstonovelapproachesthatareonlybeginningtobeexploredandstudied.

Eachmethodologyispresentedwithpracticalguidance,includingdescription,implementationcontexts,step-by-stepapplications,real-worldexamples,observedimpact,andkeysuccessindicators.

Figure7.24EmergingMethodologiesforAI-EnhancedStudentEngagement

Peer

Exchange

AI-Supported

Asynchronous

Discussion

Board

AI-GeneratedPromptsforSynchronousDiscussions

AI-Mediated

Peer

Discussions

AI-ModeratedBreakoutRooms

FacultyInteraction

AI-EnhancedTeachingAssistant

AI-Customised

Instructor-Like

Feedback

AI-Enhanced

Faculty

Feedback

PredictiveAnalytics

InstructionalDelivery

AI-Enhanced

Flipped

Classroom

AvatarTeaching

AdaptiveMicro-Learning

AIReal-timeInstructorCoaching

Experiential

andApplied

Learning

EnvironmentandInclusivity

AIfor

Role-Playing

AILive

Captioning,Transcription,

Translation

PhysicalObject-BasedAI

Simulation

AI-EnhancedXR

AIforInclusiveContentCreation

AILearning

Management

Assistant

ContentandAssessment

AI-Generated

Multi-Level

Explanations

AI-Created

Engagingand

RelevantContent

AITutor

AI-SupportedInteractiveReading

AIReal-Time

Feedbackfor

Students

AI-GeneratedMemory

RetentionExercises

AIforStudentEngagement13

FacultyInteraction

AI-EnhancedTeachingAssistant

Description

UsingAIasasupplementarytoolforTeachingAssistantsinvolvesintegratinggenerativeAI(e.g.,ChatGPT)intoTA-ledinstructionandsupportsessions.RatherthangivingstudentsdirectaccesstoAI,TAsuseittoenhanceteachingefficiencyandquality,suchasgeneratingexercises,clarifyingconcepts,

providinghints,debuggingcode,andgivingfeedback.

·SuitableSettings:Online/On-SiteSynchronous

·MaturityLevel:Emerging,withfewinstitutionsexperimenting·ToolRequired:AdedicatedAI-poweredtoolisrequired

PracticalGuide

CaseStudy

TehranPolytechnic&ChatGPT-AugmentedTA(2024)

InaDataStructuresandAlgorithms(DSA)course,teachingassistants(TAs)usedChatGPTasa

supplementarytooltoimproveteachingquality,

Step-by-StepInstruction

1.Preparation-DesignstructuredAIprompts

tailoredtocoursecontent(e.g.,exercises,codesnippets,problemscenarios).

RefineAIoutputstoensurecorrectness,

pedagogicalclarity,andalignmentwithlearningobjectives.

2.DuringTASessions/OfficeHours-UseAItogenerateexampleexercises,hints,and

clarificationsinrealtime:

·VerifyandeditAIoutputsbeforepresentingtostudents.

·Guidestudentsthroughstep-by-step

reasoningusingAI-generatedmaterialsasascaffold.

guidedbystructuredpromptsandhumanverification.

Implementation:

·40undergraduatesweresplitintotwogroups:onewithtraditionalTAsupport,theotherwithTA+ChatGPTassistance.

·TAsusedstructuredprompts(problem,traits,algorithm,real-worldcase,code).ChatGPT-4ogeneratedexercises;ChatGPT-o1handled

advancedreasoning.Alloutputswereverified

3.EvaluationandFeedback-ComparestudentperformancewithandwithoutAI-enhancedTAsupport.AdjustAIpromptsandusagestrategiesbasedonobservedlearninggapsor

misconceptions.

andrefinedbeforeuse.

·AI-assistedproblemsetsandstep-by-stepexplanationsguidedstudentsthrough

complextopics.TAsfacilitatedexercises,feedback,andcomparisonswiththenon-AIgroup.

Impact:PreliminaryresultssuggestthatstudentsintheTA+ChatGPTgroupscored16.5pointshigheronaveragethantheTA-onlygroup(p<0.001).Improvementwasmostsignificantincomplextopics

likerecursionanddynamicprogramming.

ImpactIndicators

·AcademicPerformance:Compareexamscores,assignmentgrades,andtopic-specificmastery(e.g.,recursion,dynamicprogramming)betweenAI-assistedandTA-onlygroups.

·TAEfficiency:TrackTApreparationtimeandabilitytoprovidepersonalisedfeedback.

FacultyInteraction

AIforStudentEngagement14

AI-CustomisedInstructor-LikeFeedback

Description

InthismethodologygenerativeAI(chatbot/assistant)istrainedoncourse-specificinstructormaterials(pastfeedback,modelanswers,rubrics,exemplarcomments)soitcangivestudentsformative,

instructor-styleguidance.TheAIactsasa24/7“checkpoint”thatechoescourseexpectationsandtone.

·SuitableSettings:OnlineAsynchronous

·MaturityLevel:Emerging,withfewinstitutionsexperimenting·ToolRequired:AdedicatedAI-poweredtoolisrequired

PracticalGuide

CaseStudy

UniversityofWashington&AI-enhancedInstructor-StudentFeedbackLoop(2024)

Step-by-StepInstruction

1.Definegoals&policy-decidewhatthebotmayandmaynotdo(draftfeedbackonly,nograding;allowed/forbiddencontent),publishanAI

statementinthesyllabus.

2.Assembletrainingcorpus-collectpastfeedback,rubrics,annotatedstudentdrafts,exemplarcomments,andinstructornotes.

AssociateProfessorKatyPearcedeveloped

course-specificAIchatbotstrainedonyearsofherownassignmentfeedback.

Implementation:

3.Designprompts/behaviour-codifytone,

depth,andscope(e.g.,“giveinstructor-style

formativefeedbackfocusedonthesisclarity,

evidence,andstructure;suggest2nextsteps”).

·Pearcecollectedpastfeedbackacross

multipleyearsofteachingthesame

assignmentandtrainedachatbotto

approximateherfeedbackstyle,tone,andexpectations.

4.Train/configurethebot-fine-tuneoruseRAG(retrieve+generate)togroundanswersinthe

coursecorpus;addguardrails(refuseonpolicy-violatingprompts).

·Studentssubmittedadraftandaskedthechatbotforfeedback.

·ThechatbotprovidedPearce-styleformativeguidanceonthesisclarity,argumentstrength,structure,andevidenceuse.

5.Integrate&launch-embedinLMSorprovideaclearaccesspoint

Studentsiteratedontheirdraftsmultipletimessincethebot“nevergetstired.”

6.Monitor&QA-spot-checkoutputsregularly,samplethreadsforhallucinations/bias,log

problematicresponses.

Impact:Studentswhonormallyavoidedofficehoursoraskingforhelpengagedwiththechatbotfrequently.Studentssubmittedmorepolisheddrafts,reportingthattheirworkhadalreadybeen“checked”beforesubmission.Furtherresearchisneededtotesttheaccuracyofthefeedback.

ImpactIndicators

·FeedbackFidelity:%ofAIrecommendationsthatinstructorsmarkas“useful/accurate”inspotchecks.

AIforStudentEngagement15

PredictiveAnalytics

Description

ThismethodologyusesLMS,SISandadvisingdatatopredictengagementandpersistencerisk,

producingrisktiersforearlyaction.Providescourse-andprogramme-levelinsightswithbuilt-in

outreachworkflows,usinginstitution-specificmodelsdesignedfortransparency,fairnessandregularcalibration.

·SuitableSettings:Online/On-CampusAsynchronous

·MaturityLevel:Mature,implementedbyanumberofinstitutions·ToolRequired:AdedicatedAI-po