Immersive technologies and recruitment assessment and lifelong learning

Immersive Technology Strategieswww.davidwortley.com

Immersive Technologies for Recruitment, Immersive Technologies for Recruitment, Assessment and Lifelong LearningAssessment and Lifelong Learning

Moscow Edutech 2011David Wortley FRSA


Key TakeawayImmersive technologies will be used for continuous formative assessment, lifelong learning, career development and e-portfolios / profiles

We are entering the era of the portable lifelong personal coach / mentor facilitated by serious games, social networks, virtual learning environments and cloud computing


Topics

Definition and role of Serious Games and Immersive Technologies

Example Applications Future Challenges and Trends Summary and Conclusion


Definition and Role of Serious Games and Immersive Technologies


Immersive Technologies

Games Virtual Worlds Social Networks

Immersive Technologies provide an attractive, accessible and affordable space in which to devote our discretionary time, attention and

money


Serious Games and Immersive Experiences

Involve Challenges, Rules, Rewards, Physical and Virtual Worlds, Social Networks, Assessment, Profiles, Personal Development and Commercial Exploitation


Serious Games are Our Personal Choice

Serious Games are where we choose to spend our discretionary time, attention and finances which makes

them very important commercially and developmentally


Attractive, Accessible, Affordable

Immersive technologies focus on attractiveness (engagement), accessibility (no barriers) and

affordability (cost and time)


The Importance of Immersive TechnologiesThe Importance of Immersive Technologies

Immersive Technologies are important because they provide an ideal platform for engagement, motivation, assessment,

training needs analysis, profiling, coaching and development


What are the Key Features ?

Personalisation / relevance Interface and UbiquityCost in time and moneyAbility to control / shapeRichness of experienceChallenge / motivation Intrinsic and extrinsic rewards


Example Applications


Learning through Games

Watch, copy, get feedback, iterate and share


From Cradle to Grave

Immersive technologies will engage, motivate, assess, adjust and profile


Profiling and Needs Analysis

Identifying strengths and weaknesses, profiling and personalising needs


Building Knowledge Communities

Intel’s Planet Blue is an internal social network


Connecting the Physical & Virtual

Virtual visualisation of real time data


The Digital Alter Ego

The mobile device will become our digital mentor


Future Challenges and Trends


In a Nutshell

Successful Immersive technologies need multiple disciplines


Common Language ?

Experts speak in different languages


Expectations

Generation Y learners expect high levels of engagement


Expectations

Clients expect value for money and modest costs


Likely Solution

Software which has embedded expertise and resources and partners to provide pedagogical and storytelling

skills


Simulations linked to real data


New Applications

Using Sensor interfaces to control learning activities


Summary and Conclusion


Key TakeawayImmersive technologies will be used for continuous formative assessment, lifelong learning, career development and e-portfolios / profiles

We are entering the era of the portable lifelong personal coach / mentor facilitated by serious games, social networks, virtual learning environments and cloud computing


What will this mean in practice ? Personalised learning Integrated games-based learning & assessment Intelligent persistent lifelong profiling Collaborative peer to peer learning Learning by discovery of new knowledge Virtual worlds linked to real world data Tutor/Mentor/Coach tools for content management Learning communities


Questions


Immersive Technologies for Recruitment, Immersive Technologies for Recruitment, Assessment and Lifelong LearningAssessment and Lifelong Learning

Moscow Edutech 2011David Wortley FRSA

Education

Immersive technologies and recruitment assessment and lifelong learning