Handbook on Intelligent Techniques in the Educational Process: Vol 1 Recent Advances and Case Studies

399 Pages·2022·10.024 MB·English

by  Mirjana Ivanović, Aleksandra Klašnja-Milićević, Lakhmi C. Jain

Learning and Analytics in Intelligent Systems 29
Mirjana Ivanović
Aleksandra Klašnja-Milićević
Lakhmi C. Jain   Editors
Handbook
on Intelligent
Techniques in
the Educational
Process
Vol 1 Recent Advances and Case Studies
Learning and Analytics in Intelligent Systems
Volume 29
SeriesEditors
GeorgeA.Tsihrintzis,UniversityofPiraeus,Piraeus,Greece
MariaVirvou,UniversityofPiraeus,Piraeus,Greece
LakhmiC.Jain,KESInternational,Shoreham-by-Sea,UK
Themainaimoftheseriesistomakeavailableapublicationofbooksinhardcopy
form and soft copy form on all aspects of learning, analytics and advanced
intelligentsystemsandrelatedtechnologies.Thementioneddisciplinesarestrongly
related and complement one another significantly. Thus, the series encourages
cross-fertilization highlighting research and knowledge of common interest. The
series allows a unified/integrated approach to themes and topics in these scientific
disciplines which will result in significant cross-fertilization and research dissem-
ination. To maximize dissemination of research results and knowledge in these
disciplines, the series publishes edited books, monographs, handbooks, textbooks
andconferenceproceedings.
IndexedbyEICompendex.
Moreinformationaboutthisseriesathttps://link.springer.com/bookseries/16172
· ·
Mirjana Ivanovic´ Aleksandra Klašnja-Milic´evic´
Lakhmi C. Jain
Editors
Handbook on Intelligent
Techniques
in the Educational Process
Vol 1 Recent Advances and Case Studies
Editors
MirjanaIvanovic´ AleksandraKlašnja-Milic´evic´
FacultyofSciences FacultyofSciences
DepartmentofMathematics DepartmentofMathematics
andInformatics andInformatics
UniversityofNoviSad UniversityofNoviSad
NoviSad,Serbia NoviSad,Serbia
LakhmiC.Jain
KESInternational
Selby,UK
ISSN 2662-3447 ISSN 2662-3455 (electronic)
LearningandAnalyticsinIntelligentSystems
ISBN 978-3-031-04661-2 ISBN 978-3-031-04662-9 (eBook)
https://doi.org/10.1007/978-3-031-04662-9
©TheEditor(s)(ifapplicable)andTheAuthor(s),underexclusivelicensetoSpringerNature
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Preface
Asoneofthecrucialsectorsofsociety,educationhasasubstantialimpactonalmost
allothersectors.Differentcomputer-supportededucationalsystemshavebeendevel-
oping for many decades with the intention to make the process of teaching and
learningeasierandmoreconvenientinmodern,dynamicsociety.Influencesofrapid
development of ICT and other related technologies on developing more and more
quality,sophisticatededucationalsystemsareunavoidableandevident.Societalchal-
lengestofurtherdevelopmentofeducationalsystemsfordifferentdomains,purposes,
andlevelsofeducationaremanifoldandarenotlimitedonlytospecificsituations
liketherecentoneconnectedtotheCOVID-19pandemic.
Over the years, the use of e-learning and tutoring systems brought numerous
advantagesandbenefitsoverthetraditionalteachingmethods.Researcheffortsare
focusedonimprovingtheoverallperformancesandfunctionalitiesofthesesystems
furtheremployingemergenttechnologies.Attentionisespeciallypaidtothedesign
ofe-learningarchitecturesthatsupportadaptabilitytostudents’personalneedsand
learninghabits.Inthelastdecade,thearchitecturesthatofferahighlevelofperson-
alizationandintelligentservicesandprovidesupporttoimprovethemotivationof
learners,andbetterlearningoutcomesaredominant.
Nowadays, intensive development and wide applications of AI techniques and
approachessignificantlyinfluencetheeducationalsectorandthedevelopmentofa
range of sophisticated intelligent educational systems. We are witnessing that the
futureofeducationiscoupledwithtechnologiesandtheiradvancements.Theappli-
cationsofAIineducationalprocessesarenumerousstartingfromintelligenttutoring
systems(ITS),smartlearningenvironments,towardstheuseofvirtualandaugmented
realityandrobots.
ArtificialIntelligencehasthepotentialtoaddresssomeofthebiggestchallenges
in education today, but also in the future in order to establish innovative teaching
and learning practices, and ultimately accelerate the progress and performance of
learning.
v
vi Preface
This book presents a collection of 17 chapters that bring interesting aspects of
the state-of-the-art of application of intelligent techniques in different educational
processesandsettings.Chaptersarefocusedondescribingthevarietyofapproaches
in diverse educational domains and levels of education; discuss their capabilities,
benefits,andpossiblelimitationsinpracticaluse.
Wehopethattheworkspresentedinthebookwillbeofinteresttoreaders,will
motivateourcolleaguesandresearcherstoapplypresentedandsimilarapproaches,
trytoenhancethem,andproposebetterandmoreadvancedsolutions.
Chapter1“CurrentTrendsinAI-basedEducationalProcesses—AnOverview”by
MirjanaIvanovic´,AleksandraKlašnja-Milic´evic´,MarcinPaprzycki,MariaGanzha,
Costin Ba˘dica˘, Amelia Ba˘dica˘, and Lakhmi C. Jain is an introductory one and
considers the influence of modern artificial intelligence techniques on educational
processes.Theauthorsfocusonprovidinganoverview ofthecurrentstate-of-the-
art of developing intelligent educational systems that have significant effects on
learningandteachingprocesses.RecentworksthatputlightondifferentrolesofAI
indevelopingeducationalsystemsarediscussed:Adaptivepersonalizationsystems
andintelligenttutoringsystems,assessmentandevaluationofstudents’outcomes,
andthebenefitsandthechallengesofeducationaldataminingandlearninganalytics.
-
Chapter2“DigitalizationofEducation”,byÐordeNadrljanski,MilaNadrljanski,
andMiraPavlinovic´isfocusedondiversityandfeaturesofconceptsandinitiativesfor
digitalizationineducation.Theadvantagesandchallengesrelatedtothedevelopment
ofdigitalizedenvironmentsineducation,aswellasthegreaterneedforprofessional
development of people working in digitalization, are discussed. In addition, they
encourage and promote innovation in many different spheres of life. They stated
thatthereisaverystronglinkbetweeneducationandskillsneededtoutilizedigital
technologies in different sectors of society. The very important conclusion is that
digitalizationisanimportanttoolformakingfundamentalchangesintheprocesses,
content,andvariousformsofworkineducationalsettingstoincreasethequalityand
relevanceofeducationforall.
Chapter3“RemoteTeachingandLearningMathinEnglishThroughCLIL”by
Maria Guida and Letizia Cinganotto focuses on teaching Mathematics by using
umbrellamethodologyCLIL(ContentandLanguageIntegratedLearning).Authors
investigatetheopportunitiesandchallengesofCLILinMathematicsinremoteand
hybrid settings due to the pandemic. Examples of repositories, web tools, digital
boardsusedbyteachersforremoteCLILteachingarepresentedasawaytofoster
students’engagement,interaction,andinteractivity.Despitetheproblemsduetothe
pandemic,theteachersinItalywereabletodeliveradequatecontentinameaningful
way,usingproblem-basedorproject-basedlearning.Communicationandinteraction
amongthestudentsandwiththeteachersthroughthediscussion,explanation,and
negotiationofthedifferentCLILactivitiesarediscussed.
Chapter 4 “The Potential of Artificial Intelligence for Assistive Technology in
Education”byKaterinaZdravkovadiscussestheimportantaspectsoftheincorpo-
ration of assistive technology in education. It is evident that persons with various
disabilities should have an equal access to quality education, and chapters show
Preface vii
how assistive technologies support such persons to keep and improve their func-
tioning,whichreinforcesinclusiveeducation.Further,thechapterpresentsaplethora
of AI-supported educational tools intended to help people with special needs and
elderly people, encompassing the tools for visual, hearing, communication, intel-
lectual,cognitive,andmotorimpairment.Additionally,someethicalchallengesof
AI-supportededucationaltoolsareraised.
InChap.5“AdaptiveandIntelligentWeb-BasedLearningandControlTechnolo-
gies”,ValeryM.Kaziev,andLyudmilaV.Glukhovaconsideredthecurrentproblem
ofevolutionofadaptiveandintelligenttechnologiesofmoderneducationandtheir
influenceonthedigitalinfrastructureofeducationalenvironments.Thepurposeof
theirstudyisanevolutionarysystemanalysisofthedigitalopportunitiesfortheeffec-
tivedevelopmentoftheinformationandeducationalspaceofuniversitiesfromthe
Russianmodelofcompetence-orientededucation.Theyproposedtheformal,mathe-
maticalmodelofadaptivelearningdecision-making.Keymethods,approaches,and
technologiesofadaptingandintellectualizingweblearningareconsideredincluding
didacticaspects.Theauthorsalsoinvestigated theissuesofself-organization,web
education, their adaptation to digital transformations in society, the environment
of the educational system and proposed a list of basic intelligent web learning
technologies.
Thenext,Chap.6“ExemplarUse-casesforTrainingTeachersonLearningAnalyt-
ics”byArvindW.Kiwelekar,ManjushreeD.Laddha,andLaxmanD.Netakprovide
ready-to-use examples for conducting teachers training programs on Learning
Analytics.Moreprecisely,thechapterdocumentsasetofexemplarsusedtodemon-
strate LA applications in daily classroom activities. These exemplars have been
designedandusedmainlytotrainnewlyrecruitedteachersondataanalysismethods
(suchashypothesistesting,analysisofvariance(ANOVA),correlationanalysis,and
regressionanalysis)duringfacultyinductionprograms.
Chapter7“ImpactofLessonPlanningonStudents’AchievementusingLearner
ProfileSystem”byMunazzaA.Mirza,KhawarKhurshid,ZawarShah,FaryalShah,
AndrewLevula,andAleksandraKlašnja-Milic´evic´proposedandevaluatedaLearner
ProfileSystem,whichisaweb-basedsolutiontogeneratemultipletypesoflearner
profiles. The profiles include the basic information about the learners, preference
and interest profile, learning styles, and motivational goal orientation. The pilot
studyincluded60middleschoolstudentstomeasuretheconstructvalidityandreli-
ability.Afterward,anexperimentalstudywasdoneon307middleschoolstudents
to examine the impact of LPS on learners’ achievement. Teachers’ perception and
theirperspectiveregardingthefeasibilityanduseoftheLPSisalsoconsidered.The
authorsconcludedthatthegroupthatlearnedusingtheLPSdemonstratedsignificant
improvementintheirassessmentscoresincomparisontothecontrolledgroup.
PeterIlicintheChap.8“TowardsanUnderstandingofStudentDigitalEcosystems
forEducation”putattentiontotheuseofICTforeducationalpurposes.Thechapter
shedslightonthisissueandtakesaninitialsteptowardsmappingstudents’digital
ecosystems to enable course design that better fits student learning expectations.
Further, different methods were employed to obtain a better understanding of the
viii Preface
participants’degreeoftechnologicaladoptionandpracticeinrelationtocollabora-
tiveeducationalactivities.InsightintothestructureofJapaneseuniversitystudents’
digital ecosystems was developed by capturing and analyzing participant activity
in log data. The author presented several key findings that may help curriculum
designers in improving their courses. Also, he considered the effects of students
shiftingbetweendevicetypes(mobileandnon-mobile)dependingonthecontextand
purpose.Theoverallresults,aswellasimplicationsforeducation,werediscussed,
alongwithsuggestionsforpossiblefutureresearch.
Different applications and challenges of computational argumentation for
modeling distinct aspects of learning processes are presented in Chap. 9 “Compu-
tationalArgumentationforSupportingLearningProcesses:ApplicationsandChal-
lenges”byCarlosChesñevar,CésarA.CollazosandAnaMaguitman.Thechapter
is devoted to argument-based recommender systems for educational purposes;
argument-based shared knowledge for computer-supported collaborative learning
andargument-basedopinionminingforelicitingstudents’knowledgebasedoninfor-
mationitemscorrespondingtodifferenttopicsofstudy.Thecurrentstate-of-the-artin
thedomainisalsobrieflypresented.Italsogivesagoodstartingpointforresearchers
working on intelligent techniques for educational processes who are interested in
incorporatingargumentationasametaphorformodellingintelligentdecisionmaking
in Intelligent Tutoring Systems and Computer-Supported Collaborative Learning
systems.
Chapter10“RevealingLatentStudentTraitsinDistanceLearningthroughSNA
and PCA” by Rozita Tsoni, Evangelos Sakkopoulos, and Vassilios S. Verykios
considerssignificantissuesinadistancelearningpostgraduatecourse.Theauthors
proposedanovelapproachbasedonlearninganalytics.Theapproachisbasedona
richspectrumofmetricsofSocialNetworkAnalysisthatcancapturecomplicated
interactionofsocialstudents’behavior,alongwithacademicperformanceindicators,
inaprocessthataimstorevealthelatentcharacteristicsofstudentsparticipatingin
thediscussionfora.
Chapter 11 “Smart Technology in the Classroom: Systematic Review and
ProspectsforAlgorithmicAccountability”byMariaOvchinnikova,DanielOstnes,
Arian Garshi, Malin Wist Jakobsen, Jørgen Nyborg-Christensen, and Marija
Slavkovik brings a comprehensive review of the use of smart technologies in the
classroom. The authors explored the state-of-the-art literature in several emergent
subdisciplines:wearables,AIandeducation,schoolsurveillance,accountability,and
so on. Both positive and negative effects of using smart technologies are pointed
out,andaframeworktoeffectivelyidentifyaccountabilityforsmarttechnologyin
educationisproposed.
AutomatedgradingisthecentraltopicoftheChap.12“ObjectiveTestsinAuto-
matedGradingofComputerScienceCourses:AnOverview”byMarinLujak,Marija
Slavkovik,AlexisLebis,MathieuVermeulen,andArnaudDonie.Authorsanalyzed
andmutuallycomparedthemostusedobjectivetestsincomputersciencecoursesin
MoodleandMOOCsandoutlinedtheadvantages,technicallimitations,andethical
challenges.Testfeedbackmechanismsthatfacilitatecontinuouslearningforstudents
as well as the identification and recognition of possible evaluation mistakes of the
Preface ix
system of AI-supported methods for automating objective tests in programming
are considered. Special attention is paid to the identification and mitigation of the
context-specificethicalchallengesandessentialcharacteristicsoftests.
Chapter 13 “Correlating Universal Design of Learning and the Performance in
ScienceatElementarySchoolLevel”byMunazzaA.Mirza,KhawarKhurshid,Asma
Hasan,ZawarShah,andFaryalShahisdevotedtotheessenceofuniversaldesignof
learning.Theauthors’studyaimstoinvestigatetheimpactonalearner’sacademic
performance when a teacher uses the Universal Design of learning framework for
planningsciencelessons.Aframeworkbasedontheconstructivisttheory,builton
cognitiveneuroscienceemphasizesengagingmultiplebrainnetworksbyproviding
guidelinesorganizedintothreeessentialprinciplesispresented.Theexperimentsare
conductedtodiscovertheeffectivenessoftheUDL-basedlessonimplementationin
scienceandaquasi-experimentalpre-testandpost-testdesignwasusedinthestudy.
Authorsfoundthatelementaryschoolpupilsachievebettergradesinsciencewhen
taughtusingauniversaldesignoflearningapproachincontrasttothosewhohave
beentaughtusingtraditionalteachingmethod.
Next,theChap.14“FacilitatingCollaborativeLearningwithVirtualRealitySimu-
lations, Gaming and Pair Programming” by Piia Näykki, Janne Fagerlund, Minna
Silvennoinen,MariManu,TuulaNousiainen,MerjaJuntunen,andMikkoVesisenaho
bringstoreadersaninterestingandemergingtrendineducationalsettings.Authors
presented socio-interactional functions that support collaborative learning through
three case examples. The examples are based on the use of technology-enhanced
simulation-basedlearningenvironments,Vive/Minecraftapplyingvirtualandmixed
reality and pair programming in a creative media project design with Scratch.
These powerful experiential learning contexts provide engaging opportunities for
collaborativelearning.
“Gamification and the Internet of Things in Education” is the title of Chap. 15
authoredbyGeorgiosPappas,JoshuaSiegel,IoannisN.Vogiatzakis,andKonstantinos
Politopoulos. As gamification and the Internet of Things can impact education in
amanner previouslyimpossible,gamified toolsbuiltupongame enginescanoffer
opportunitiesinthedevelopmentofinnovativevirtuallabsandotherinteractiveexpe-
riences for students. The authors designed and developed a training gamified tool
appliedinthefieldofenvironmentalstudies.Theyshowedhowthisisintegratedwith
theInternetofThingstoenabletriggersinavirtual3Dspace.Additionally,theyalso
providedinformationonhowthisinnovationhasbeenusedinarealdistance-learning
classforMaster’sdegreestudents.
Chapter16“Communication-DrivenDigitalLearningEnvironments:10Yearsof
ResearchandDevelopmentoftheCampusPlatform”byLuísPedroandCarlosSantos
underlinestheCampusplatformandtheimportanceofcommunicationconceptsand
affordancesintheresearchanddevelopmentofadigitallearningenvironment.They
arguedtheapproachthatvaluesthesocialconstructionofknowledge,theimportance
of networks, collaboration, and sharing in educational processes. Apart from that,
the evaluation study of the platform is presented, which allowed to characterize
it as an open communication ecosystem for effective dialogue, participation, and
engagement.