Automatic Authoring of Adaptive Educational Hypermedia

Adaptive Hypermedia (AH) can be considered the solution to the problems arising from the “one-size-fits-all” approach to information delivery prevalent throughout the WWW today. Adaptive Educational Hypermedia (AEH) aims to deliver educational content appropriate to each learner, adapted to their preference and educational background. The development of AEH authoring tools has lagged behind that of delivery systems. Recently AEH authoring has come to the fore, with the aim of automating the complex task of AEH authoring, not only within a system but porting material between different AEHs. Advances in intra-system automation are described using the LAOS framework, whereby an author is only required to create a small amount of educational material which then automatically propagates throughout the system. Advances in inter-system conversions are also described; the aim is to move away from a “create once, use once” authoring paradigm, currently in force with most AEH systems, towards a “create once, use many” paradigm. The goal is to allow authors to use their content in the AEH delivery system of their choice, irrespective of the original authoring environment. As a step along this road we describe the usage of a single authoring environment (MOT) to deliver content in three independentlydesigned Educational Hypermedia systems (AHA!, WHURLE and SCORMcompliant Blackboard). This chapter describes therefore advances in automatic authoring and conversion towards a simple and flexible AEH authoring paradigm. INTRODUCTION TO AEH AUTHORING Adaptive hypermedia (AH; Brusilovsky, 2001a) started as a spin-off of hypermedia and Intelligent Tutoring Systems (ITS; Murray, 1999). Its goal was to bring the user model capacity of ITSs into hypermedia. However, due to technical limitations, such as bandwidth and time constraints, AH only implemented simple user models. This simplicity also gave AH its power as, suddenly, there were many new application fields and also implementation was considerably easier. Early AH research concentrated on variations of simple techniques for adaptive response to changes in user model. No wonder that most of AH development was research-oriented, applied only to the limited domain of courses the researchers themselves were giving (AHA!, De Bra & Calvi, 1998; Interbook, Brusilovsky et al., 1998; TANGOW, Carro et al., 2001) and with very rare commercial applications (Firefly, developed at MIT Media Lab. and acquired by Microsoft). Recently there has been a shift in attitudes. The development of the Semantic Web (Berners-Lee, 2003), and the ongoing push to develop Ontologies (Gruber, 1992) for knowledge domains has extended the importance of AH. Indeed AH now appears to be the tool of choice for collating the static information of these new approaches and bringing then to life. Moreover, AH is spreading from its traditional application domain, education, to others, especially the commercial realm, which is eager to be able to provide personalization for its customers. Indeed, we often see the phenomenon from other communities re-inventing adaptive hypermedia for their own purposes and applications. Adaptive Educational Hypermedia (AEH; Brusilovsky, 2001b) is, in principle, superior to regular Educational Hypermedia (EH), as it allows for personalization of the educational experience. Regular EH, such as that delivered by WebCT and Blackboard is not adaptive: exactly the same lesson is delivered to each student. Pedagogical research has shown (Coffield, 2004) that different learners learn in different ways. This is a truth self-evident to most teachers; if a student is having trouble learning a subject, then they will alter the manner in which they are teaching it and try a different approach. Traditional EH systems could be compared to inflexible teachers, who base their lesson mainly on drilling and repetition. Educational systems (real or virtual) that adapt their presentation to the needs of each learner aim to improve the efficiency and effectiveness of the learning process. If each learner has their own Learning Style (Coffield, 2004) and is given a set of resources specific to this particular style then that learner will not only learn ‘better’, but will be able to more effectively develop the given information into deeper understanding and knowledge. AEH systems seek to address the inflexibility of current EH methods. Systems such as MOT, AHA! and WHURLE all answer the need for an adaptive and flexible approach to teaching. They allow current online educational systems to break away from the “one-size-fits-all” mentality and move towards having an appropriate lesson for each student. AEH systems aim to improve upon current static EH systems. This is not to say that they are the universal panacea for online education. Education is not undertaken in a vacuum; the social aspect is also vital. It is essential for learners: to be able to build common ground; to ask and answer (negotiate meaning); to argue and debate; to explicate mental models; to share expertise; to collaborate; and to construct novel ideas and understanding. Work on computer-supported cooperative work (CSCW) addresses this side of the educational process, and often AEH systems will fold this research into them (for example WHURLE can be used in such a social manner). Collaborative work can be encouraged by the use of simple online social tools: email, for asynchronous communications; fora, for persistent asynchronous group discussions; and chat rooms, for synchronous group discussions. The addition of Adaptation to this whole structure is another improvement to the student’s personal online educational experience. However, with increasing numbers of students, and the resulting increase in class size of many learning bodies, traditional methods of education (such as the tutorial, and the field trip) often become impractical – in terms of time and cost. Online education can help to fill this need, EH and AEH were developed to do just this. Given the qualities of AEH systems, it might be reasonable to expect a much wider uptake than actually is happening. A major hindrance of this is that the creation of good quality AEH is not trivial, often involving a greater expenditure of time and money to produce, when compared to standard online educational systems. Creating content within a single AEH system can be a complex and difficult undertaking. Many issues must be considered, amongst them: • What knowledge domain(s) will the lesson partake of? • Do any previous e-learning materials exist that are both available and reusable? • What are the objectives of the lesson and how are they to be achieved for a heterogeneous group of learners? • Which traits of a learner are to be modelled and how is this User Model created? • How is the data, concerning these traits, to be gathered, implicitly (without the learner’s knowledge) or explicitly (information is requested from the learner)? • Given that there exists a heterogeneous group of learners how many versions of the same material need to be created? For example, if a group of learners are to be divided into two sub-groups, one which requires visual materials and the other which requires textual based materials, then it follows that at least two sets of the material are required to teach that lesson. • What are the rules for adaptation? Does the author of the lesson have any control over their use or creation? • How are the various versions to be presented to the learner, and does the learner have any control over this? Most AEH systems require the author to consider these issues with little or no help. The author is left adrift and often must become an expert in Adaptive Hypertext before creating anything. It is hardly surprising then, that AEH systems are not used widely outside of their own development circles, as these developers are the only people with the required level of expertise to create content for them! This problem arose whilst AEH was still a new area of research. A natural “one-to-one” paradigm developed, with developers creating the AEH system that was specific to their desires and insights, along with the necessary authoring tools. Cross-platform considerations were not important; transporting data between systems was generally considered irrelevant. Nowadays, a lot of research effort concentrates on the ‘authoring challenge’ (Wu et al., 1998; Specht et al., 2001; Murray, 2003; Cristea & Cristea, 2004) in AEH, with the goal of reducing complexity, thereby delivering the greater flexibility of an AEH for the same cost as current online systems. This chapter approaches this challenge from the point of view of automation, minimizing, but not restricting, the author’s input and reducing overload. Advances in inter-system conversions are also described, the aim being to move away from a “create once, use once” authoring paradigm, as with most AEH systems; towards a “create once, use often” paradigm. The goal is to allow authors to use their content in the AEH system of their choice, irrespective of the original authoring environment. As a step down this road we describe using a single authoring environment (MOT) to deliver content in three independently designed Educational Hypermedia systems (AHA!, WHURLE and SCORM compliant Blackboard). The remainder of this chapter is organized as follows. First we present LAOS, a generic AH authoring framework that incorporates several layers of semantics to better express the authored AEH. The major part of this chapter focuses on the two major dimensions of AEH authoring automation that we have identified: automation within an AEH authoring environment, and automation outside it, comprising conversion between AEH systems. Finally we draw conclusions.