designing data enabled learning platforms
Post on 13-Apr-2017
412 Views
Preview:
TRANSCRIPT
© 2016 Ness SES. All Rights Reserved 1
Designing for online learning environments in the age of big data. James&Williams,&&Director&of&Digital&Services&@jwilliams_uk&
Sawad&Brooks,&&Lead&User&Experience&Designer&@Rrrgggbbb&
© 2016 Ness SES. All Rights Reserved 2
Market overview – online learning today Education Theory How to leverage data Design approach > prototyped example Design principles
© 2016 Ness SES. All Rights Reserved 3
Online Learning Environments
© 2016 Ness SES. All Rights Reserved 4
Online learning is currently not engaging enough and loses people’s attention.
35%
56%
4% 5%
HarvardX and MITx - First Year Engagement (after sign-up)
Never engaged
Viewed less than half course content
Explored half or more of course content w/o certification
Earned certificates
© 2016 Ness SES. All Rights Reserved 5
When used as a tool to compliment traditional teaching in schools and universities it can have a negative effect…
30% of students in a class cannot be depended upon to have reviewed online material on their own …Teacher time is then spent “catching them up,” delaying the rest of students..
© 2016 Ness SES. All Rights Reserved 6
Online experiences are not as interactive as classrooms
Online When a student doesn’t understand a concept they replay the content. Repeating it does not necessarily make it more understandable.
vs
Classroom If a student has a question about a concept, the teacher will often attempt to reframe the concept in a different way.
© 2016 Ness SES. All Rights Reserved 7
Evolving online learning environments by leveraging data
© 2016 Ness SES. All Rights Reserved 8
- Trigger and drive improved learning experiences. - Provide Information on how students progress, to course correct them. - Enrich their study and present similar material in a different way.
Data and machine learning techniques can:
© 2016 Ness SES. All Rights Reserved 9
Length of dwell time Touches Verbal responses
Affective signs Initial assessment Bitesize assessment
Data analytics leads to finding behavioral patterns… which can improve the learning speeds of everyone
Data studied
© 2016 Ness SES. All Rights Reserved 10
“You don’t understand anything until you learn it more than one way.” – Marvin Minsky, Legendary AI scientist and Turing Award winner
We need to evolve understanding From linear content like books… To networked content like classroom discussion. Enabling Multimodal Learning increases cognitive processing ability.
© 2016 Ness SES. All Rights Reserved 11
Enable uploaded materials and their constituent components to relate or connect with each other and create a hierarchy of relatedness: Paragraphs, images, graphics, chapters, notes, videos, podcasts become closely linked and accessible. Students use what they prefer to learn from.
Componentizing networked content can enable multi modal learning over the linear experience
© 2016 Ness SES. All Rights Reserved 12
Within-document
Within-course
Cross-courses External Systems
Cross-documents
Networked componentized content uses different sources to enrich the learning experience.
© 2016 Ness SES. All Rights Reserved 13
Focus on learner needs to understand their ideal personalized learning journey
© 2016 Ness SES. All Rights Reserved 14
Focus on the needs of the learner to design the experience
Nancy Learner Needs
• Clear outline of progression and achievement.
• Real time understanding of knowledge strengths and gaps.
• The right content and activity focus at the right time, tailored to me.
• Different ways of processing the content
• Access to variety of sources that enrich my learning.
Use proto personas
© 2016 Ness SES. All Rights Reserved 15
Enhance learner outcomes with a data enabled platform
Learning results Explore and process Assessment Immersive content consumption
Initial Learning assessment Stage
© 2016 Ness SES. All Rights Reserved 16
Focus on the learner goals and needs at each stage
Learning results Explore and process Assessment Immersive content consumption
Initial Learning assessment
• The best way to learn for me
• Learn and process • Tips, hints and
guidance helpful
• Understand errors • Tested on what is needed • Understand my learning status • Guidance to research content
• Create a depth of knowledge • Solidify learnings
• Understand status
• Plan course of action
Learner goals and
needs
Stage
© 2016 Ness SES. All Rights Reserved 17
Explore the opportunities that your data sources provide
Learning results Explore and process Assessment Immersive content consumption
Initial Learning assessment
• The best way to learn for me
• Learn and process • Tips, hints and
guidance helpful
• Understand errors • Tested on what is needed • Understand my learning status • Guidance to research content
• Create a depth of knowledge • Solidify learnings
• Understand status
• Plan course of action
Learner goals and
needs
Stage
Data driven platform
opportunities
Personalized order of learning OPTIONS
Live content highlighting nudges connected to
your scoring
Real-time scoring results
Personalized assessments
Progression breakdown
Real-time learning recommendations
Related course content
Webcast event
Youtube/ 3rd party videos
User gen content recommendations
Blog posts/ Podcasts wiki
Topic forums
Personalized course next steps OPTIONS
Detailed course progression breakdown
Real-time learning recommendations
User gen content recommendations
Self evaluations Learning journey breakedown
© 2016 Ness SES. All Rights Reserved 18
Explore the different routes a personalized journey can take
Learning results Explore and process Assessment Immersive content consumption
Initial Learning assessment
• The best way to learn for me
• Learn and process • Tips, hints and
guidance helpful
• Understand errors • Tested on what is needed • Understand my learning status • Guidance to research content
• Create a depth of knowledge • Solidify learnings
• Understand status
• Plan course of action
Learner goals and
needs
Stage
Data driven platform
opportunities
Personalized order of learning OPTIONS
Live content highlighting nudges connected to
your scoring
Real-time scoring results
Personalized assessments
Progression breakdown
Real-time learning recommendations
Related course content
Webcast event
YouTube/ 3rd party videos
User gen content recommendations
Blog posts/ Podcasts wiki
Topic forums
Personalized course next steps OPTIONS
Detailed course progression breakdown
Learner journey
Learner assessment
Personalized Course options 2
Personalized course option 1
Option 2
Option 1
Option 3
Assessment & scoring
Review progression
Personalized Course options 1
Personalized Course options 2
View related content 1
View related content 2
Assessment & scoring
Assessment & scoring
Personalized Course options 1
Personalized next steps option 2
Real-time learning recommendations
User gen content recommendations
Self evaluations Learning journey breakdown
© 2016 Ness SES. All Rights Reserved 19
Prototype the experience
© 2016 Ness SES. All Rights Reserved 20
Assessment to calibrate the system. Learners takes quick bitesize tests to customize their journey
© 2016 Ness SES. All Rights Reserved 21
Personalized content recommendations and learning routes based on aggregated data sources of information
© 2016 Ness SES. All Rights Reserved 22
A transparent learning platform Shows what information is gathered and clearly improves effectiveness with time with help from learner inputs.
© 2016 Ness SES. All Rights Reserved 23
Enable peer to peer communication between learners, teachers & subject matter experts to ask for help and support and promote engagement
© 2016 Ness SES. All Rights Reserved 24
Visualizing their progress students can see their success and where more effort is recommended and where to go to learn more
© 2016 Ness SES. All Rights Reserved 25
Principles of Designing for Learning Environments
© 2016 Ness SES. All Rights Reserved 26
Principles of Designing for Learning Environments
Talk with the teachers and learners to understand their motivations, needs, goals and individual and collective behaviors. Fit the design learning model to the users, not the users to the model. Research before and test after. Create user facing stories for each algorithm to capture the motivation of the user and what action they might take from the information - so that the solution is always user-centric.
© 2016 Ness SES. All Rights Reserved 27
Make the actions and decisions of the learning product transparent so the learner understands the logic for what is happening. Remember that learning is fun – the engagement factor is paramount. From the start, create meaningful categories that let you make sense of the data, tell a story about the experience, and ensure you develop a way to share and discuss data in your organization; start by defining the basics together.
Principles of Designing for Learning Environments
top related