XAPI 中文实践社群月会XAPI Chinese CoP Meeting

Apr.22, 2016

Jessie Chuang

jessie@classroomaid.org

中文实践社群网站(含学习与参考资源)

http://xapi-cop.net/zh/

中文实践社群脸书群组https://www.facebook.com/groups/648340368618407/

xAPI Visualization and Analytics services (w/i developer doc. & recipes)

http://www.visualcatch.org/

线上课程(含实作与反馈): XAPI 设计入门http://xapi-cop.net/zh/xapi-design-beginners-guide/

每周一次(周四上午9:30-11:00AM)，共五堂课，含课後案例实作+指导反馈

建议、询问或报名: mlearning@classroomaid.org

Community/Resource Links

Topics● Visca 嵌入儀表板的討論

● XAPI 國際實施案例分享

● 中文社群業者案例分享

● 新配方的設計與討論(課中、作業、學習設計/計畫)

Case Study

4C/ID Model for Complex LearningComplex learning is always involved with achieving integrated sets of learning goals—

multiple performance objectives.

NOT acquiring each of these constituent skills separately, but to use all of the skills in

a coordinated and integrated fashion while doing real-life jobs. (i.e., integrated

objectives)

● Schema construction for nonrecurrent aspects (schema construction)

● Rule automation for recurrent aspects (drill-and-practice)

Citation:

http://www.cogtech.usc.edu/publications/clark_4cid.pdf

http://www.nwlink.com/~donclark/hrd/learning/id/4c_id.html

4C

Learning TasksLearning Tasks: concrete, authentic, whole task experiences that are provided to

learners in order to promote schema construction for nonrecurrent aspects and, to a

certain degree, rule automation by compilation for recurrent aspects. Instructional

methods primarily aim at induction, that is, constructing schemata through mindful

abstraction from the concrete experiences that are provided by the learning tasks.

Design steps:

● Design learning tasks

● Sequence task practice

● Set performance objectives

Possible mediums:

LMS, Learning Design Tools,

Diversified Applications for

different purposes (integrated

through APIs and SSO), badging,

real-world job or project ...

Supportive InformationSupportive Information — information that is supportive to the learning and

performance of non-recurrent aspects of learning tasks. It provides the bridge between

learners' prior knowledge and the learning tasks. Instructional methods primarily aim

at elaboration, that is, embellishing schemata by establishing non-arbitrary

relationships between new elements and what learners already know.

Design steps:

● Design supportive information

● Analyze cognitive strategies

● Analyze mental models

Possible mediums:

CMS, eBook, curriculum,

presentation tools (video,

animation, VR, AR…) , tutorial,

knowledge base, adaptive

content recommender

JIT InformationJIT Information — information that is prerequisite to the learning and performance of

recurrent aspects of learning tasks. It gives learners step-by-step knowledge they need

to know in order to perform the recurrent skills.

Design steps:

● Design procedural information

● Analyze cognitive rules

● Analyze prerequisite knowledge

Possible mediums:

Mobile Apps, AR, Digital

Performance Support kits,

Instruction or reminder

embedded in job, mentors, peers,

AI assistance ...

Part-Task PracticePart-task Practice — practice items that are provided to learners in order to promote

rule automation for selected recurrent aspects of the whole complex skill. Instructional

methods primarily aim at rule automation, including compilation and subsequent

strengthening to reach a very high level of automatically.

Design step:

● Design part-task practice

Examples:

drilling practice of multiplication tables,

playing scales on musical instruments

Possible mediums:

Quiz, assessment, game,

simulation, apprenticeship,

IoT sensors in tool /

machine / environment ...

Case Study

(應用 xAPI 進行使用資料收集與反饋設計)

Technology-enabled AssessmentSupport learning and teaching by

communicating evidence of learning

progress and providing insights to

teachers; administrators; families; and

the learners. These assessments can be

embedded within digital learning

activities to reduce interruptions to

learning time.

2016 NATIONAL EDUCATION

TECHNOLOGY PLAN

U.S. DEPARTMENT OF EDUCATION http:

//tech.ed.gov

Citation: http://www.tandfonline.com/doi/pdf/10.1080/23265507.2015.1074870

Semantically Legible DataPointsFor instruction and assessment to become one, however, these need to be ‘semantically

legible data points’. Our definition of a semantically legible datapoint is ‘learner-

actionable feedback’. Every such datapoint can offer an opportunity that presents to

the learner as a ‘teachable moment’.

These datapoints can involve either or both a machine response to learner action or

machine-mediated human response, thereby harnessing both collective human

intelligence and artificial intelligence.

Semantically legible data are self-describing, structured data.

Bill Cope & Mary Kalantzis (2015) Interpreting Evidence-of-Learning: Educational research in the era of big

data, Open Review of Educational Research, 2:1, 218-239, DOI: 10.1080/23265507.2015.1074870

The Moderating Role of Collaborative Visualization in Team Knowledge Integration

Seeing versus Arguing - The Moderating Role of Collaborative Visualization in Team Knowledge Integration

(Jeanne Mengis, University of Lugano, Switzerland)

Key: self-explanatory dataviz available in real time