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 Meeting minutes: http://xapi-cop.net/zh/2016/05/17/2016-04-22-cop-meeting/

1. XAPI 中文实践社群月会
XAPI Chinese CoP Meeting
Apr.22, 2016
Jessie Chuang
jessie@classroomaid.org

2. 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

3. 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)

4. Case Study

5. 4C/ID Model for Complex Learning
Complex 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

7. 4C

8. Learning Tasks
Learning 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 ...

9. Supportive Information
Supportive 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

10. JIT Information
JIT 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 ...

11. Part-Task Practice
Part-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 ...

12. Case Study
(應用 xAPI 進行使用資料收集與反饋設計)

14. Technology-enabled Assessment
Support 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

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

16. Semantically Legible DataPoints
For 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

17. 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