The constantly evolving domain of adaptive training warrants an examination of standards for adaptive instructional systems (AIS), specifically in the area of metadata tagging as it relates to the methods to curate, apply, and evaluate content in the authoring process. Metadata tags provide information not only to authors of AIS's, but are key in driving learning object searches. Metadata tagging represents key micro-communications between systems and search engines, and its absence limits the ability to meaningfully consume and exchange information with learning management systems. In the effort to standardize tools and methods for authoring content for generalizable AIS's, this paper will advocate for establishing a standard on metadata tagging methodology for learning objects that would include pedagogical identifier codes. The establishment of this standard would not only ease efforts in the development and implementation of learning designs for AIS's, but would promote efforts to expand the aims of AIS's to push beyond domain specific content mastery tasks to support broader cross-disciplinary discriminate intelligence in learners.
The constantly evolving domain of adaptive training warrants an examination of
standards for adaptive tutoring systems, specifically in the area of metadata tagging.
Metadata tags provide information not only to authors of tutoring system, but are key
in driving learning object searches. Metadata tagging represents key micro-
communications between systems and search engines, and without it, limits the ability to
meaningfully consume and exchange information with learning management systems. As
such, in the effort to standardize tools and methods for authoring content for adaptive
instructional tutoring systems (AIS’s), this paper will limit its scope to reviewing the
gap that exists in the report regarding the metadata management requirements and
existing solutions for European Union (EU) Institutions and Member States [
In 2014, the Interoperability Solutions for European Public Administrations (ISA)
Programme reported on their commissioned study aimed at recommending coordination
of data standards, governance, and management within and between different
organizations at both the national and EU level to promote greater interoperability between
information systems. The results of this study identify the set of high-level processes
for managing the lifecycle of metadata, propose a governance structure for data
standards including roles and responsibilities, as well as identify tools and best practices for
managing and consuming data standards [
To begin with, the authors of this report identify the need for standardizing primary
data models and reference data, and distinguish the relevant obstacles for addressing
both. Data models -- as a collection of entities, their properties and relationship to each
other -- represent conceptual or real-world elements. When changes are intended for
data models, what is needed is a strongly managed implementation plan aligned with a
software upgrade cycle [
Within this context, then, the gap in the ISA report as it relates to metadata tagging
standards can be found in how the ISA addressed and proposed standards for the
different phases of the lifecycle of metadata [
The IEEE Learning Object Metadata (LOM) is a metadata model consisting of
conceptual data schema designed in a way to allow for extensions to the established
schema, such as new vocabularies or taxonomies [
Within the educational category, there are eleven elements with accompanying
descriptors: interactivity type; learning resource type; interactivity level; semantic
density; intended end user role; context; typical age range; difficulty; typical learning time;
description; and language [
The argument to design, create, and standardize pedagogical tagging rests in the issue that content and learning objects in and of themselves do not necessarily lead to greater learning. Rather, content is merely the vessel through which learning occurs. Tagging content absent of a contextualization of how the content can support learning limits its potential applicability across a range of domains, and does not help AIS designers and authors to find content that best supports a learning objective.
What is needed in addition to tagging content and learning objects is the learning objective: identifying how the content supports critical thinking and discriminate intelligence. Discriminate intelligence here means the ability to distinguish between not just right and wrong answers, but between good-better-best answers, and generating unique solutions to ill-defined problem sets. Therefore, prescribing a standard for metadata tagging that identifies what skills learning objects support would not only contribute to broad educational aims across a range of domains, but it would allow for learning objects to be reused and referenced across domains that might normally be filtered out because of limiting tagging identifiers.
The importance of creating high quality consistent metadata for learning resources
has been an area of concern in the e-learning area since the inception of the LOM as a
standard, as is the recognized need for better use of pedagogies to enhance
instruction/learning [
Some suggested approaches to tagging has included using a collaborative approach
for tagging to overcome problems associated with establishing a formal ontology
creation [
As has been identified by other researchers [
Currently, the IEEE LOM description for the Interactivity Type element within the
Educational Category is described is as follows: “active: active learning is supported by
content that directly induces productive action by the learner; expositive: expositive
learning occurs when the learner’s job mainly consists of absorbing the content
exposed to them; mixed: a blend of active and expositive interactivity types” [
The advocacy for using pedagogical identifiers is not a new idea. Hadji, Choi, and
Jemni’s [
Essentially, the Hadji, Choi and Jemni model [
In 2001, however, Bloom’s Taxonomy [
Bloom’s Revised Taxonomy of 2001 [
Today in face-to-face classrooms, Bloom’s Revised Taxonomy continues to be used
as a tool to balance assessments with assignments for the purposes of insuring all orders
of thinking are addressed in students’ learning [
The importance of Bloom’s Revised Taxonomy discussion lays in the fact that to propose an effective design for the standardizing metadata tagging for AIS’s, the inclusion of pedagogical identifiers should rest both on widely accepted industry practices and be useful for the aims and purposes of designing and reusing AIS learning objects. Adopting a standard that would encourage AIS designers and authors to use metadata tagging that contextualizes content within Bloom’s taxonomical framework could aid in more effective selection of content to support learning aims, as well as broaden the scope of possible learning objects that can be incorporated in a learning course that might otherwise be overlooked if tagged ineffectively and limited by mere content identifiers.
In sum, this proposed standard is in line with the ISA efforts to maintain a standard
for structural metadata management for different phases of the lifecycle of metadata,
in particular by addressing the ISA’s gap of addressing designing and creating of
metadata tagging for learning objects [
specific content, but rather think more purposefully about designing environments support both content mastery and discriminate intelligence.
In all, the value of establishing a metadata tagging standard for AIS’s that includes pedagogical identifiers based on Bloom’s Revised Taxonomy is anchored in the fact that content, in and of itself, does not promote greater learning nor support the development of discriminate intelligence. Rather, it is the way in which a learning environment is designed and implemented, the pedagogy used, and the outcomes one seeks to achieve through content that yields robust learning outcomes and improved discriminate intelligence.
Ultimately, the significance of establishing a standard for AIS’s with Bloom’s Revised Taxonomy pedagogical identifiers allows for a more manageable and reusable method of employing a metadata tagging tool for authoring adaptive instructional courses, particularly across a range of domains whose learning objectives and desired outcomes are not limited by a narrowly constructed understanding of what learning activities look like and do. Future work in this area should include how the proposed meta-data standard would be applied, the types of pedagogical information that would be included in this standard, how this standard would be mapped in relevant systems, a more in-depth analysis and comparison of Bloom’s Revised Taxonomy versus other established learning taxonomies, as well as determining whether other elements of the IEEE LOM metadata standard warrant similar design revisions for AIS standards.
This research was sponsored by the US Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-17-2-0152. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.