XAPI Introduction (C)

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xAPI Introduction Jessie Chuang Classroom Aid Inc.

description

An introduction to the latest learning standard Experience API, xAPI.

Transcript of XAPI Introduction (C)

xAPI Introduction

Jessie Chuang

Classroom Aid Inc.

Time to Rethink Learning !

Mobile learning

Blended learning

Distributed learning

Flipped Classroom

Inquiry-based learning

Self-directed learning

Social (peer) learning and collaboration

Cooperative Problem Solving

70-20-10 model of learning

Performance support

Knowledge Management

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Recording Learning Events

Social Learning

Group Learning

image credit: Search Engine People Blog

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Technology is evolving very fast and segmented

Mobile first!

Simulations, AR, location-based learning, wearables, IoT ...

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Introducing xAPI...

xAPI tracking all kinds of learning experiences

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Recording Learning Events

Learning happens in interactions:

openclipart.org

Instructors, Peers, Experts.

Contents: Courses, Books,

Web pages, Games, AR .

Activities(making, exercises, researching, online, offline .)

Learner

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The xAPI specification has two primary parts

defines the syntax of the xAPI data format (data model)

the vocabularies should be community-driven

all activities and context can be tracked

any enabled application/device can send statements

defines the characteristics of learning record stores (LRS) - a crucial component of xAPI

data can be exchanged between LRSs (set free from LMS)

learner can have life-long personal learning locker

LRSs need to validate xAPI statements

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Course

Webpage

Game

Simulator

Coaching

Social

Learning

Project

Mobile Apps

LRS

Learning data is sent to LRS

Other activities

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LMS

LRS

LRS

Reporting

Tool

Learning records can be delivered to LMSsLRSs or Reporting Tools.

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A Whole Picture

LRS communicates with all xAPI-enabled software tools to collect learners data. It records group learning, informal learning(e.g. playing games, performance support...), and social learning learning-based activity stream - on any device or platform.

Stian Hklev

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LRS

An LRS is defined by two interfaces:

Statement interface (statement API)

Document interface - this interface handles three types of documents

State interface (state API)

Activity profile interface (activity API)

Agent profile interface (agent API)

The LRS is responsible for

validating that the system sending data is authorized,

checking that the data being sent is xAPI-compliant,

storing the data properly,

making that data available to any other authorized system or activity provider when asked.

Advanced Applications of xAPI

- Data Transfer based on RESTful HTTP w/i LRS

Agent Profile API

personal info., learner profile and modeling, user settings, learning journal, career plan & goal

an integrated picture of a learner activities across systems and devices with multiple identities

Activity Profile API (for activity provider)

interactions between learners (collaboration, social or competition)

learning planning tool (access to or update the LRS internal definition of a given activity id, even before the activity sends any statement)

State API

persist state across devices

Authentication services, querying services, visualization services, and personal data services are some examples.

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LRS and possible services

from ADL Andy Johnson

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Recording Learning Events

This is only the basic idea. Crafting the statements with more context and related information is necessary to support analytics and reporting.

Based on JSON, xAPI originates from ActivityStreams (AS): stream of activity data statements(borrowed from social analytics), and has been modified for learning

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Semantic

Contextualized

From any device and sensor

LRS frees the learning data so they can be put together, analyzed, modeled, reused, carried with learners and accumulated life-long

xAPI tracking is...

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11 Attributes in xAPI Data Format

Unique Identifier

Actor (required)

Verb (required)

Object (required)

Result

Context

Timestamp

Stored (internal recording timestamp)

Authority

(Protocol) Version

Attachments

All information in XAPI statements can be separated into :

meta-data,

descriptive information, and

complementary data.

Syntax-1

Actor:

Agent (= persona) or group (multiple IDs allowed)

Verb:

ID = an IRI(URL) = a specific semantic meaning +

human readable display

Object:

an agent, a group, a statement or an activity(most common)

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Syntax-2

Activity:

ID = an IRI(URL) = with a specific boundary (granularity)

Definition:

Name

Description

objectType

Extentions (useful to customize reporting)

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Syntax-3

Result:

Score

Success

Duration

Completion

Response (learners response to the experience)

Extentions

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Syntax-4

Context:

Registration (differentiate multiple attempts)

Instructor

Team

ContextActivities (parent, grouping, category, other - like related lesson)

Revision

Platform

Language

Statement (refer to one other statement for a whole experience)

Extentions

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Context, Context, Context

The XAPI differentiates between the core context and the wider context.

The core context includes the instructor(s), the direct peers involved in an activity (team), the learning environment (platform), the language that was used in the performance, and a framing statement for an activity (e.g., the course that relates to the activity).

The extended context includes a set of data-records about the wider context of a learning activity. This wider context is not explicitly specified and can include the location of the learner, the wider (social) relations, the duration of an activity, environmental factors (e.g., temperature or noise level) etc. The format and the content of the wider context is specific to the AP and is not subject to the interoperability of the data format.

Thats why xAPI can assess learner styles and soft skillswe can collect different kinds of evidences through good learning designs.

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Sky is the limit

If a system is to be stable the number of states of its control mechanism must be greater than or equal to the number of states in the system being controlled.

By limiting the data that can be transferred in a statement, we are putting ourselves in a box that will make the Tin Can specification hard to use as technology evolves.

Not like SCORM, with xAPI, there is no limitation of learning designs and tracking relevant evidences.

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Identify Design Profile

ADL asked CoPs work on Design Profiles:

Finally, we will collaboratively work on standardizing how specific types of use cases should be expressed using the xAPI. -- ADL

The conventions and rules on how to use the xAPI can be decided upon by each CoP and applied to the base xAPI specification as profiles.

Design Profile: A reusable template that conveys how to record a specific type of learning experience and should be produced by an xAPI CoP during or after the process of developing a controlled vocabulary. A design profile should contain metadata and a JSON representation of the following: profile name, use case description, actor, verb, object/activity type, context, and possible results. -- ADL

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Profile Design Example - Fromative Assessment

Basic considerations:

Key actors

What they are expected to do

What resources are used

sequence of activities

Example:

Learner XYZ launched question 1234 at 14:30:21 on 2014-04-05.

Learner XYZ responded [to] question 1234 with 12 at 14:30:31 on 2014-04-05.

Learner XYZ asked for a hint at 14:30:54 on 2014-04-05.

Learner XYZ responded [to] question 1234 with 8 at 14:31:11 on 2014-04-05.

Learner XYZ launched for a video lesson 1234V at 14:31:54 on 2014-04-05.

Learner XYZ responded [to] question 1234 with 9 at 14:32:11 on 2014-04-05.

Learner XYZ completed question 1234 at 14:32:11 on 2014-04-05.

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Lifeguard

Example1

From TinCanApi.com

Driving simulator

Example 2

From TinCanApi.com

Example 3

Game

From TinCanApi.com

Example 4

An employee

From TinCanApi.com

Learning, doing, knowledge transfer, and productivity tracking all combined

From Floatlearning.com

(check out the xAPI statements)

xAPI + Open Badges => Learner ePortfolio

Both are representing learner data by exploiting HTTP, JSON, and REST - simple, lightweight method that lowers entry barrier for developers. Together, they offer a new way to think about constructing interoperable learner model data!

Read more:

Are Open Badges the Future for Accrediting Skills?

from Doug Belshaw

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from BadgeOS.org

Every learner is a developing constellation.

Re-thinking learning needs, start from re-thinking assessment !

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The whole picture =

Training and Learning Architecture(TLA)

ePortfolio

Learner modeling

Machine readable

Competency standards

Knowledge map

Standard alignment

xAPI COP

Common vocabulary

Learning Design

Sharing of metadata & paradata (LR)

Re-usability

Semantic analysis

TLA Services

TLA will also include services for managing learner profiles. Open Badges can be referenced by learner profiles, which will likely contain other learner data such as goals, reflection, etc.

The TLA will also include services for creating and accessing competency definitions to serve as a common way to reference educational standards, learning objectives, and competency definitions through web APIs

(Damon Regan, Elaine M. Raybourn, and Paula J. Durlach)

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xAPI = building blocks

Elements of DataEnriched Assessment

Continous

There is no need to distinguish between learning activities and moments of assessment. Instead, a model of the learners knowledge state is continually assessed and updated. This enables learning to be modeled as an ongoing process rather than as a set of discrete snapshots over time.

Feedback - oriented

Feedback can be provided directly to the learner, to an instructor, or to the system (e.g., an adaptive test or an intelligent tutor).

Personalized feedback - for instance, based on a design principle proposed by Shute (2008) in a review of the feedback literature, the system could offer direct hints to lowachieving learners and reflection prompts to higherachieving learners.

The effective presentation of feedback in online learning environments poses an interesting design challenge.

Elements of DataEnriched Assessment (cont)

Multifaceted

Learners abilities to learn from resources or interactions with others is influenced by factors beyond their current knowledge state. (the following facets have been researched)

Affective state the learner's mood or emotions

Interpersonal competencies(communicate, collaborate)

Selfregulation(study strategies) (Zimmerman, 1990)

Goal orientation(a learners purpose)

Mindset(a learners beliefs)

Learners attributions of social cues in their environment (social belonging)

The multiple facets of a learner translate into key competencies for individuals to be productive and resilient in future educational and professional settings. Explicitly assessing these competencies as desired outcomes of learning can inform the design of learning environments to support their development and thereby better serve learners for the long term.

Whats your goals? or problems to solve?

What are KPIs? break down performance metrics?

What feedback loops should be built?

How Sears is using an LRS to aggregate data from multiple LMS systems

How to translate and migrate historical data from existing systems into an LRS

What tools and techniques were used to drive large scale near real-time competency rollup reporting

How to sync HRIS data with an LRS to define groups of people

http://www.elearningguild.com/DevLearn/sessions/session-details.cfm?event=261&track=50&fromselection=doc.3503&from=sessionslist&session=5815

The old way how we design courses and even our documents makes it impossible for an employee to find the one piece of information they need at the time they need it. And it makes tracking anything useful in it even more difficult.

Successful Story of Driving KM through #Gamification

Accenture began leveraging a gamification approach to its KM program over five years ago with the launch of a collaboration recognition and reward program called the Addo Agnitio Award (A3). It started out by measuring a modest set of key activities that employees could undertake to demonstrate their commitment to embracing collaborative behaviors. Those activities were assigned point values, and a collaboration and knowledge sharing score was calculated for all employees. In the intervening years, more than 30 activities have now been identified to demonstrate three key behaviors:

connecthow people connect to the content and communities they need to do their job,

contributethe level at which people are contributing their knowledge and the impact of those contributions on other people, and

cultivatethe willingness to interact with and build upon the ideas and perspectives of other employees, to help nurture a spirit of collaboration.

http://wp.me/p3SgJG-2eD