1 1 Andreea Molnar, Cristina Hava Muntean School of Computing National College of Ireland QoE-MOT – A Learner Quality of Experience- Oriented Authoring Tool

2 2 Overview Adaptive e-Learning Systems (AeLS) Multimedia Content Issues Authoring AeLS Quality of Experience LOAS (QoE-LAOS) Framework Quality of Experience MOT (QoE-MOT) Authoring Tool Conclusions & Future Work

3 3 Adaptive e-Learning Systems The main goal is to provide personalised educational content tailored to learners profiles Adaptation is based on: Learner profile Learner device Leaner context Learner network performance, etc

4 Multimedia Content Issues (1) Increasing useof multimedia in e-learning courses Not all people perceive multimedia quality in the same way Educational material, especially video, is affected by poor QoS (Quality of Service): Unclear voice Unclear image Synchronisation problems between voice and video Delay in accessing the educational content

5 Multimedia Content Issues (2) Is there a solution? Take into account the characteristics of the multimedia educational content as well as network and learner device in the course design and adaptation rules specification phases. An authoring tool which would help the course creators to create this kind of course.

6 Authoring AeLS Type of authoring tools do not support content adaptation: HyCo –a simple and intuitive interface for generating learning content MEAT – it allows single authoring for modal interfaces support content adaptation: MOT (My Online Teacher) – a general authoring system A-SCORM Course Creator Tool – creates adaptive SCORM conformant courses

7 QoE-LAOS Framework An extension of LOAS authoring model that has 5 layers: Domain Model (DM) User Model (UM) Goal and Constraints Model (GM) Adaptation Model (AM) Presentation Model (PM) Adds three new sub-layers QoE Content Features sublayer QoE Characteristics sublayer QoE Rules sublayer

8 QoE-MOT (Quality of Experience-MOT) QoE-MOT is based on the generic authoring tool: MOT Support for creation of performance-aware adaptive courses It follows the QoE-LAOS authoring model

9 QoE-MOT: Content Features (1) Stores various versions with different properties for each file File characteristics metadata are also kept Text: size, length, format (e.g. plain text) Image: size, format (e.g. jpg), resolution Webpage: size, no. of objects embedded in a file Video: bit rate, frame rate, resolution, encoding scheme

10 QoE Content Features (2) QoE-MOT Exemplification New metadata for the multimedia version 1 file

11 QoE-MOT: QoE Rules (1) Defines adaptation rules based on the QoE characteristics Different strategies can be introduced at this level, providing the author with the possibility to choose between them The rules are written using LAG adaptation language

12 QoE-MOT: QoE Rules (2) Exemplification: if enough (DM.Concept.access DM.Concept.type == bitrate,2) then (if DM.Concept.bitrate <=maxbitrate t hen UM.GM.suitable = true else UM.GM.suitable = false) if enough (DM.Concept.access UM.GM.suitable == true,2) then PM.GM.Concept.show = true

13 Conclusions Multimedia content can be damaged by the network condition QoE-MOT an authoring tool for the AeLS was presented QoE-MOT is based on the QoE-LAOS authoring model It extends MOT with new features that allow QoE aware rules adaptation authoring

14 Future work To automate the process of content metadata extraction Reusable adaptation strategies for authoring the content have been proposed and will be further tested Subjective tests will be performed to evaluate QoE-MOT

15 Questions?