O slideshow foi denunciado.
Utilizamos seu perfil e dados de atividades no LinkedIn para personalizar e exibir anúncios mais relevantes. Altere suas preferências de anúncios quando desejar.
XAPI 中文实践社群月会
XAPI Chinese CoP Meeting
Feb. 19, 2016
Jessie Chuang
jessie@classroomaid.org
Topics
● XAPI Vocabulary spec. From ADL
● Linked Data / Semantic web. / Web 3.0
● Linked Data in education and content rec...
Draft v1.0 published in Feb. 2016:
Vocab Spec. - gitbook: http://bit.ly/read-vocab-spec
Vocab Primer - gitbook: http://bit...
“MUST” in xAPI Vocabulary Spec.
Anyone establishing new vocabularies and new vocabulary terms for xAPI MUST use
HTTP IRIs ...
Why Linked Data?
The ability to link data from diverse sources is a motivator for many projects, as
different CoPs seek to...
Linked Data / RDF - Resource Description Framework
RDF and JSON-LD work in a simple way of dividing information into tripl...
A cornerstone of the semantic web is its use of newer graph-based approaches
and technologies – such as the RDF and SPARQL...
For most types of data storage, there is the concept of some elements of data (whether they be for
example data nodes or d...
● A shift in thinking from publishing data in human readable HTML
documents to machine readable documents.
● It provides a...
DBpedia
Linked Data in Education
Content recommendation
Reasoned from OER Linked Dataset
and DBPedia dataset
Facebook OGP is a lightweight version of Semantic Web
Semantic Computing (SC)
It’s to represent concepts and their relations in an integrated semantic network
that loosely mimi...
Semantic Search
Semantic search is to improve search results by focusing on user intent and
how the search relates to othe...
http://searchengineland.com/google-launches-knowledge-graph-121585
Google Knowledge Graph API (to replace Freebase API)
The Knowledge Graph Search API (launched Dec. 2015) lets you find ent...
Learner
Learning DesignerData Analyst
● Interoperability
● Analytics (algorithms,
machine learning API)
● Recommender (con...
Layer of Data Management
Methodology of
Leveraging Big Data
It’s been used in...
Lean Startup Prototyping
Marketing Analytics
Business Intelligence...
More:
results, goals, history,
learner profile / preferences
/ habits / attributes, device ...
From: http://www.slideshare.net/phish108/ar-discovery-the-challenges-53902694
Sensors
Actuators
Learning
Planning
Activity/Agent Profile API
IRS, Quiz service
Integration of Workflow and Data flow *Adaptive design
*Bra...
Amazon --- “Anyone who doesn’t do this will be fired. “
Amazon.com is one of the best examples of a programmable enterpris...
Clients can listen for statements being pushed to them from the LRS.
Webhooks are a way to register client applications th...
Images from Hong Ding Edu. Tech.
Embedded VisCa
Dashboard for
teachers or learners
Case Study
课中出席、上课反应、形成性评量结果、回家作业与複习学习历程记录 =>
学生个别状况分类
(能力、态度、兴趣..., 个体 vs 群体)
学习资源 & 策略
matching
推荐内容/策略 to 学生 & 老师
● 网路免...
XAPI data
Whenever K fails practice
A in Hong Ding, VisCa
will notify 1Know
Assessment and practice service
Light Learning...
Monetize Your Data and Add Values (intelligence) !
● Let’s collaborate for consistency in:
○ Competency standards
○ User m...
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 ...
X api chinese cop monthly meeting   feb.2016
X api chinese cop monthly meeting   feb.2016
X api chinese cop monthly meeting   feb.2016
X api chinese cop monthly meeting   feb.2016
X api chinese cop monthly meeting   feb.2016
Próximos SlideShares
Carregando em…5
×

X api chinese cop monthly meeting feb.2016

Topics
XAPI Vocabulary spec. From ADL
Linked Data / Semantic web. / Web 3.0
Linked Data in education and content recommender
Semantic search and Google Knowledge Graph
APIs eat software (connect with partners and services)
How should we exploit data and build intelligence layer?
Case Study (Hong Ding Educational Technology)
Monetize your data and add value (intelligence)

  • Seja o primeiro a comentar

  • Seja a primeira pessoa a gostar disto

X api chinese cop monthly meeting feb.2016

  1. 1. XAPI 中文实践社群月会 XAPI Chinese CoP Meeting Feb. 19, 2016 Jessie Chuang jessie@classroomaid.org
  2. 2. Topics ● XAPI Vocabulary spec. From ADL ● Linked Data / Semantic web. / Web 3.0 ● Linked Data in education and content recommender ● Semantic search and Google Knowledge Graph ● APIs eat software (connect with partners and services) ● How should we exploit data and build intelligence layer? ● Case Study (Hong Ding Educational Technology) ● Monetize your data and add value (intelligence)
  3. 3. Draft v1.0 published in Feb. 2016: Vocab Spec. - gitbook: http://bit.ly/read-vocab-spec Vocab Primer - gitbook: http://bit.ly/read-vocab-primer “In addition to structural interoperability, semantic data interoperability is also needed for both humans and applications to meaningfully interpret the information being exchanged. “ AcrossX vocab registry is the first vocabulary registry besides ADL & IEEE ADB registries that completely follows the xAPI Vocab. Spec. : (by Jessie Chuang, Jason Haag) : https://w3id.org/xapi/acrossx ADL xAPI Vocabulary Spec.
  4. 4. “MUST” in xAPI Vocabulary Spec. Anyone establishing new vocabularies and new vocabulary terms for xAPI MUST use HTTP IRIs so that they can be resolved/dereferenced. Anyone creating new vocabulary terms MUST provide descriptive metadata by minimally using the recommended classes and properties in this specification, and associate the terms with a vocabulary (concept scheme). Anyone establishing a new vocabulary MUST publish a human-readable representation of the vocabulary dataset as HTML accessible at the IRI. Anyone establishing a new vocabulary MUST publish at least one additional machine- readable representations of the vocabulary dataset in RDF (e.g., RDFa, JSON-LD, Turtle).
  5. 5. Why Linked Data? The ability to link data from diverse sources is a motivator for many projects, as different CoPs seek to take advantage of semantically rich data that was previously spread across disparate sources. By adopting W3C’s RDF standard as the data model for xAPI vocabulary resources and their metadata, the xAPI specification can potentially gain a whole new level of precision for machine readability and semantic interoperability. Upon implementation of this vocabulary specification (and refinement of vocabulary publishing practices) the xAPI community will benefit from new capabilities - open up new doors for improved learning analytics, federated search (of vocabulary), dynamic look-up of xAPI vocabulary data within authoring applications, improved discovery and reuse of xAPI vocabularies, multilingual translation, and basic natural language processing capabilities. -- Jason Haag, ADL
  6. 6. Linked Data / RDF - Resource Description Framework RDF and JSON-LD work in a simple way of dividing information into triples: “subject – predicate – object.” RDF / JSON-LD 是 W3C 的语义网 (Semantic Web) 资料模型标準,其 Graph Data Model 是 NoSQL 的一种,基本组成成分为 Subject – Predicate – Object,称为 triples,叁者都是以 URI 来代表,Subject 与 Object 是任何可被识别的实体或资讯类 对象 (nodes),Predicate 代表这两者的关係 (edge, link)。 这样极简的构造允许结构或非结构化的资料数据互相整合,不须事先规定相同架构, 特别适合分岐、分散不同来源的大数据(Big Data)。 Linked Data 是语义网 (Semantic Web) 的正确实践。主要目的是让机器可读懂 (machine-interpretable) 所传递的资料,以发展人工智慧。
  7. 7. A cornerstone of the semantic web is its use of newer graph-based approaches and technologies – such as the RDF and SPARQL W3C initiatives.
  8. 8. For most types of data storage, there is the concept of some elements of data (whether they be for example data nodes or data tables) having more precedence, or importance, over other elements. (image from http://www.linkeddatatools.com/semantic-web-basics)
  9. 9. ● A shift in thinking from publishing data in human readable HTML documents to machine readable documents. ● It provides a way to homogeneously integrate heterogeneous resources, taking all that information published in HTML documents in different places, and allow it all to be treated - and researched - as if it were one database. ● Opening up the web of data to artificial intelligence processes (getting the web to do thinking for us). ● Encouraging businesses to use data already available on the web (e.g. DBpedia from all Wikipedia data, read Taking Advantage of Existing Linked Data ) Semantic Web : Web 3.0
  10. 10. DBpedia
  11. 11. Linked Data in Education Content recommendation Reasoned from OER Linked Dataset and DBPedia dataset
  12. 12. Facebook OGP is a lightweight version of Semantic Web
  13. 13. Semantic Computing (SC) It’s to represent concepts and their relations in an integrated semantic network that loosely mimics the inter-relation of concepts in the human minds. The knowledge is represented by ontologies and can be used to annotate data and infer new knowledge. SC plays a crucial role in dealing with multi-sensory and multi-model observations, leading to integration of data from diverse sources. SC has a rich history of 15 years, resulting in various annotation standards for a variety of data. The annotated data is used for interpretation by cognitive & perceptual computing.
  14. 14. Semantic Search Semantic search is to improve search results by focusing on user intent and how the search relates to other information in a wider sense, or its contextual relevance -- what a user really means. The Knowledge Graph (launched May, 2012) is Google’s database of information. The information is gained by crawling the web. Google indexes and organizes this information (known as graphing), rendering it useful to queries and commands. Google becomes more of a "knowledge engine" rather than the traditional "information engine". (Forbe, Nov. 2015) Hummingbird (launched Sep., 2013) was essentially an entirely revamped version of Google’s search algorithm. BTW, Customizing Your (company’s) Knowledge Graph
  15. 15. http://searchengineland.com/google-launches-knowledge-graph-121585
  16. 16. Google Knowledge Graph API (to replace Freebase API) The Knowledge Graph Search API (launched Dec. 2015) lets you find entities in the Google Knowledge Graph. The API uses standard schema.org types and is compliant with the JSON-LD specification. Some examples of how you can use the Knowledge Graph Search API include getting a ranked list of the most notable entities that match certain criteria, annotating / organizing content using the Knowledge Graph entities. The Knowledge Graph has millions of entries that describe real-world entities like people, places, and things. These entities form the nodes of the graph. The following are some of the types of entities found in the Knowledge Graph: Book, BookSeries, EducationalOrganization, Event, GovernmentOrganization, LocalBusiness …. etc.
  17. 17. Learner Learning DesignerData Analyst ● Interoperability ● Analytics (algorithms, machine learning API) ● Recommender (context matching, adaptive/ZPD) ● Learning theories ● Psychology ● Design (experience design, UI) ● Subject Matter Expertise *Engagement *Visualization as cognitive agent *Navigator (recommender) *Context !!! inform iterate co-design integrate *Community & social cues *Personalized assistance Gamified layer on data from across platforms Big Data [Data-Driven Learning]
  18. 18. Layer of Data Management
  19. 19. Methodology of Leveraging Big Data It’s been used in... Lean Startup Prototyping Marketing Analytics Business Intelligence Rapid Cycle Tech Evaluations(DOE) Data-Driven Learning Design Data is communication ! (with human’s intelligence)
  20. 20. More: results, goals, history, learner profile / preferences / habits / attributes, device ...
  21. 21. From: http://www.slideshare.net/phish108/ar-discovery-the-challenges-53902694 Sensors Actuators
  22. 22. Learning Planning Activity/Agent Profile API IRS, Quiz service Integration of Workflow and Data flow *Adaptive design *Branches/options Videos or MOOC platform Mobile Apps IoT Wearable AR VR ... Real behavior data sent to Game/ Gamification/ 3rd platforms for rewards
  23. 23. Amazon --- “Anyone who doesn’t do this will be fired. “ Amazon.com is one of the best examples of a programmable enterprise. The company evolved from an online bookseller to a leader in cloud computing and infrastructure-as-a-service in large part because of a mandate set forth by its CEO Jeff Bezos in 2002. He proclaimed that all services within the company must be built in a way that they could be exposed to one another to enable simple communications. In addition, all of these so-called service interfaces must be planned and designed to enable exposure to outside developers. Bezos couldn’t foresee which of these services would end up being externalized. But the move transformed Amazon internally and led to some products that went far beyond online bookselling: Amazon’s Elastic Compute Cloud and its relational database services, among others. Read about the story rant by an ex-Amazon-now-Google-employee. Software is eating the world (Marc Andreessen, 2011), APIs eat software.
  24. 24. Clients can listen for statements being pushed to them from the LRS. Webhooks are a way to register client applications that are interested in certain sets of statements. Every webhook that is registered contains the client endpoint as well as filters that dictate what kind of statements the client wants the LRS to send. A WebHook is an HTTP callback: a simple event-notification via HTTP POST. A web application implementing WebHooks will POST a message to a URL endpoint registered when certain things happen. (www.webhooks.org) Webhooks
  25. 25. Images from Hong Ding Edu. Tech. Embedded VisCa Dashboard for teachers or learners
  26. 26. Case Study 课中出席、上课反应、形成性评量结果、回家作业与複习学习历程记录 => 学生个别状况分类 (能力、态度、兴趣..., 个体 vs 群体) 学习资源 & 策略 matching 推荐内容/策略 to 学生 & 老师 ● 网路免费资源 ● 老师 / 学生分享 资源 ● Discovery from metadata / paradata ● 精选付费内容/ 服务推荐 ● 学习夥伴 ● 家长协助 ● 设定提醒 ● 重複複习练习 ● 偏好内容或活 动型态 协助自主学习与群体学习 资讯汇整方便设计教案、掌握学生
  27. 27. XAPI data Whenever K fails practice A in Hong Ding, VisCa will notify 1Know Assessment and practice service Light Learning Management System: 1Know 1Know pushes a helpful video or resource link to K This is K XAPI data Whenever K finishes watching video B, VisCa will notify Hong Ding Hong Ding pushes an appropriate practice set to K Feedback Request Interact .. Seamless Partnership Automate differentiated learning paths, which can be designed by instructors or adapted by algorithms. You know better about your learners !
  28. 28. Monetize Your Data and Add Values (intelligence) ! ● Let’s collaborate for consistency in: ○ Competency standards ○ User management data models ○ Content management model & metadata ○ Behavior events - xAPI statements recipes ● API call charge model (query, statistics, document of learner profile…) ● Security ○ Technology ○ Regulation and management ● By collective decisions of CoP participants
  29. 29. 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/ ADL resources list http://adlnet.gov/adl-research/performance-tracking-analysis/experience- api/ Community/Resource Links

    Seja o primeiro a comentar

    Entre para ver os comentários

Topics XAPI Vocabulary spec. From ADL Linked Data / Semantic web. / Web 3.0 Linked Data in education and content recommender Semantic search and Google Knowledge Graph APIs eat software (connect with partners and services) How should we exploit data and build intelligence layer? Case Study (Hong Ding Educational Technology) Monetize your data and add value (intelligence)

Vistos

Vistos totais

741

No Slideshare

0

De incorporações

0

Número de incorporações

106

Ações

Baixados

4

Compartilhados

0

Comentários

0

Curtir

0

×