D David Smits

Creating and delivering adaptive courses with AHA

AHA! is an Open Source adaptive hypermedia platform, resulting from 10 years of experience with creating, using and improving on-line adaptive courses and presentations. This paper focuses on some recent additions to AHA! that are especially important for adaptive educational applications, namely stable presentations, adaptive link (icon) annotations and adaptive link destinations. We not only describe the technical aspects of these parts of AHA! but also illustrate their use in educational applications. We describe some fundamental limitations of Web-based adaptive applications, and show how AHA! deals with them in order to provide adaptation to prerequisite relationships in the way one would expect.

Defining Adaptation in a Generic Multi Layer Model: CAM: The GRAPPLE Conceptual Adaptation Model

Authoring of Adaptive Hypermedia is a difficult and time consuming task. Reference models like LAOS and AHAM separate adaptation and content in different layers. Systems like AHA!, offer graphical tools based on these models to allow authors to define adaptation without knowing any adaptation language. The adaptation that can be defined using such tools is still limited. Authoring systems like MOT are more flexible, but usability of adaptation specification is low. This paper proposes a more generic model, CAM, which allows the adaptation to be defined in an arbitrary number of layers, where adaptation is expressed in terms of relationships between concepts. This model allows the creation of more powerful yet easier to use graphical authoring tools.

AHA! Meets AHAM

After many years of hypertext research, the Dexter model was defined [7] to capture the features of most existing hypertext systems in a single, formal reference model. Likewise, the AHAM model [5] (based on Dexter) describes most features that are found in adaptive hypermedia systems (ahs). In the AHA! project funded by the NLnet Foundation we are extending the simple AHA system [4, 6] with the condition-action rules that were introduced in AHAM [8]. This results in a more versatile adaptation engine, with more intuitive and more powerful rules.

GRAPPLE: Learning Management Systems Meet Adaptive Learning Environments

Learning Management Systems (LMSs) are used in many (educational) institutes to manage the learning process. Adaptive Learning Environments (ALEs) offer support for the learning process through adaptive guidance and perhaps also personalized learning material (content). GRAPPLE offers a new infrastructure that brings both together. This is done through single sign-on, a common User Model Framework and an (asynchronous) event bus that coordinates the communication between the other components. Authors can create structured course material and define the adaptation through a graphical interface, and a flexible and very extensible adaptation engine offers almost any type of presentation and adaptation an author might want. This chapter reports on early experience with the GRAPPLE environment, for teaching and for learning.

Authoring and Management Tools for Adaptive Educational Hypermedia Systems: The AHA! Case Study

Creating and maintaining adaptive educational applications is hard work for teachers and developers. In order to help the author perform these tasks the e-learning systems must provide authoring and management tools. In this chapter we describe several useful tools for working with adaptive educational hypermedia systems, using the Adaptive Hypermedia Architecture (AHA!) system. AHA! is a well-known open source general-purpose adaptive hypermedia system. In the current AHA! distribution versions there are some general adaptive author tools as Concept Editor, Graph Editor, and Form Editor, all accessible through the overall Application Management Tool. There is also a specific educational tool: the Test Editor (and the associated Test Engine) and we are now developing some others such as a Course Editor and Mining tool. In this chapter we describe the AHA! system and the functionality of each of these authoring and management tools intended to help teachers and application developers.

AHA! the next generation

AHA! is a simple Web-based adaptation engine that was originally developed to support an on-line course. This paper describes AHA! version 2.0, a new major release that aims to significantly increase the adaptive versatility of AHA! without sacrificing AHA!s simplicity that makes it easy to use. The new features in AHA! are inspired by AHAM [4], a Dexter [6] based reference model for adaptive hypermedia systems.

LAG 2.0: Refining a Reusable Adaptation Language and Improving on Its Authoring

Reusable adaptation specifications for adaptive behaviour has come to the forefront of adaptive research recently, with EU projects such as GRAPPLE1, and PhD research efforts on designing an adaptation language for learning style specification [1]. However, this was not the case five years ago, when an adaptation language for adaptive hypermedia (LAG) was first proposed. This paper describes the general lessons learnt during the last five years in designing, implementing and using an adaptation language, as well as the changes that the language has undergone in order to better fulfil its goal of combining a high level of semantics with simplicity, portability as well as being flexible . Besides discussing these changes based on some sample strategies, this paper also presents a novel authoring environment for the programming-savvy adaptation author, that applies feedback accumulated during various evaluation sessions with the previous set of tools, and its first evaluation with programming experts.

GALE: a generic open source extensible adaptation engine

This paper motivates and describes GALE, the Generic Adaptation Language and Engine that came out of the GRAPPLE EU FP7 project. The main focus of the paper is the extensible nature of GALE. The purpose of this description is to illustrate how a single core adaptation engine can be used for different types of adaptation, applied to different types of information items and documents. We illustrate the adaptive functionality on some examples of hypermedia documents. In April 2012, David Smits defended the worlds first adaptive PhD thesis on this topic. The thesis, available for download and direct adaptive access at http://gale.win.tue.nl/thesis/, shows that a single source of information can serve different audiences and at the same time also allows more freedom of navigation than is possible in any paper or static hypermedia document. The same can be done for course texts, hyperfiction, encyclopedia, museum, or other cultural heritage websites, etc. We explain how to add functionality to GALE if desired, to adapt the systems behavior to whatever the application requires. This stresses our main objective: to provide a technological base for adaptive (hypermedia) system researchers on which they can build extensions for the specific research they have in mind.