Consider this scenario: A teacher needs to quiz her students on the concepts included in a specific lesson and wants to provide additional materials to those students who did not master the concepts. Given the multitude of available resources and limited time teachers have, how will she quickly find the items and resources needed to meet her students’ needs? The answer is metadata.
If you Google the term metadata, you often find a definition that reads something like, “metadata is data about data.” However, in the context of education, metadata can more aptly be defined as: tags used to describe educational assets. It can be split into three camps: descriptive, administrative and structural.
- Descriptive metadata can describe a learning asset or resource related to education — including learning standards, lessons, assessment items, books, etc. — for purposes such as identification, search and discovery. Descriptive metadata can be thought of as a keyword or tag on an asset that makes it easier to find. Examples include subject, grade level, and related skills and concepts.
- Administrative metadata is used to manage a learning asset. Examples of this type of metadata include status, disposition, rights and licensing.
- Structural metadata describes how data is organized or formatted and is often governed by a widely-adopted standard that ensures the data is accurately represented when exchanged and presented. Structural metadata enables content to be machine readable.
Taxonomy is the science of classification. In the world of education, taxonomies are a type of controlled vocabulary, typically curated in hierarchical form, that are used to further enrich and connect descriptive metadata. In general, controlled vocabularies can range from simple terms like subject and grade to more robust, comprehensive taxonomies that catalog things like concepts and topics. The application of these terms within the metadata structure is used to describe educational assets. A successful network of metadata and taxonomies are created when they are developed in parallel with focused purpose.
How does metadata enable us to more easily discover and use educational content? Let’s consider a few scenarios. First, the teacher we introduced in the first paragraph:
Assessment & Corrective Instruction: A teacher needs to quiz her students on the concepts included in a specific lesson and wants to provide additional materials to those students who did not master the concepts.
Imagine that instructional materials, an assessment item bank and supplemental materials could all be tagged with the same conceptual taxonomy. Machine learning algorithms can use this information to connect and recommend related content.
Learning Standards Alignment: A content developer or provider needs to ensure that the lessons included in her curriculum package cover all required learning standards for a given state, as well as identify where instructional content may align to other states’ learning standards, enabling the expansion of the curriculum package to other markets.
When content is tagged and enriched with descriptive metadata, taxonomies can provide an efficient path to ensuring that the content is properly aligned to learning standards. Structured metadata can also be used to unpack standards, to ensure comprehensive content coverage for a single standard or collection of standards covered in a curriculum package. Applying consistent metadata across multiple states enables us to identify common skills. As a result, it is easier to modularize instructional content and leverage it for use in multiple states while ensuring tight, accurate standard alignment.
Content Search and Discovery: A product manager for an education application needs to be able to provide users with an intuitive browse and search experience for learning standards and related content.
Application providers can optimize the content search experience for educators by capturing, tagging and delivering learning standards and content in a consistent and machine-readable metadata format. This enables educators to find the content necessary to help their students achieve standard mastery.
As the amount of data and instructional assets continues to grow in education and impact the classroom, tagging these resources with descriptive learning metadata helps teachers find relevant, standards-aligned content to use in their classrooms.