Demystifying Learning Technology Standards, Part II: Acceptance and Implementation
In our March issue, Part I of this two-part article on learning technology
standards introduced the development and evolution of standards and presented
the key organizations promoting these standards. Here, Part II provides a
glimpse into acceptance and implementation, illustrated by SCORM specifications
as they may be applied to courseware development.
The rise of interest in standards that apply to learning technologies is only
the beginning. Proposed standards are just starting to have their initial impact
on institutions and on individual teaching faculty. In the future, releases of
SCORM specifications and IMS metadata standards may be somewhat more generally
familiar to faculty developers, but it is probably safe to say that at present
most have at best a vague notion of their existence and utility.
The hope is
that widespread acceptance of learning technology standards will foster shared
resources among institutions and provide new efficiencies for program
administrators. Standards will play a larger role in institutional planning and
program development discussions in the not-so-distant future. In the meantime,
in order to illustrate the implementation of the proposed standards, it may be
useful to describe a few points about how the proposed standards can be applied
by courseware developers.
It is important to reflect on the process of
evolution that standards take. This was described briefly in Part I of this
article (Syllabus, March 2002). Most formal standards for learning technology,
accepted by the IEEE and ISO, are likely to be years away. At present,
developers may act on proposed standards and those adopted into releases such as
The intent of ADL Co-Labs in the development of standards is to make SCORM an
integrative model that relies on and extends specifications from other groups.
ADL participates with other organizations, such as AICC and IMS in the
development of specifications, and when the specifications become stable, it
incorporates them into a SCORM release. The expectation is that the
implementation of SCORM specifications can help learning technology—in our
present example, courseware—to become reusable, interoperable, stable, and
For an instructional designer or online course developer to
comply with SCORM specifications, there are five essential elements to
implement: the course structure, multimedia assets, sharable content objects
(SCOs), content aggregation, and content packaging. The proper implementation of
all of these elements in courseware development constitutes basic conformance
with SCORM 1.2.
With the implementation of the first element, course
structure, it is essential to define content hierarchy, similar to writing a
conventional table of contents. Multimedia assets are identified within the
course structure, along with SCOs. Context-specific metadata (data about data)
is needed to describe the context in which each of these course elements is
presented. Information about sequencing and navigation within the course content
resources of a dynamically delivered course is necessary and will describe how a
given sequence meets specific learning objectives. Figure 1 outlines a generic
course structure as an example.
For the purposes of our example of courseware
development, metadata can be defined as data about the course content data. The
asset, SCO, and content aggregation information is required to have metadata to
facilitate content discovery and maintenance. Metadata standards are developed
through collaborative efforts. The IEEE LTSC P1484 committee contributed the
Learning Object Metadata (LOM), and IMS Global Learning Inc. provided IMS
Learning Resources Metadata XML binding specifications. SCORM 1.2 has adopted
the two to provide a schema for content tagging.
The current release, SCORM
1.2, employs a new content aggregation model. As described in the SCORM 1.2
content aggregation model, "The content structure is intended to represent a
wide variety of content aggregation approaches. The content structure can
represent a content aggregation ranging from very, very small learning
resources—as simple as a few lines of Hypertext Markup Language (HTML) or a
short media clip—to highly interactive learning resources that are tracked by a
[learning management system] LMS. The content structure is neutral about the
complexity of content, the number of hierarchical levels of a particular course
(i.e., taxonomy), and the instructional methodology employed to design a
The SCORM 1.2 release has adopted the IMS content packaging
specifications. The IMS content packaging specifications utilize a specific data
structure for the interoperability of the Internet-based content with various
authoring environments. The proposed model has two major components. The first
is the definition of the course structure in a manifest file coded in XML, and
the second is the provision of specific file references to the various course
structure elements included in the manifest (see Figure 2).
With each new
release, SCORM specifications will offer increasing benefits. An example of this
progression is that SCORM 1.2 allows SCOs anywhere in the content hierarchy
structure. The previous release of SCORM allowed SCOs only in the leaf nodes.
The significance is, of course, that the ability to move the sharable content
objects further up in the hierarchy means that more of the course will be
sharable through any given SCO.
Toward Learning Style-Based Content Sequencing
The course content can be sequenced with a wide variety of content
aggregation approaches. But at present, learning technology standards do not
provide specifications to handle the pedagogical learning style-based content
sequencing. A simpler sequencing model is being adopted by SCORM and proposed by
The pedagogical framework proposed in Learning Cube (Syllabus December
2001 and January 2002) could be used to provide content sequencing based on
learning styles, i.e., apprenticeship, incidental, inductive, deductive, and
discovery, as well as to provide adaptive use of assets, SCOs, and content
aggregation in terms of text, graphics, audio, video, animation, and simulation
content resources. The interactivity and the synchronous communication objects
such as discussion boards and chat could also be incorporated as SCOs.
author has proposed a best practice extension to the content packaging model
that includes a learning style taxonomy-based content sequencing scheme. The
proposal has been provided to ADL Co-Labs for future consideration. The SCORM
1.2 specifications have advanced the purpose of resource sharing. As standards
continue to develop, additional attention to learning styles could provide
extensive new benefits to learners.
Nishikant Sonwalkar, Ph.D., is the
principal educational architect at the Educational Media Creation Center at the
Massachusetts Institute of Technology and serves as the pedagogical adviser for
Web-based educational experiments and projects. email@example.com
Categories of Metadata in SCORM 1.2
The General category groups the general information that describes the
resource as a whole.
The Lifecycle category groups the features related
to the history and current state of this resource and those who have
affected this resource during its evolution.
The Meta-metadata category
groups information about the metadata record itself (rather than the
resource that the record describes).
The Technical category groups the
technical requirements and characteristics of the resource.
Educational category groups the educational and pedagogical
characteristics of the resource.
The Rights category groups the
intellectual property rights and conditions of use for the
The Relation category groups features that define the
relationship between this resource and other targeted resources.
Annotation category provides comments on the educational use of the
resource and information on when and by whom the comments were
The Classification category describes where this resource
falls within a particular classification system.
Source: SCORM 1.2 Content Aggregation Model
Special thanks to:
Dan Rehak (Carnegie
Mellon University), Jeff Merriman, Vijay Kumar (MIT), Bill McDonald
(AICC), Judy Brown (Academic ADL Co-Lab), and Philip Dodds (DOD ADL
Co-Labs) for useful communication and permission to use SCORM figures and