HANDELkompetent is a research project, funded by the German Federal Ministry of Education and Research (BMBF). The developed concepts, tools and contents are the foundation for learners in retail for situation aware and work process integrated learning. As a first step towards the situation awareness, appropriate learning contents are selected, depending on the learner’s current knowledge level. To adjust the learning pathway furthermore, the HANDELkompetent app is context aware. I.e. different aspects like timeframe, noise or location are considered in the selection of learnable contents. At any time, the learner can focus on those contents that are appropriate for him, the current environment and his knowledge level.

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HANDELKOMPETENT - ENABLING ADAPTIVE
LEARNING PATHWAYS BY SITUATION AWARENESS
LEARNTEC, 31st January 2018, Sebastian Opriel

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Retail in Germany
IAB Betriebspanel, März 2017; HDE Branchenreport Einzelhandel – Der Handel als Wirtschaftsfaktor, 2015; HDE Branchenreport Einzelhandel – Der Handel als Arbeitgeber, 2013
1 to 4
employees
5 to 9
employees
20 to 99
employees
> 99
employees
Participation in continuing education
29 %
58 %
84 % 86 %HANDELkompetent
Primary target
Average participation in continuing education: 47 %
482.000.000.000 Euro in sales
3.000.000 employees
300.000 companies
1 to 4 employees : 38 % (114.000 companies)
5 to 9 employees : 52 % (156.000 companies)
20 to 99 employees : 9 % (27.000 companies)
> 99 employees: 1 % (3.000 companies)
Third largest commercial sector

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The BMBF funded project HANDELkompetent
 Funding: 1,2 Mio. € (81 % from BMBF), Funding number: 01FK14018
 Project duration: 01.05.2015 – 30.04.2018
 Partners
 Fraunhofer ISST, Dortmund
 Qualitus GmbH, Cologne
 systemkonzept GmbH, Cologne
 Zentralstelle für Berufsbildung im Handel e. V. (zbb), Berlin
 Implementation partners
 Metzgerei Sack
 IHK Köln
 Berufsgenossenschaft für Nahrungsmittel und Gastgewerbe
 Berufsgenossenschaft für Handel und Warendistribution

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Main Idea
 Mobile e-learning with situation awareness
 Learning content consists of
e-learning nuggets (~5 min.)
 Mobile devices gather current context:
Noise, time, location, etc.
 Recommend fitting contents on basis of
 Preselected pool of contents
 Current situation and context
 Learners’ competences https://github.com/TJAppsLab/knowledge_base/wiki/
Estimote-Beacons-and-Triangulation (2017-04-05)

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Systems
Learning modules (SCORM)
ILIAS
Editor
App
Environmental
context

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Roles
Learner
Management
Competence
godfather
Manager
Learning content
creator
Professional
organization
Co-workers
Learning tandem
partner
Guidance &
schedule
Supervision
Definition
of goals
Definition of goals
Definition
of needs
Collaboration
Notification on
topics & content
Content
Need for
Content
Feedback
Supervision
Discussion

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Learning Pathway Determination
Pool of learning contents of a company
Chosen further education
topics for employee
Competence level
based learning
Situation aware
content selection
Contents with no
restriction
Management
Competence
godfather
1 2

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Learning Contents
 HANDELkompetent
developed 30 learning
contents (current status)
 4 nuggets without
restrictions
 6 nuggets based on
competences
 20 nuggets with
context conditions
 from six categories
 General topics
 Lift and carry
 Standing
 Mental strains
 Sales training
 Company specific
contents

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Competence Level Based Learning
 Competence grading via 360°
survey (40 questions)
 Competences
 4 main categories
 21 sub categories
 4 rating levels
 2 levels of content difficulties
 Assign users to one of them

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Situation Aware Content Selection
 Define for each learning content
access rules
 Time periods
 Noise
 Device
 Connection
 Tagged Locations
Cellular icon by Bernar Novalyi from Noun Project

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Digression Beacons
 Architecture
 Microprocessor
 Bluetooth LE-Module
 Battery
 Function
 Different protocols
 Main purpose: Send
Bluetooth advertising
signals, containing a
unique id
Estimote.com

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Situation Aware Content Selection
 Detect environmental context and current situation by devices‘ sensors
 Filter learning contents against detected sensor values
Cellular icon by Bernar Novalyi from Noun Project

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System architecture
HK ≙ HANDELkompetent

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HANDELkompetent Editor – Features
 Serves as data supplier for HANDELkompetent App
 Synchronizes data with ILIAS (unidirectional)
 Users
 Contents
 User’s learn contents status
 Manage situation and context model
 Locations (company, building, room, places tagged with beacons)
 Periods
 Environments (noise, device, connection)
 Contexts (location, period, environment)
 Assign contexts to learn contents

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HANDELkompetent Editor – Frontend

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HANDELkompetent Editor – Frontend

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HANDELkompetent App – Features
 Authentification of users
 Fetch data from HANDELkompetent Editor
 Give an overview of courses and contents
 Receive environmental information through sensors
 Restrict contents depending on environmental context (period, location,
noise)
 Display SCORM-Modules in InAppBrowser
 Display other materials in appropriate app (PDF viewer, etc.)

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HANDELkompetent App – Frontend

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HANDELkompetent App – Frontend

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HANDELkompetent App – Frontend

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HANDELkompetent App – Frontend

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HANDELkompetent App – Frontend

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HANDELkompetent App – Frontend

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HANDELkompetent App – Frontend

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THANK YOU
sebastian.opriel@isst.fraunhofer.de
https://xing.com/profile/Sebastian_Opriel
https://linkedin.com/in/sebastianOpriel
https://slideshare.net/SebastianOpriel
https://researchgate.net/profile/Sebastian_Opriel
Sebastian Opriel, M.Sc.
Fraunhofer Institute for Software
and Systems Engineering ISST
Digitization in Logistics
Researcher Fraunhofer Institute for Software
and Systems Engineering ISST
Emil-Figge-Str. 91, 44227 Dortmund, Germany
Phone: +49 (0) 2 31 / 9 76 77-0
Web: www.isst.fraunhofer.de