Quality Assurance Strategies for High Quality Learning Objects

Quality Assurance Strategies for High Quality Learning Objects Karin Lundgren-Cayrol Suzanne Lapointe Gilbert Paquette LICEF, TÉLUQ - UQAM MERLOT CONFERENCE 9 August 2006

Overview • • • Goal and Objectives Learning Ressources (LR) LR Repository Types Evaluation Criteria LR Life-Cycle and Quality Assurance Strategies • Conclusion

Goals and objectives Provide a set of Quality Assurance Strategies based on the Learning Resource Life-Cycle Objectives • Establish viable quality assurance strategies • Provide some pertinent evaluation criteria • Help plan methodological help for repository designers and learning resource authors and users

A Learning Resource Definition Electronic book Video Image Any entity, digital or non-digital, which is intended to be, or may be used for the purpose of learning, education or training . CDROM SCORM Object Learning Design Software

Learning Resource Repository Types • Private repositories: author bibliography and productions, students personal portfolio, course student production showcase A few metadata, quality is in the usefulness of the repository to the participants • Community repository: a university department, a group of professor in the same domain, a research repository Need a larger effort and a high degree of quality insurance, use a domain ontology (specific classification and relation between resources) • Public repository: totally open (Creative commons), limited access or repository – Protect the consumer – Protect the IP through CC or a DRM system.

Evaluation Criteria Dimensions • • • Pedagogical Quality Content clarity and conciseness, instructional strategies aligned to the learning objectives, appropriate media according to target audience, etc… Ergonomy User-friendliness, motivating, visually attractive, built-in accessibility features, etc. . Interoperability, reusability Technical independence and robustness, metadata schema and tagging procedures, conformance to standards

The LORI Evaluation Criteria • • • Content Quality Veracity, accuracy, balanced presentation of ideas, and appropriate level of detail Goal Alignment • Usability Ease of navigation, predictability of the user interface, and the quality of UI help features Alignment among learning goals, activities, assessments, and learner characteristics • Accessibility Adaptive content or feedback driven by differential learner input or learner modeling • Reusability Feedback and Adaptability Motivation Ability to motivate, and stimulate the interest or curiosity of, an identified population of learners Visual Design of visual and auditory information for enhanced learning and efficient mental processing Support for learners with disabilities Ability to port between different courses or learning contexts without modification • Standard conformance Adherence to international standards and specifications

LR Life-Cycle and Quality Strategies Life-cycle of a LR After inclusion Before inclusion Design/ Production During contribution Adaptation/ Reuse/Assignment Deposit and metadata referencing Quality of the process Quality of the object Quality of Metadata

Before Inclusion • Design and Production Strategies – Use a solid and adapted ID method – Identify clearly knowledge and user competencies – Favor pedagogical strategies putting the learner in the center. – Apply evaluation criteria during development and implement at least one learner evaluation cycle – Be informed about Access 4 All production principles – Let (content, pedagogy, media, delivery) specialists use their expertise

Authoring Actors • • • Content Expert Instructional Designer Media Specialist Delivery Specialist Project Leader Build or integrate objects that you can quality certify Interactive Objets Are Software

Instuctional Engineering Method MISA Problem definition 100 Training system 102 Training objectives 104 Target Learners 106 Actual situation Knowledge Modeling 210 Knowledge modeling principles 212 Knowledge model 214 Target competencies 310 Learning units content 410 Learning instruments content 610 Knowledge and competency management Materials Modeling 230 Media principles 330 Development infrastructure 430 Learning materials list 432 Learning materials models 434 Media elements 436 Source documents 630 Learning system / resource management 108 Reference documents Instructional Modeling 220 Instructional principles 222 Learning events network 224 Learning units properties 320 Instructional scenarios 322 Learning activities properties 420 Learning instruments properties 620 Actors and group management Delivery Modeling 240 Delivery principles 242 Cost-benefit analysis 340 Delivery planning 440 Delivery models 442 Actors and user’s materials 444 Tools and telecommunication 446 Services and delivery locations 540 Assessment planning 640 Maintenance / quality management

Learning Design as Composed Objects Media Elements Basic Resources Documents Tools Actors Operations Scenarios Processes Units of Learning

During Contribution • Multi-actor expertise for metadata – Content Expert / Author • Title, LR language, key words, description, type, version, contributors, intended end user, learning context • Text mining algorithms can help – Library technician • Version, classification, rights, relations metadata • Overall respect of the standard used – Computer Technicians • Format, size, required conditions, Installation Remarks, meta-metadata, record language • Can be automated • In general, reduce form-filling: use wizards, smart automatic or semi-automatic computer agents

During Contribution • Demand Membership for contributors: responsability and motivation; make contributors visible • Make sure that the author provides the following infos: – – Degree of Pedagogical Reusability Content quality Interface quality How it might be an efficient learning or teaching tool

Completeness or Usability

After Inclusion in the Repository • • • Retrieval quality, maintenance should be planned at inclusion Provide peer reviews and evaluations from actual users/reusers. Advertise innovative and high quality resources Provide recommendations to authors for improvements Propose search options: metadata, classification, free text etc.

Give me a chance! Too Much Overkills Too Little Just Kills Karin Lundgren-Cayrol Suzanne Lapointe Gilbert Paquette LICEF, TÉLUQ - UQAM MERLOT CONFERENCE 9 August 2006