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Fremtidens Datalogiskeuddannelser
Bent Thomsen
"Study the past if you would define the future...." Confucius
TilvalgTilvalg
DAT10DAT10DAT6DAT6
TilvalgTilvalg T F K
DAT1‐4DAT1‐4
TilvalgTilvalg
INF1‐6 INF1‐6 DAT1‐6DAT1‐6 SW1‐6SW1‐6
Datalogi Software Datalogi og tilvalgsfag
Datalogi og tilvalgsfag
Informatik Informations-teknologi
Bachelor
Kandidat SW7‐10SW7‐10
Cand.polyt. i software
TilvalgTilvalg
Cand.scient. i datalogi og tilvalgsfag
DAT5‐6DAT5‐6
DAT10DAT10
Cand.scient. i datalogi og tilvalgsfag
Cand.scient. i datalogi
INF7‐10INF7‐10
Cand.scient. i informatik
Tilvalg = tilvalgsfag i naturvidenskab, humaniora eller samfundsvidenskab(tilvalg i idræt, humaniora eller samfundsvidenskab giver studietids-forlængelse på et halvt år (et semester))
Datalogiske Uddannelser 2016
DAT7‐10DAT7‐10
Cand.scient. i datalogi
BAIT5BAIT5DAT1‐5DAT1‐5
DAT5‐6DAT5‐6
DAT9‐10DAT9‐10
Cand.scient. i datalogi (it)
IT7‐8IT7‐8
IT9‐10IT9‐10
K+F+T:Cand.it i Interaktive Digitale Medier +Cand.mag i InformationsvidenskabF: Cand.polyt i Værdikæder og InnovationsledelseF+K: Cand.it i it ledelse
Interaktionsdesign(fra 2017):Cand.polyt. i sustainable design
IxD1‐6IxD1‐6
Interaktions-design
IxD7‐10IxD7‐10
Cand.scient. i interaktions-design (fra 2017)
Datalogiske Uddannelser 2016• De fleste uddannelser er designet i 2009 og indført i E2010
• Små justeringer undervejs
• Følger 3*5+15 modellen• Spareøvelse !!• Ønske om flere kurser/aktiviteter på eksamensbeviset• Obligatorisk valgfrihed på minimum 10 ECTS (kun på kurser!)• Ingen formel sammenhæng mellem kurser og projekter• Alignment med Bologna• Kurser a’ 5 ECTS
• ~150 timers indsats for den studerende• Honoreres med 150+1.5*n timer (200 timer + hjælpelærer for hver 50)• ~ 12 forelæsning + miniprojekt/workshop/…
• Project a’ 15 ECTS• Honoreres med 15 timer pr. Stud ~ 90 timer pr. gruppe
• Erstattede 2*3+2*3+18 modellen • 2 SE og 2 PE kurser• Kurser a’ 3 ECTS med 210 timer ~ 15 forelæsning/øvelser sessioner• Project a’ 18 ECTS ~100 timer pr. gruppe
Software Ingeniør bachelor Uddannelsen før 2010 og efter 2010
Software Ingeniør kandidat Uddannelsen før og efter 2010
Datalogi bachelor og kandidat efter 2010
Undersøgelse af SW uddannelsen• Assessing Problem‐Based Learning in a Software Engineering Curriculum Using Bloom’s Taxonomy and the IEEE Software Engineering Body of Knowledge
• PETER DOLOG, LONE LETH THOMSEN, and BENT THOMSEN• Trans. Comput. Educ. 16, 3, Article 9 (May 2016), 41 pages. DOI=http://dx.doi.org.zorac.aub.aau.dk/10.1145/2845091
• Analyze competence levels according to Bloom’s taxonomy• assignment of Bloom taxonomy levels based on evidence found in the study regulation or gathered from all projects • Analyzed all semester projects from the fourth semester (SW4), seventh semester (SW7), and 10th semester (SW10)• It is not an assessment of individual students
• Compared with IEEE Software Engineering Body of Knowledge (SWEBOK) • expected level for person with 4‐year SW degree program and 4 years of experience
• Compared with the Graduate Software Engineering 2009 Curriculum Guidelines for Graduate Degree Programmes in Software Engineering (GSwE2009)
• Preliminary evaluation of consequences of change from “old” to “new” Aalborg model• “new” = 3*5+15 model
Software Engineering Body of Knowledge
RequirementsEngineeringProcessRequirementsElicitationRequirementsAnalysisRequirementsSpecificationRequirementsValidationRequirementsManagement
SoftwareRequirements
Software DesignBasic ConceptsKey Issues inSoftware DesignSoftware Structureand ArchitectureSoftware DesignQuality analysisand EvaluationSoftware DesignNotationsSoftware DesignStrategies andMethods
SoftwareDesign
Linguistic MethodsFormal MethodsVisual Methods
Reducation inComplexity
Linguistic MethodsFormal MethodsVisual Methods
Anticipation ofDiversity
Linguistic MethodsFormal MethodsVisual Methods
Structuring for validation
Linguistic MethodsFormal MethodsVisual Methods
Use of ExternalStandards
SoftwareConstruction
Basic ConceptsandDefinitionsTest LevelsTest TechniquesTest-related MeasuresManaging the TestProcess
SoftwareTest
BasicConceptsMaintenanceProcessKey issuesInSoftwareMaintenanceTechniquesforMaintenance
SoftwareMaintenance
Management of theSCM ProcessSoftwareConfigurationIdentficationSoftwareConfigurationControlSoftwareConfigurationStatus AccountingSoftwareConfigurationAuditingSoftware ReleaseManagementandDelivery
SoftwareConfigurationManagement
OrgaqnizationalManagementProcess/ProjectManagementSoftwareEngineeringMeasurement
SoftwareEngineeringManagement
Engineering ProcessConceptsProcess InfrastructureProcess MeasurementProcess DefinitionQualitative ProcessAnalysisProcessImplementationand Change
SoftwareEngineering
Process
RequirementsToolsDesign toolsConstruction toolsTesting toolsMaintenance toolsEngineering ProcessToolsQuality toolsCongifurationManagementToolsEngineeringManagementToolsInfrastructureSupportToolsMiscellaneous toolIssues
SoftwareTools
Heuristic MethodsFormal MethodsPrototyping MethodsMiscellaneous methodIssues
SoftwareMethods
SoftwareEngineering
Tools & Methods
QualityConceptsDefinition& Planningfor QualityTechniquesRequiring2 or morePeopleSupport tootherTechniquesTesting SpecialToSQA or V&VDefect FindingTechniquesMeasurement inSoftware QualityAnalysis
Software Quality
SWEBOK
WWW.SWEBOK.ORG
GSwE2009 vs. AAU
Overall conclusions• Software engineering students at Aalborg University achieve higher levels of competencies in several areas
• software requirements fundamentals, software design, software construction (Application vs. Analysis/Evaluation)• These higher competence levels are mainly achieved through the project work
• A few areas are at par or below• software testing, no significant differences in comparison to the SWEBOK • software quality, requirements management and change management
• SWEBOK: application level, AAU SW: comprehension• Requires work in/with organizations of some maturity to achieve higher levels or longer running interaction with customers
• Compared to GSwE2009, only few areas need attention• social, legal, and historical issues• data confidentiality, security, surveillance, and privacy
• In addition students achieve enhanced transferable skills• project management, communication, negotiation, and conflict resolution. • Well‐known skills obtained through group‐based problem‐based learning.
• Analyzing grades for master’s thesis projects, students at Aalborg University seem to perform above average. • We attribute this, in part, to the fact that students at Aalborg University accumulate a lot of experience in uncovering real
problems and finding good solutions, as well as plenty of experience in managing and executing projects.
PBL effects on grades
Konsekvenser af 3*5+15 modellen
• Konsekvenser for Projekt arbejde• Mindre teori i rapporter• Mindre reflekterende (og dermed lavere score på Bloom’s taxonomi)
• Konsekvenser for kursus undervisning• Mere focus på kurser (inkl. Tre eksamener)• Masser af miniprojekter (mere PBL i kurser?)• Brug af workshops• Øvelser i plenum• Brug af quizzes • Video understøttelse af svære elementer• Brug af eksternt producerede video materiale• Flipped classroom
Mine konklusioner
• Vi har et “godt product”• Vi skal være varsomme med radikale forandringer
• Selvfølgelig kan der laves forbedringer• Selvfølgelig skal der laves forandringer
Tilbage til fremtiden
• Forslag om afskaffelse af Lineær algebra og flytning af diskret mat.• Diskret mat på 1. semester + statistik på 2. semester• Dækning af underrepræsenterede emner fra SWEBOK/GSwE2009?
• data confidentiality, security, surveillance, and privacy• Nye trends i mainstream:
• Parallelism• Functional programming• Formal methods
• Programmering i folkeskolen og i fritiden (hour‐of‐code, coding pirates)
• Større forskel på DAT og SW bachelor ?• Forskel på de studerendes selvopfattelse og opførsel allerede på 3./4. semester
SMAC – the fifth era of computing
• After the mainframe era, mini‐computing era, personal computer and client‐server era, and the web era comes:
• SMAC ‐ Social, Mobile, Analytics and Cloud technologies• Software‐as‐a‐Service (SaaS)• Infrastructure‐as‐a‐Service (IaaS)• Data Analytics/Big Data
• Additional topics:• automation and robotics • the IoT, • cybersecurity• agile and DevOps
• DevOps is a cultural shift and collaboration between development and operations• strategic planning, innovation management, enterprise architecture, program management, and change management
Konsekvenser af regeringens spareprogram• Normer reduceret fra E2016
• 140+1.5*n for kurser• ~ en forelæsning mindre pr. Kursus
• 14.5 timer pr. Stud til vejledning• ~ 1‐2 vejledermøder færre
• Besparelser på m2• Ingen grupperum til pre‐speciale og speciale studerende• Gruppearbejde i storrum• Virtuelt gruppearbejde?• Individuelt projektarbejde?• Kan disse besparelser gøres til pædagogiske virkemidler?
• Brug af eksternt produceret materiale i “standard” kurser (MOOC) ?
• 2*5 + 20 model eller 2*7.5 + 15 eller …?
Diskussion
• Jeg maner til forsigtighed, men skal vi være mere radikale?• Større forskel på DAT og SW Bachelor?• SMAC – skal den nye era tænkes mere gennemgribende ind?
• F.eks. På SW7/SW8
• Hvordan kan vi opretholde kvaliteten i vores uddannelser med de nyeøkonomiske rammer?
• Kan/skal det tænkes ind i studieordningerne?
• Data Science – er der brug for det i Nordjylland?
Data Science
• Conclusions from 2015 Reaseach Evaluation:• Furthermore, society needs people that know how to handle data, so it is important to educate students in Data Science.
• The recommendation is to start a Data Science programme as soon as possible.• What should be in a Data Science curriculum?
• Mathematics and statistics• Programming• Parallel and distributed systems• Databases• MapReduce and no‐SQL systems• Machine intelligence• Visualization of Data
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