1、Information technology for learning, education and training Learning analytics interoperability Part 1: Reference model Technologies pour lducation, la formation et lapprentissage Interoprabilit de lanalytique de lapprentissage Partie 1: Modle de rfrence TECHNICAL REPORT ISO/IEC TR 20748-1 First edi
2、tion 2016-12-15 Reference number ISO/IEC TR 20748-1:2016(E) ISO/IEC 2016 ii ISO/IEC 2016 All rights reserved COPYRIGHT PROTECTED DOCUMENT ISO/IEC 2016, Published in Switzerland All rights reserved. Unless otherwise specified, no part of this publication may be reproduced or utilized otherwise in any
3、 form or by any means, electronic or mechanical, including photocopying, or posting on the internet or an intranet, without prior written permission. Permission can be requested from either ISO at the address below or ISOs member body in the country of the requester. ISO copyright office Ch. de Blan
4、donnet 8 CP 401 CH-1214 Vernier, Geneva, Switzerland Tel. +41 22 749 01 11 Fax +41 22 749 09 47 copyrightiso.org www.iso.org ISO/IEC TR 20748-1:2016(E) ISO/IEC TR 20748-1:2016(E)Foreword iv Introduction v 1 Scope . 1 2 Normative references 1 3 T erms and definitions . 1 4 Abbreviated terms 3 5 Use c
5、ases and practices . 3 5.1 General . 3 5.2 Learning analytics 4 5.3 Assessment . 4 5.4 Data flow and data exchange 4 5.5 Accessibility preferences 5 6 Reference model for learning analytics interoperability 5 6.1 General . 5 6.2 Workflow for general data analytics 5 6.3 Reference architecture derive
6、d from workflow and use cases . 6 6.3.1 General 6 6.3.2 Learning and teaching activity process 7 6.3.3 Data collection process. 8 6.3.4 Data storing and processing process 9 6.3.5 Analysing process 10 6.3.6 Visualization process 11 6.3.7 Feedback process .12 Annex A (informative) Use cases and pract
7、ices 15 Bibliography .31 ISO/IEC 2016 All rights reserved iii Contents Page ISO/IEC TR 20748-1:2016(E) Foreword ISO (the International Organization for Standardization) and IEC (the International Electrotechnical Commission) form the specialized system for worldwide standardization. National bodies
8、that are members of ISO or IEC participate in the development of International Standards through technical committees established by the respective organization to deal with particular fields of technical activity. ISO and IEC technical committees collaborate in fields of mutual interest. Other inte
9、rnational organizations, governmental and non-governmental, in liaison with ISO and IEC, also take part in the work. In the field of information technology, ISO and IEC have established a joint technical committee, ISO/IEC JTC 1. The procedures used to develop this document and those intended for it
10、s further maintenance are described in the ISO/IEC Directives, Part 1. In particular the different approval criteria needed for the different types of document should be noted. This document was drafted in accordance with the editorial rules of the ISO/IEC Directives, Part 2 (see www.iso.org/directi
11、ves). Attention is drawn to the possibility that some of the elements of this document may be the subject of patent rights. ISO and IEC shall not be held responsible for identifying any or all such patent rights. Details of any patent rights identified during the development of the document will be
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13、 related to conformit y assessment, as well as information about ISOs adherence to the World Trade Organization (WTO) principles in the Technical Barriers to Trade (TBT) see the following URL: www.iso.org/iso/foreword.html. The committee responsible for this document is ISO/IEC JTC 1, Information te
14、chnology, SC 36, Information technology for learning, education and training. A list of all parts in the ISO/IEC 20748 series, published under the general title Information technology for learning, education and training Learning analytics interoperability, can be found on the ISO website.iv ISO/IEC
15、 2016 All rights reserved ISO/IEC TR 20748-1:2016(E) Introduction The increasing amount of data being generated from learning environments provides new opportunities to support learning, education and training (LET) in a number of new ways through learning analytics. Learning analytics is a composit
16、e concept built around the use of diverse sub-technologies, workflows and practices and applied to a wide range of different purposes. For instance, learning analytics is being used to collect, explore and analyse diverse types and interrelationships of data, such as: learner interaction data relate
17、d to usage of digital resources; teaching and learning activity logs; learning outcomes and structured data about programmes; curriculum and associated competencies. Learning analytics is an emerging technology addressing a diverse group of stakeholders and covering a wide range of applications. Lea
18、rning analytics raises new interoperability challenges related to data sharing; privacy, trust and control of data; quality of service, etc. Through use case collection in the ad- hoc group on learning analytics interoperability, established under JTC1/SC36 in 2014, the following issues were identif
19、ied and captured as general requirements for learning analytics applications: For the learner: tracking learning activities and progression; tracking emotion, motivation and learning-readiness; early detection of learners personal needs and preferences; improved feedback from analysing activities an
20、d assessments; early detection of learner non-performance (mobilizing remediation); personalized learning path and/or resources (recommendation). For the teacher: tracking learners/group activities and progression; adaptive teacher response to observed learners needs and behaviour; early detection o
21、f learner disengagement (mobilizing relevant support actions); increasing the range of activities that can be used for assessing performance; visualization of learning outcomes and activities for individuals and groups; providing evidence to help teacher improve the design of the learning experience
22、 and resources. For the institution: tracking class/group activities and results; quality assurance monitoring; providing evidence to support the design of the learning environment; providing evidence to support improved retention strategies; support for course planning. In addition, learning analyt
23、ics practice can build upon prior work in LET standardization and innovation but there are several factors that require special attention. These factors include: requirements arising from the analytical process; data items required to drive operational LET systems are not always the same as desired
24、for learning analytics; ISO/IEC 2016 All rights reserved v ISO/IEC TR 20748-1:2016(E) volume, velocity and variety of the data collected for analytics indicate different IT architectures, which imply different interoperability requirements; use of learner data for analytics introduces a range of eth
25、ical and other socio-cultural issues beyond those which arise from exchanging data between operational systems. Therefore, this document gives a conceptual description of the behaviour of components related to learning analytics interoperability. In particular, this document specifies terms as well
26、as proposes a reference model for the learning analytics process and interoperability.vi ISO/IEC 2016 All rights reserved TECHNICAL REPORT ISO/IEC TR 20748-1:2016(E) Information technology for learning, education and training Learning analytics interoperability Part 1: Reference model 1 Scope This d
27、ocument specifies a reference model that identifies the diverse IT system requirements of learning analytics interoperability. The reference model identifies relevant terminology, user requirements, workflow and a reference architecture for learning analytics. 2 Normative references The following do
28、cuments are referred to in the text in such a way that some or all of their content constitutes requirements of this document. For dated references, only the edition cited applies. For undated references, the latest edition of the referenced document (including any amendments) applies. There are no
29、normative references in this document. 3 T erms a nd definiti ons For the purposes of this document, the following terms and definitions apply. ISO and IEC maintain terminological databases for use in standardization at the following addresses: IEC Electropedia: available at http:/ /www.electropedia
30、.org/ ISO Online browsing platform: available at http:/ /www.iso.org/obp 3.1 accessibility usability of a product, service, environment or facility by individuals with the widest range of capabilities Note 1 to entry: Note 1 to entry: Although “accessibility” typically addresses users who have a dis
31、ability, the concept is not limited to disability issues. SOURCE: ISO/IEC 24751-1:2008, 2.2 3.2 assessment means of measuring or evaluating learner understanding or competency 3.3 dashboard user interface based on predetermined reports, indicators and data fields, upon which the end user can apply f
32、ilters and graphical display methods to answer predetermined business questions and which is suited to regular use with minimal training SOURCE: ISO/TS 29585:2010, 3.3 ISO/IEC 2016 All rights reserved 1 ISO/IEC TR 20748-1:2016(E) 3.4 data analysis systematic investigation of the data and their flow
33、in a real or planned system SOURCE: ISO/IEC 2382:2015, 2122686 3.5 data collection process of bringing data together from one or more points for use in a computer EXAMPLE EXAMPLE To collect transactions generated at branch offices by a data network for use at a computer centre. SOURCE: ISO/IEC 2382:
34、2015, 2122166 3.6 data exchange storing, accessing, transferring, and archiving of data SOURCE: ISO 10303-1:1994, 3.2.15 3.7 d a t a f l o w movement of data through the active parts of a data processing system in the course of the performance of specific work SOURCE: ISO/IEC 2382:2015, 2121825 3.8
35、data format arrangement of data in a file or stream SOURCE: ISO/IEEE 11073-10201:2004, 3.14 3.9 data source functional unit that provides data for transmission SOURCE: ISO/IEC 2382:2015, 2124348 3.10 individual human being, i.e. a natural person, who acts as a distinct indivisible entity or is consi
36、dered as such SOURCE: ISO/IEC 24751-1:2008, 3.21 3.11 learning analytics measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs 3.12 learning platform integrated set of (
37、online) services that provide learner, teacher and/or others involved in learning, education and training with information, tools and resources to support and enhance educational delivery and management2 ISO/IEC 2016 All rights reserved ISO/IEC TR 20748-1:2016(E) 3.13 learning outcome what a person
38、is expected to know, understand or be able to do at the end of a training programme, course or module SOURCE: ISO/IEC 17027:2014, 2.57 3.14 usability extent to which a product can be used by specified users to achieve specified goals, with effectiveness, efficiency and satisfaction, in a specified c
39、ontext of use SOURCE: ISO 9241-11:1998, 3.1 3.15 wor k f l ow depiction of the actual sequence of the operations or actions taken in a process Note 1 to entry: Note 1 to entry: A workflow reflects the successive decisions and activities in the performance of a process. SOURCE: ISO 18308:2011, 3.52 4
40、 Abbreviated terms ADL advanced distributed learning AFA access-for-all API application programming interface ICT information and communication technologies LET learning, education and training LMS learning management system LOD linked and open data PLE personal learning environment VLE virtual lear
41、ning environment xAPI experience API 5 Use cases and practices 5.1 General Use cases were collected from national bodies and liaison organizations of ISO/IEC JTC1/SC36. The use cases illustrate key functionalities related to learning analytics by focusing on particular requirements that stakeholders
42、 may have and then outlining how such requirements can be reflected in workflows for learning analytics. A total of fifteen use cases were received in 2014. Use cases considered four main areas: learning analytics; assessments; ISO/IEC 2016 All rights reserved 3 ISO/IEC TR 20748-1:2016(E) data flow
43、and data exchange; accessibility preferences. The summary of the use cases is presented in Clause 5. The complete list of use cases is available in Annex A. 5.2 Learning analytics A stakeholder has previous experience with analytics dashboards available in online learning platforms (known as learnin
44、g management systems (LMS) or virtual learning environments (VLE). In general, data logs were not in a format that non-technical users could interpret, but these are now rendered (displayed) via a range of graphs, tables and other visualization forms, and custom reports designed for learners, educat
45、ors, administrators and data analysts. Learners may get basic analytics from dashboards such as progress relative to the cohort average marks or engagement ratio. Learning analytics are delivered with more advanced features, namely predictive analytics. Predictive analytics focuses on the pattern of
46、 learners static data (e.g. demographics; past attainment) and dynamic data (e.g. pattern of online logins; quantity of discussion posts). Once a students trajectory is drawn (e.g. “at risk”; “high achiever”; “social learner”), timely interventions can be planned (e.g. offering extra social and acad
47、emic support; presenting more challenging tasks). Learning analytics are used to enhance the personalized learning environment (PLE). Based on learning analytics output, the PLE can recommend learning pathways combined with learning content or resources. This service model enables fine-grained feedb
48、ack (e.g. which concepts have been grasped and at what level), and adaptive presentation of content (e.g. not showing material that depends on the mastery of concepts that the learner is yet to acquire). Other types of learning analytics are social network analytics and discourse analytics. Social n
49、etwork analysis makes visible the structures and dynamics of interpersonal networks to understand how people develop and maintain these relations (in the classroom or learning community). Discourse analytics requires the use of sophisticated technology to assess the quality of text in order to scaffold the higher-order thinking and writing skills that we seek to instil to learners. 5.3 Assessment One of the adv
