ADAPT2

Overview

ADAPT² Architecture

ADAPT² (read adapt-square) - Advanced Distributed Architecture for Personalized Teaching and Training - is a framework for research on personalized and adaptive learning, which brings together researchers exploring novel types of interactive learning content with researchers exploring various kinds of personalization approaches. As a part of its mission, ADAPT² currently provides personalized learning systems to support large classes for several computer science education topics such as Java, Python, and SQL. It has been used in many universities on four continents.

ADAPT² consists of the following principal component types.

Portals, such as Knowledge Tree, which provide a single sign-on point for users of personalized learning systems
User-modeling servers such asCUMULATE, which maintain knowledge models of individual students
Content Servers, which provide access to various kinds of interactive learning objects
Adaptive Shells, which offer various kinds of personalized access to learning objects
PERSEUS - personalization service engine

To provide personalized service to its end users, these components communicate with each other using several standard communication protocols. Two main groups of protocols are Content Invocation protocols, which enable a portal or an adaptive shell to call interactive learning objects residing on various content servers, and [[User Modeling protocols|CUMULATE protocol] for reporting user activities and requesting current state of their knowledge from user-modeling servers.

A typical personalized learning system supported by ADAPT² works in the following way:

Students log in through a portal, such as Knowledge Tree, which determines which courses (learning groups) they can access and choose one of these courses.
A selected course provides access to one or more adaptive shells, such as MasteryGrids. Each of these shells provides personalized access to multiple kinds of learning content made accessible for the course. The selected course also determines which student modeling server will be used for personalization.
Using the current state of the user models, which the adaptive shell requests from the user-modeling server, the shell helps each student find and launch an interactive learning object that is most appropriate for the current state of their knowledge.
While the students work with the selected interactive learning object, all their activities are reported back to the user-modeling server, which uses these activities to update the state of individual learners' knowledge.
After completing their work with each learning object, the students return to the adaptive shell, which now uses the updated state of the user model to assist the learners with selecting the next knowledge- and context-appropriate learning object.

The personalized learning process supported by ADAPT² is quite typical for personalized learning.

Knowledge Tree

Knowledge Tree is a link aggregating portal. It presents content structured according to the folder-document paradigm. Knowledge Tree provides authentication and authorization and implements a simplified form of access control. It supports collaborative authoring and social annotation. (more)

CUMULATE

CUMULATE is a central user modeling server responsible for collecting evidence of user activity and for generating user models, i.e., assertions about the knowledge and mastery of individual users. Personalization components of the architecture, such as personalized shells and personalized learning content, could get access to the user models (using CUMULATE protocols) to offer personalized access and other personalized services to the end users. ==> (more on CUMULATE)

Adaptive Shells

ADAPT2 supports multiple types of adaptive shells (aka value-adding services) which are the key components for providing adaptation and personalization. Adaptive shells stand between a portal and learning objects coming from multiple content servers. In contrast to the portal, which is not personalized, adaptive shells can provide personalized access to learning objects. The ability to insert various adaptive shells between the portal and the learning content makes possible to explore various personalization approaches. Examples of adaptive shells explored by our lab in the past include:

NavEx for concept-based personalization
QuizGuide and [JavaGUide]] for topic-based personalization
Knowledge Sea II for social navigation support
Progressor shells for a single-content social comparison
Progressor+ shell for multi-type social comparison

Since 2015 most of our research uses MasteryGrids shell. MasteryGrids offers a flexible and customizable interface for delivering and exploring personalized content access. It combines knowledge-based personalization explored by NavEx and QuizGuide with social navigation and comparison ideas explored by Knowledge Sea II, Progressor, and Progressor+.

Content Servers

Content servers provide learning objects for students to interact with. Content servers that natively work with ADAPT² include several systems developed by PAWS lab: WebEx, QuizPACK, c/jWADEIn, SQLKnoT, QuizJET, PCEX. ADAPT2 can also use learning objects developed by many other research teams. There are currently two ways to make interactive learning content usable in ADAPT2.

For unrestricted use, learning content server has to implement with ADAPT² content invocation protocol and CUMULATE knowledge reporting protocols. Examples of of content servers that implement these protocols are SQL Tutor (University of Canterbury, New Zealand), PCRS (University of Toronto), and ACOS server (Aalto University).

For the use in MasteryGrids interface only, a learning content server has to implement LTI protocol for launching learning activities and reporting learner progress. Examples of LTI-compatible learning content that are currently used in courses supported by ADAPT² are CodeWorkout (Virginia Tech) and DBQA (University of St. Thomas).

PERSEUS

PERSEUS is a Personalization Service Engine. It provides adaptive support for non-personalized (educational) hypermedia systems by abstracting content presentation/aggregation from user modeling. PERSEUS protocols are based on RDF and RSS 1.0. Although, PERSEUS was initially developed for ADAPT² framework, its data model permits seamless support of any other hypermedia application. Currently PERSEUS supports social navigation, topic-based navigation, concept-based navigation, and adaptive filtering techniques.

Standardization

Data models of ADAPT² components are partially serialized as RDF. For more information refer to ADAPT² RDF Binding.

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