This document discusses interactions in learning environments that use IMS Learning Design specifications. It analyzes how pedagogical aspects are expressed at runtime in IMS LD players. The authors selected the SLeD player and analyzed several real-world learning designs to identify support for and obstacles to different interaction types, such as student-student and student-teacher interactions. Challenges included unclear instructions for collaboration, roles that were not separately identifiable by teachers for support purposes, and complex mappings of roles to learning paths. The analysis aims to inform improvements to IMS LD runtime environments.
A review-miml-framework-and-image-annotationEditor IJMTER
This review paper creates a bridge between MIML classification framework and
Image annotation. There are generally four classification frameworks, known as Single
Instance Single Label (SISL), Multi-Instance Learning (MIL), Multi-Label Learning (MLL)
and Multi-Instance Multi-Label Learning (MIML). This paper introduces various
classification frameworks with examples and related algorithms. An annotation is one type of
metadata that can be attached to any video, image (2D/3D), text, audio and other data in the
form of explanation, comments, navigation or presentational markup. This paper briefly
introduces different types of annotation, annotation dataset, techniques and current research
challenges in annotations
Ontological Model of Educational Programs in Computer Science (Bachelor and M...ijsrd.com
In this work there is illustrated an ontological model of educational programs in computer science for bachelor and master degrees in Computer science and for master educational program “Computer science as second competence†by Tempus project PROMIS.
NetLearn: Social Network Analysis and Visualizations for LearningMohamed Amine Chatti
The most valuable and innovative knowledge is hard to find,
and it lies within distributed communities and networks. Locating the
right community or person who can provide us with exactly the knowledge
that we need and who can help us solve exactly the problems that
we come upon, can be an ecient way to learn forward. In this paper, we
present the details of NetLearn; a service that acts as a knowledge lter
for learning. The primary aim of NetLearn is to leverage social network
analysis and visualization techniques to help learners mine communities
and locate experts that can populate their personal learning environments.
A review-miml-framework-and-image-annotationEditor IJMTER
This review paper creates a bridge between MIML classification framework and
Image annotation. There are generally four classification frameworks, known as Single
Instance Single Label (SISL), Multi-Instance Learning (MIL), Multi-Label Learning (MLL)
and Multi-Instance Multi-Label Learning (MIML). This paper introduces various
classification frameworks with examples and related algorithms. An annotation is one type of
metadata that can be attached to any video, image (2D/3D), text, audio and other data in the
form of explanation, comments, navigation or presentational markup. This paper briefly
introduces different types of annotation, annotation dataset, techniques and current research
challenges in annotations
Ontological Model of Educational Programs in Computer Science (Bachelor and M...ijsrd.com
In this work there is illustrated an ontological model of educational programs in computer science for bachelor and master degrees in Computer science and for master educational program “Computer science as second competence†by Tempus project PROMIS.
NetLearn: Social Network Analysis and Visualizations for LearningMohamed Amine Chatti
The most valuable and innovative knowledge is hard to find,
and it lies within distributed communities and networks. Locating the
right community or person who can provide us with exactly the knowledge
that we need and who can help us solve exactly the problems that
we come upon, can be an ecient way to learn forward. In this paper, we
present the details of NetLearn; a service that acts as a knowledge lter
for learning. The primary aim of NetLearn is to leverage social network
analysis and visualization techniques to help learners mine communities
and locate experts that can populate their personal learning environments.
FACE EXPRESSION RECOGNITION USING CONVOLUTION NEURAL NETWORK (CNN) MODELS ijgca
This paper proposes the design of a Facial Expression Recognition (FER) system based on deep
convolutional neural network by using three model. In this work, a simple solution for facial expression
recognition that uses a combination of algorithms for face detection, feature extraction and classification
is discussed. The proposed method uses CNN models with SVM classifier and evaluates them, these models
are Alex-net model, VGG-16 model and Res-Net model. Experiments are carried out on the Extended
Cohn-Kanada (CK+) datasets to determine the recognition accuracy for the proposed FER system. In this
study the accuracy of AlexNet model compared with Vgg16 model and ResNet model. The result show that
AlexNet model achieved the best accuracy (88.2%) compared to other models.
The increased potential of the ontologies to reduce the human interference has wide range of applications. This paper identifies requirements for an ontology development platform to innovate artificially intelligent web. To facilitate this process, RDF and OWL have been developed as standard formats for the sharing and integration of data and knowledge. The knowledge in the form of rich conceptual schemas called ontologies. Based on the framework, an architectural paradigm is put forward in view of ontology engineering and development of ontology applications and a development portal designed to support ontology engineering, content authoring and application development with a view to maximal scalability in size and complexity of semantic knowledge and flexible reuse of ontology models and ontology application processes in a distributed and collaborative engineering environment.
Learner Ontological Model for Intelligent Virtual Collaborative Learning Envi...ijceronline
An enacting approach to intelligent virtual collaborative learning model is explored through the lens of critical ontology. This ontological model enables to reuse of the domain knowledge and to make the knowledge explicitly available to the agent working as an Expert System, which uses the operational knowledge in collaborative learning environment. This ontological model used by the agent to identify the preliminary competency level of the user. This environment offers personalized education to each learner in accordance with his/her learning preferences, and learning capabilities. Here the factors considered to identify the learning capability taken are demographic profile, age, family profile, basic educational qualification and basic competency scale. The conception of heuristics is then used by the agent to determine the effectiveness of the learner by referring the different parameters of the learner available in the ontological model.To help getting over this, the paper describes the experience on using an ontological model for collaborative learning to relate and integrate the history of the learner by maintaining the history of learner in collaborative learning environment that will be used by the Multi-Objective Grey Situation Decision Making Theory to infer the understanding level of user and produces the conditional content to the user
Ontology matching finds correspondences between similar entities of different ontologies. Two ontologies may be similar in some aspects such as structure, semantic etc. Most ontology matching systems integrate multiple matchers to extract all the similarities that two ontologies may have. Thus, we face a major problem to aggregate different similarities.
Some matching systems use experimental weights for aggregation of similarities among different matchers while others use machine learning approaches and optimization algorithms to find optimal weights to assign to different matchers. However, both approaches have their own deficiencies.
it's our presentation during the third international conference of information systems and technologies ICIST 2013 held at Tangier, Morocco in which we propose a new approach for human assessment of ontologies using an online questionnaire.
FACE EXPRESSION RECOGNITION USING CONVOLUTION NEURAL NETWORK (CNN) MODELS ijgca
This paper proposes the design of a Facial Expression Recognition (FER) system based on deep
convolutional neural network by using three model. In this work, a simple solution for facial expression
recognition that uses a combination of algorithms for face detection, feature extraction and classification
is discussed. The proposed method uses CNN models with SVM classifier and evaluates them, these models
are Alex-net model, VGG-16 model and Res-Net model. Experiments are carried out on the Extended
Cohn-Kanada (CK+) datasets to determine the recognition accuracy for the proposed FER system. In this
study the accuracy of AlexNet model compared with Vgg16 model and ResNet model. The result show that
AlexNet model achieved the best accuracy (88.2%) compared to other models.
The increased potential of the ontologies to reduce the human interference has wide range of applications. This paper identifies requirements for an ontology development platform to innovate artificially intelligent web. To facilitate this process, RDF and OWL have been developed as standard formats for the sharing and integration of data and knowledge. The knowledge in the form of rich conceptual schemas called ontologies. Based on the framework, an architectural paradigm is put forward in view of ontology engineering and development of ontology applications and a development portal designed to support ontology engineering, content authoring and application development with a view to maximal scalability in size and complexity of semantic knowledge and flexible reuse of ontology models and ontology application processes in a distributed and collaborative engineering environment.
Learner Ontological Model for Intelligent Virtual Collaborative Learning Envi...ijceronline
An enacting approach to intelligent virtual collaborative learning model is explored through the lens of critical ontology. This ontological model enables to reuse of the domain knowledge and to make the knowledge explicitly available to the agent working as an Expert System, which uses the operational knowledge in collaborative learning environment. This ontological model used by the agent to identify the preliminary competency level of the user. This environment offers personalized education to each learner in accordance with his/her learning preferences, and learning capabilities. Here the factors considered to identify the learning capability taken are demographic profile, age, family profile, basic educational qualification and basic competency scale. The conception of heuristics is then used by the agent to determine the effectiveness of the learner by referring the different parameters of the learner available in the ontological model.To help getting over this, the paper describes the experience on using an ontological model for collaborative learning to relate and integrate the history of the learner by maintaining the history of learner in collaborative learning environment that will be used by the Multi-Objective Grey Situation Decision Making Theory to infer the understanding level of user and produces the conditional content to the user
Ontology matching finds correspondences between similar entities of different ontologies. Two ontologies may be similar in some aspects such as structure, semantic etc. Most ontology matching systems integrate multiple matchers to extract all the similarities that two ontologies may have. Thus, we face a major problem to aggregate different similarities.
Some matching systems use experimental weights for aggregation of similarities among different matchers while others use machine learning approaches and optimization algorithms to find optimal weights to assign to different matchers. However, both approaches have their own deficiencies.
it's our presentation during the third international conference of information systems and technologies ICIST 2013 held at Tangier, Morocco in which we propose a new approach for human assessment of ontologies using an online questionnaire.
USING ONTOLOGIES TO OVERCOMING DRAWBACKS OF DATABASES AND VICE VERSA: A SURVEYcseij
For a same domain, several databases (DBs) exist. The emergence of classical web to the semantic web has
contributed to the appearance of the notion of ontology that have shared and consensual vocabulary. For a
given, it is more interesting to take advantage of existing databases, to build an ontology. Most of the data
are already stored in these databases. So many DBs can be integrated to enable reuse of existing data for
the semantic web. Even for existing ontologies, the relevance of the information they contain requires
regular updating. These databases can be useful sources to enrich these ontologies. In the other hand, for
these ontologies more than the ratio ‘size of the instances on the size of working memory’ is large more
than the management of these instances, in memory, is difficult. Finding a way to store these instances in a
structured manner to satisfy the needs of performance and reliability required for many applications
becomes an obligation. As a consequence, defining query languages to support these structures becomes a
challenge for SW community. We will show through this paper how ontologies can benefit from DBs to
increase system performance and facilitate their design cycle. The DBs in their turn suffers from several
drawbacks namely complexity of the design cycle and lack of semantics. Since ontologies are rich in
semantic, DBs can profit from this advantage to overcoming their drawbacks.
Enhancing Academic Event Participation with Context-aware and Social Recommen...Dejan Kovachev
The plethora of talks and presentations taking place at academic conferences makes it difficult, especially for young researchers to attend the
right talks or discuss with participants and potential collaborators with similar interests. Participants may not have a priori knowledge that allows
them to select the right talks or informal interactions with other participants. In this paper we present the context-aware mobile
recommendation services (CAMRS) based on the current context (whereabouts at the venue, popularity and activities of talks and presentations)
sensed at the conference venue. Additionally, we augment the current context with the academic community context of conference participants
which is inferred by using social network analysis and link prediction on large-scale co-authorship and citation networks of participants. By
combining the dynamic and social context of participants, we are able to recommend talks and people that may be interesting to a particular
participant. We evaluated CAMRS using data from two large digital libraries - the DBLP and CiteSeerX, and participants from two conferences -
ICWL 2010 and EC-TEL 2011. The result shows that the new approach can recommend novel talks and helps participants in establishing new
connections at conference venue.
Technical Challenges for Realizing Learning AnalyticsRalf Klamma
Technical Challenges for Realizing Learning Analytics
Learntec 2015, January 28, 2015, Karlsruhe, Germany,
Ralf Klamma
Advanced Community Informations Systems (ACIS) Group
RWTH Aachen University
Cloud Services for Improved User Experience in Sharing Mobile VideosDejan Kovachev
Despite the popularity of mobile video sharing, mobile user experience (UX) is not comparable with traditional TV or desktop video productions. The issue of poor UX in mobile video sharing can be associated with the high development cost, since the creation and utilization of a multimedia processing and distribution infrastructure is a non-trivial task for small groups of developers. In this paper, we present our solution comprised of mobile video processing services based on standard libraries which augment the raw video streams. Our services utilize the cloud computing paradigm for fast and intelligent processing in near-real time. Video streams are split in chunks and then fed to the "resource-unlimited" distributed/cloud infrastructure which accelerate the processing phase. Application developers have the possibility to apply arbitrary computer vision algorithms on the video stream thus improving the quality of user experience depending on the application requirements. We providing navigation cues and content-based zooming of raw video streams. We evaluated the proposed solution from two perspectives - distributed chunk-based processing in the cloud and a user study by means of mental workload. Running experiments in mobile video applications demonstrate that our proposed techniques improve mobile user experience significantly.
Learning Analytics for the Lifelong Long Tail LearnerRalf Klamma
Learning Analytics for the Lifelong Long Tail Learner
Ralf Klamma
RWTH Aachen University
Informatik 5 (DBIS)
CELSTEC, Heerlen, The Netherlands
February 24, 2011
Identification of Learning Goals in Forum-based CommunitiesMilos Kravcik
When Internet users search for information, surf on websites or discuss with others, their actions are driven by certain goals. Extraction of users' goals can enable higher effectiveness and accuracy of web services. Supporting users in based on their goals can be highly beneficial, especially supporting of learners in the preparation for an exam as a learning process, Different phases of learning are identified when users learn collaboratively. We scrutinize how goals are constructed and achieved within a community, examining not only social activities based on patterns of behavior, but also emotions and intents users express in their posts. As a result we elicit users’ goals. We achieved good accuracy in defining emotions of users and recognizing their intents and social patterns in our case. Here we discuss how the obtained results contribute to mining of learning community goals.
Social Software and Community Information SystemsRalf Klamma
Social Software links social entities on the Internet. With this term we label new communication and collaboration media like wikis, blogs, social bookmarking but also traditional media supporting communities of practice. Scientific and professional communities challenge information systems engineering with high demands on traceable and secured collaboration and processing of scientific data. Flexibility, adaptation, interoperability are only a few requirements to mention.
With the advent of international standards XML-based standards like MPEG-7 for the handling of complex multimedia metadata and service oriented architectures engineers and community facilitators can create more generic services for the many communities with diverse but professional needs. Therefore, communities have to be incorporated in the community information systems engineering process.
In the talk we present a new reflective information system architecture called ATLAS offering self observation mechanisms for the establishment of a community-centered learning and improvement process for social software.
Open Graphical Learning Modeler: Brief intro to the OpenGLM authoring tool for IMS Learning Design
Prepared for Theory and Practice of Design for Learning Workshop @ Online Educa 2011, Berlin, Germany
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Interactions for Learning as Expressed in an IMS LD Runtime Environment
1. Interactions for Learning as
Expressed in an IMS LD Runtime
Environment
Michael Derntl1 Susanne Neumann2 Petra Oberhuemer3
1 RWTH Aachen University, Advanced Community Information Systems
2 University of Vienna, Center for Teaching and Learning
3 University of Vienna, Educational Affairs
derntl@dbis.rwth-aachen.de
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
1 This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License.
2. Advanced Community Information Systems
(ACIS)
Responsive
Web Engineering Community
Web Analytics
Open
Visualization
Community
and
Information
Simulation
Systems
Community Community
Support Analytics
Lehrstuhl Informatik 5
Requirements
(Information Systems)
Prof. Dr. M. Jarke
2
Engineering
3. Motivation
IMS Learning Design (LD) was developed as a
specification supporting any pedagogical approach [1]
Separation of environments for designing units of
learning (i.e. the authoring environment) and running
units of learning (i.e. the runtime environment)
Challenge: unclear how a deployed package will appear
in a VLE
Much previous research (and tools) about conceptual
and authoring issues; little research about expression of
pedagogical aspects at runtime
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
3 [1] IMS Global: IMS Learning Design Information Model, Version 1.0. http://is.gd/imsldv1 (2003)
4. IMS LD Structure in a Nutshell
Components are weaved into a method following a
stage-play metaphor
Act 1 Act 2 Act n
Role-Part 1 Role-Part 2 Role-Part n Method
Components
Role Activity Environment Activity Structure
Tasks LOs Tools
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
4
5. Objectives
Analyzing the expression of pedagogical aspects in
IMS LD runtime with focus on multi-role settings
(interaction)
– Visual presentation
– Interaction metaphors
Identifying shortcomings and recommendations for
IMS LD runtime developers
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
5
6. Methodology (1)
Player selection
– Several players are available, e.g. GRAIL, SLeD, CLIX,
Astro Player, …
– Original plan: SLeD and AstroPlayer
– But: AstroPlayer lacked support of some features (e.g.
display multiple activity descriptions)
– So: SLeD!
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
6
7. The SLeD Player
Navigation Content Area
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
7
8. Methodology (2)
Selection of framework for pedagogical aspects
– Several candidates like Reeves‟ pedagogical dimensions
[2] or Reigluth/Moore framework for comparing
instructional strategies [3]
– Reigeluth/Moore allow precise and multi-faceted analysis
of learning interactions [2] Reeves, T.: Evaluating What Really Matters in
Computer-Based Education. (1997)
– Types of interactions: [3] Reigeluth, C.M., Moore, J.: Cognitive Education
and the Cognitive Domain. In: Reigeluth, C.M. (ed.),
Instructional- Design Theories and Models, pp. 51-68.
Lawrence Erlbaum, Mahwah, NJ (1999)
Human Non-human
Student Student Student Student Student
– – Other – – – Other
Lehrstuhl Informatik 5
(Information Systems)
Teacher Student Tools Information Environment
Prof. Dr. M. Jarke
8
9. Methodology (3)
Selection of IMS LD Units of Learning (UoLs)
– Solicited real-world UoLs from ICOPER consortium members
– Selection based on diversity and feature coverage
UoL Features
Deconstructivism Learner & teacher roles; Support activities, Project exploration
Modern architecture Learner & teacher roles; Brainstorming, reading, preparation of
presentation; Resource and tool usage; Support activities
Skyscrapers & Homes A Two learner & one teacher role; Reuse of learning objects and
activities; Two plays
Skyscrapers & Homes B Only learner role; Path selection; Interaction with content; Reflection
and summarizing
Shared outcome Five roles: teacher, two teams (members + coordinators); Split paths;
Role selection; Conditional activity completion; Support activities
Lehrstuhl Informatik 5
(Information Systems) Blog collaboration Learner & teacher roles; Content selection; Blogs; Discussion; Final
Prof. Dr. M. Jarke
9
reports
10. Methodology (4)
UoL analysis
– Play all paths through each UoL with all roles
– Record support and obstacles for any interaction type
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
10
11. Student – Student
Awareness of interaction only when
– explicit instructions (e.g. in the activity description)
– use of services like chat or forum
Forum
– Missing instructions
– Unclear which roles are assigned
When individuals assigned to multiple team roles
– Unclear when to act in what role
– Roles and UoL selection meshed single drop-down list
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
11
12. Student – Teacher
Key interaction; typically teacher in a support role
Problems during runtime
– Separate views on the UoL
– Unclear when to support which role
– Unclear status of supported roles (if known) – e.g. support
required, learners„ status of completion …
Lehrstuhl Informatik 5
Student (l) vs. teacher (r) view in SLeD
(Information Systems)
Prof. Dr. M. Jarke
12
13. Student – Teacher
UoL portion in Astro Player – more structure but no better
Phases (IMS LD act) provide a hint but:
– Matching e.g. in Phase II (1 vs 4 activities)? – Requires guessing, but:
Lehrstuhl Informatik 5 – No way to see the other role„s view – Guessing impossible
Supported roles have no idea that there is any support
(Information Systems)
Prof. Dr. M. Jarke
13
14. Student – Teacher
IMS LD mechanism: learning vs support activity
– Support activity optionally (!) has supported role(s)
– From the IMS LD spec: “When the optional role-ref element is
set, […] the same support activity is repeated for every user in
the role(s). When the role-ref is not available, the support
activity is a single activity (like the learning-activity)” [1]
Problems
– Activity distinction known to be difficult to understand [4]
– Same display as learning activities
– If role-ref not set the only instruction can come from the
description
– Strict separation of role views hampers understanding of
supporting and supported role
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
[4] Neumann, S., Oberhuemer, P.: User Evaluation of a Graphical Modeling Tool for IMS Learning Design. Advances in Web Based
14 Learning – ICWL 2009, pp. 287-296 (2009)
15. Student – Tool / Environment
Difficult distinction tool – environment/manipulatives
– In a VLE context, the tool is and provides the “environment”
In some UoLs there will be VLE external tools
Common practice: show the
hierarchical structure in the XML
package in the UI
– Problematic with Activity Structures
(selection, sequence)
– Note: “SEQUENCE” / “SELECTION”
are part of the titles (by designers)!
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke – Where does what end?
15
16. Student – Tool / Environment
Even more problematic with Role-Part (within Act)
Activity Structure
multiple activity descriptions Learning Activity
and environments Activity Description
Item
Beware of conditions! Item
Activity Structure
– Unexpected appearance / Learning Activity
disappearance of activities Activity Description
Item
– Hard to discern these activities Item
(only the icon distinguishes) Environment
Learning Object
– Impossible to anticipate the Item
upcoming path Item
Learning Activity
– No qualitative info presented on Activity Description
Lehrstuhl Informatik 5
UoL design Item
(Information Systems)
Prof. Dr. M. Jarke
Item
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17. Student – Information
Here: interactions with activities and learning objects
Difficult to understand difference between activity
descriptions (AD) and learning objects (LO)
– AD attached to activity
– LO attached to environments linked to activity
– LOs mentioned in the ADs need manual lookup in the
navigation tree; activity as referencing element only
– In SLeD multiple ADs appear awkwardly
Solutions?
– Integrate LOs more tightly with the activity GUI
– SLD 2.0 does not consider environments at all [5]
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
17 [5] Durand, G., Belliveau, L., Craig, B.: SLD 2.0 XML Binding. http://tinyurl.com/sld2-0-xml (2010)
18. Wrap Up
No explicit linkage between activity description (main area) and
environment objects (navigation)
– Requires LD authors to provide this info contradicts the design/runtime split
Provide in-place access to information within an activity
Roles and their interaction poorly represented
– Unclear “impersonation” status
– Missing info on currently collaborating and supported/supporting roles
Explicitly display this info (USP of IMS LD?!)
Tree based navigation
– Little process-related hints in a tree
Depict the process, the current status, and the changes
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
18