Adaptive Educational Hypermedia From generation to generation

Generation to Generation

Peter Brusilovsky

School of Information Sciences, University of Pittsburgh

Pittsburgh, PA 15260, USA

peterb@pitt.edu

SUMMARY

Adaptive hypermedia is a relatively new direction of research on the crossroads of hypermediaand user modeling. Adaptive hypermedia systems build a model of the goals, preferences andknowledge of each individual user, and use this model throughout the interaction with the user,in order to adapt to the needs of that user. Educational hypermedia was one of the firstapplication areas for adaptive hypermedia and is currently one of the most popular and well-investigated. The goal of this presentation is to provide a subjective historical overview ofresearch in adaptive educational hypermedia and summarize the current state of the art.

KEYWORDS: adaptive hypermedia, Web-based Education, Intelligent Tutoring System

INTRODUCTION

Adaptive hypermedia is an alternative to the traditional “one-size-fits-all” approach in thedevelopment of hypermedia systems. Adaptive hypermedia systems build a model of the goals,preferences and knowledge of each individual user, and use this model throughout the interactionwith the user, in order to adapt to the needs of that user (Brusilovsky, 1996). For example, astudent in an adaptive educational hypermedia system will be given a presentation that is adaptedspecifically to his or her knowledge of the subject (De Bra & Calvi, 1998), and a suggested set ofthe most relevant links to proceed further (Brusilovsky, Eklund & Schwarz, 1998). An adaptiveelectronic encyclopedia will personalize the content of an article to augment the user's existingknowledge and interests (Milosavljevic, 1997). A virtual museum will adapt the presentation ofevery visited object to the user's individual path through the museum (Oberlander et al., 1998).AH systems can be useful in any application area where a hypermedia system is expected to beused by people with different goals and knowledge and where the hyperspace is reasonably big.Users with different goals and knowledge may be interested in different pieces of informationpresented on a hypermedia page and may use different links for navigation. AH tries to overcomethis problem by using knowledge represented in the user model to adapt the information andlinks being presented to the given user. Adaptation can also assist the user in a navigationalsense, which is particularly relevant for a large hyperspace. Knowing user goals and knowledge,AH systems can support users in their navigation by limiting browsing space, suggesting themost relevant links to follow, or providing adaptive comments to visible links.

In this presentation, I attempt to provide a review of past and present research on adaptiveeducational hypermedia. I have tried to classify the variety of known work into generations andresearch directions. I hope that this work will help both experienced researchers and newcomersunderstand this field. This review is based on my personal (and probably subjective) view of thefield based on my own work on adaptive hypermedia for more than 10 years. Over these yearsmy view of adaptive hypermedia and my understanding of it has broadened quite significantly. Iwas fortunate to work on adaptive hypermedia problems with several teams that were driven bydifferent goals. I think it has helped me consider adaptive educational hypermedia from severalprospects and avoid a narrow and pragmatic view to it. To make my current prospect andviewpoint clearer to a reader, I deliberately choose to present the overview of the field in twoparallel streams. One stream attempts to provide more objective overview of a whole generationof research, while another stream presents my own research work that falls in the samegeneration of research.

ADAPTIVE EDUCATIONAL HYPERMEDIA: THE FIRST GENERATION

The research on adaptive navigation support in hypermedia can be traced back to the early1990’s. At that time, several research teams had recognized the problems of static hypertext indifferent application areas, and had begun to explore various ways to adapt the behavior ofhypertext and hypermedia systems to individual users. A number of teams addressed theproblems related to navigation in hypermedia (such as the problem of inefficient navigation orthe problem of being lost) that had been discovered when the field of hypertext reached relativematurity at the end of the 1980’s (Hammond, 1989). Other teams addressed the problems relatedto presentation (such as the need to present different information on a hypermedia page todifferent users). Within a few years, a number of technologies for adaptive navigation support(Böcker, Hohl & Schwab, 1990; Brusilovsky, Pesin & Zyryanov, 1993; de La Passardiere &Dufresne, 1992; Kaplan, Fenwick & Chen, 1993) and adaptive presentation (Beaumont, 1994;Böcker et al., 1990; Boyle & Encarnacion, 1994; Boyle & Teh, 1993) were proposed. Theadaptive navigation support technologies introduced by early adaptive hypermedia systems werelater classified as direct guidance, sorting, hiding, and annotation (Brusilovsky, 1996).

It is quite natural that educational hypermedia was one of the first application areas for AH. Ineducational context users with alternative learning goals and knowledge on the subjects requireessentially different treatment. It is also in educational hypermedia where the problem of \"beinglost in hyperspace\" is especially critical. A number of pioneer adaptive educational hypermediasystems were developed between 1990 and 1996. These systems can be roughly divided into tworesearch streams. The systems of one of these streams were created by researchers in the area ofintelligent tutoring systems (ITS) who were trying to extend traditional student modeling andadaptation approaches developed in this field to ITS with hypermedia components (Beaumont,1994; Brusilovsky et al., 1993; Gonschorek & Herzog, 1995; Pérez, Gutiérrez & Lopistéguy,1995). The systems of another stream were developed by researchers working on educationalhypermedia in an attempt to make their systems adapt to individual students (Böcker et al., 1990;De Bra, 1996; de La Passardiere & Dufresne, 1992; Hohl, Böcker & Gunzenhäuser, 1996; Kay &Kummerfeld, 1994).

I entered the field of adaptive hypermedia from ITS side. During my Ph.D. years at the at theMoscow State University I was working on adaptive sequencing of educational material, i.e.,intelligent technologies that can select the most relevant readings, examples, and problems forthe given student at the given time. I have developed several innovative sequencing algorithms(Brusilovsky, 1992a) that were implemented in ITEM/IP system (Brusilovsky, 1992b). After my

graduation, as an adjunct professor at the Moscow State University I directed several graduatestudent projects focusing on elaborating adaptive sequencing technologies and applying them todifferent subjects from geometry to geography. Two of these projects – ITEM/PG (Brusilovsky& Gorskaya-Belova, 1992) and ISIS-Tutor (Brusilovsky & Pesin, 1994) attempted to go beyondthe original sequencing: we suggested what we called adaptive hypermedia for personalizedstudent’s access to educational content (Brusilovsky et al., 1993). By introducing adaptivehypermedia we attempted to add some flexibility to classic adaptive sequencing allowingstudents to participate in selecting the most relevant educational objects. We considered adaptivenavigation support in educational hypermedia as \"best of both worlds\". Choosing the next task inan ITS with sequencing is based on machine intelligence. Choosing the next task in traditionalhypermedia is based on human intelligence. Adaptive navigation support is an interface that canintegrate the power of machine and human intelligence: a user is free to make a choice while stillseeing the opinion of an intelligent system. Following this vision we considered adaptivehypermedia as a necessary component of every ITS (Brusilovsky et al., 1993) and developed aspecific authoring approach and a toolkit for developing adaptive hypermedia components forITS (Brusilovsky, 1997).

Our main focus was adaptive navigation support, currently one of the major AH technologies.We explored several ways of adaptive navigation support in the ITEM/PG (Brusilovsky et al.,1993) and ISIS-Tutor (Brusilovsky & Pesin, 1994) projects. We introduced a specific adaptiveannotation technology that classifies pages with educational material with regard to the user'scurrent knowledge and goals. With regard to goals/interests a page can be relevant or notrelevant. With regard to knowledge, it can be a page with no new concepts, a page with new andready to be understood concepts, or a page that is not yet ready to be learned. Based on thisclassification ISIS-Tutor and ITEM/PG systems color-coded the links to presentation andproblem pages as \"ready\context guide the users to the most appropriate pages. This technology was later extensivelyevaluated and is known to reduce navigation efforts, the time it takes to achieve the goal, whileincreasing learner retention and quality of learning (Brusilovsky & Eklund, 1998; Brusilovsky &Pesin, 1998; Eklund & Brusilovsky, 1998; Weber & Specht, 1997). It has been re-used since inmany adaptive systems. We also explored direct guidance in the form of \"teach me\" button thatprovides a one-click access to the next best task. In one of the versions of ISIS-Tutor we alsoused adaptive link removal to remove all links to not-ready pages.

ADAPTIVE EDUCATIONAL HYPERMEDIA: THE SECOND GENERATION

Despite the number of creative ideas explored and evaluated in the early educational AHsystems, it was not until 1996 that this research area attracted attention of a larger community ofresearchers. There are two main factors that might account for this growth of research activity.The first factor is the accumulation and consolidation of research experience in the field. It isclearly visible that research in adaptive hypermedia performed and reported up to 1996 provideda good foundation for the new generation of research. As we noted above, early researchers weregenerally not aware of each other's work. The early papers provided no (or almost no) referencesto similar work in adaptive hypermedia, and described original methods and techniques. Almostall systems reported by 1996 were laboratory systems developed to demonstrate and exploreinnovative ideas. In contrast, many papers published since 1996 are clearly based on earlierresearch. These papers cite earlier work, and usually suggest an elaboration or an extension oftechniques suggested earlier. In addition, a large number of systems developed since 1996 areeither real world systems, or research systems developed for real-world settings. This isindicative of the relative maturity of adaptive hypermedia as a research direction.

The second and arguably most important factor is the rapid increase in the use of the WordWide Web. The Web, with its clear demand for adaptivity served to boost adaptive hypermediaresearch, providing both a challenge and an attractive platform. Almost all the papers publishedbefore 1996 describe classic pre-Web hypertext and hypermedia. In contrast, the majority ofpapers published since 1996 are devoted to Web-based adaptive hypermedia systems.

In the field of educational adaptive hypermedia, the major driving factor behind the second-generation adaptive educational hypermedia was Web-based education. The need to address theheterogeneous audience of Web-based courses individually was clear to many researchers andpractitioners. A few early adaptive hypermedia systems developed for Web-based educationcontext by 1996 such as ELM-ART (Brusilovsky, Schwarz & Weber, 1996a), InterBook(Brusilovsky, Schwarz & Weber, 1996b), PT (Kay & Kummerfeld, 1997), and 2L670 (De Bra,1996) provided a \"proof of existence\" and influenced a number of more recent systems. Themajority of adaptive educational hypermedia systems developed since 1996 are Web-basedsystems and were developed for Web-based education context. Some earlier examples are:Medtech (Eliot, Neiman & Lamar, 1997), AST (Specht et al., 1997), ADI (Schöch, Specht &Weber, 1998), Hy-SOM: (Kayama & Okamoto, 1999), AHM (Pilar da Silva et al., 1998),MetaLinks (Murray, Condit & Haugsjaa, 1998), CHEOPS (Negro, Scarano & Simari, 1998),RATH (Hockemeyer, Held & Albert, 1998), ACE (Specht & Oppermann, 1998), TANGOW(Carro, Pulido & Rodrígues, 1999), Arthur (Gilbert & Han, 1999), CAMELEON (Laroussi &Benahmed, 1998), KBS-Hyperbook (Henze & Nejdl, 1999), AHA! (De Bra & Calvi, 1998),SKILL (Neumann & Zirvas, 1998), and Multibook (Steinacker et al., 1999).

The choice of the Web as a development platform turned out to be a wise choice foreducational hypermedia systems. It granted long life to a number of pioneer systems. Inparticular, the first Web-based adaptive educational hypermedia systems developed before 1996such as ELM-ART, InterBook, and 2L670 are still in use and have been significantly updatedand extended with a number of new techniques (Brusilovsky et al., 1998; De Bra & Calvi, 1998;De Bra & Ruiter, 2001; Weber & Brusilovsky, 2001). Over the years, these systems were usedfor several experimental studies (Brusilovsky & Eklund, 1998; Brusilovsky et al., 1998; De Bra& Calvi, 1998; Eklund, 1999; Weber, 1999) that further guided development of the field.

The work on second-generation adaptive educational hypermedia was performed mainlybetween 1996 and 2002. It can be roughly split into three different streams with no clear-cutborders. The largest stream of work (produced mainly by researchers coming from the Web-based education side) focused on creating adaptive Web-based educational systems withelements of adaptive hypermedia. The main motivation was to produce systems that could beused in the process of teaching, not in developing new technologies. As a result, the works of thisstream broadly re-used already existing technologies and explored various subject areas andapproaches. A smaller stream of work (produced mainly by researchers who were very familiarwith ITS or the adaptive hypermedia area) focused on producing new techniques for adaptivehypermedia. For example early AHA! project (De Bra & Calvi, 1998) explored severalapproaches to link removal, MetaLinks (Murray, 2001; Murray et al., 1998) explored advanceapproaches to hyperspace structuring, INSPIRE explored the use of learning styles(Papanikolaou et al., 2003), and MANIC (Stern & Woolf, 2000) explored innovative approachesfor user modeling and adaptive presentation. Finally, the originally small but rapidly expandedstream of work focused on developing frameworks and authoring tools for producing adaptivehypermedia systems. The majority of work in this direction achieved the level of frameworks foradaptive Web-based education KBS-Hyperbook (Henze & Nejdl, 2000), SKILL (Neumann &

Zirvas, 1998), Multibook (Steinacker et al., 1999), ACE (Specht & Oppermann, 1998),CAMELEON (Laroussi & Benahmed, 1998), MediBook (Steinacker et al., 2001), andECSAIWeb (Sanrach & Grandbastien, 2000). While not reaching the level of end-used authoringtools, a framework typically introduces a generic re-usable architecture and approach that couldbe used to produce a range of adaptive systems with low overhead. A few of the mostexperienced teams that were working on adaptive hypermedia projects for several yearsintroduced practical authoring systems that could be applied by end-used to develop adaptivehypermedia systems and courses (Brusilovsky, 2003). Examples are InterBook (Brusilovsky etal., 1998), ART-Web/NetCoach (Weber, Kuhl & Weibelzahl, 2001), AHA! (De Bra & Ruiter,2001), ACE (Specht & Oppermann, 1998), and MetaLinks (Murray, 2003).

I started exploring Web-based adaptive hypermedia at Moscow State University in 1994(Brusilovsky, 1995a; Brusilovsky, 1995b) and continued this work at the University of Trier asan Alexander von Humboldt fellow. I was privileged to work with Gerhard Weber, the head ofone of the most prominent German ITS research group and a developer of ELM-PE system(Weber & Möllenberg, 1995). Together with Prof. Weber, we developed an innovative andpractical Web-based ITS ELM-ART (Brusilovsky et al., 1996a; Weber & Brusilovsky, 2001) –the first one to integrate a large adaptive hypermedia component. This system later won theprestigious European Academic Software award and, according to researchindex.com remainsone of the most highly cited ITS/AH systems.

While ELM-PE was a domain-oriented ITS, the work on the system allowed us to generalizethe domain-independent aspects of ELM-ART and eventually develop several authoring systems.The list of authoring systems that have roots in ELM-ART include InterBook (Brusilovsky et al.,1996b), ART-Web/NetCoach (Weber et al., 2001), and ACE (Specht & Oppermann, 1998).InterBook, the first system in this group, was developed at Carnegie Mellon’s Human-ComputerInteraction Institute where I moved to work with John Anderson, one of the greatest scholars inthe field of ITS and Cognitive Science. InterBook was an attempt to refine the concepts andtechnologies of adaptive navigation support explored in domain-dependent systems ISIS-Tutorand ELM-ART (Brusilovsky et al., 1998). InterBook has been used to run several large-scaleempirical studies of educational adaptive hypermedia (Brusilovsky & Eklund, 1998; Brusilovsky& Pesin, 1998) that have demonstrated the value of adaptive hypermedia in proving personalizedaccess to learning material. It was also used to develop several adaptive Web-based coursesincluding an ACT-R course developed with Prof. Anderson (Brusilovsky & Anderson, 1998).

ADAPTIVE EDUCATIONAL HYPERMEDIA: THE THIRD GENERATION

Altogether, the systems of the second-generation adaptive educational hypermediademonstrated a variety of ways to integrate adaptation technologies in the context of Web-basededucation and the value of these technologies. Yet, they failed to influence practical Web-basededucation. Almost 10 years after the appearance of the first adaptive Web-based educationalsystems just a handful of these systems were used for teaching real courses, typically in a classlead by one of the authors of the adaptive system. Instead, the absolute majority of Web-enhanced courses rely on so-called learning management systems (LMS) such as Blackboard(Blackboard Inc., 2002) or WebCT (WebCT, 2002). LMS are powerful integrated systems thatsupport a number of needs of teachers and students. Teachers can use a LMS to develop Web-based course notes and quizzes, to communicate with students and to monitor their progress.Students can use it for communication and collaboration. The complete dominance of LMS overadaptive systems may look surprising. Actually, for every function that a typical LMS performwe can find an AWBES that can do it much better than the LMS. Adaptive textbooks created

with such systems as AHA! (De Bra & Ruiter, 2001), InterBook (Brusilovsky et al., 1998) orNetCoach (Weber et al., 2001) can help students learn faster and better. Adaptive quizzesdelivered by such systems as SIETTE (Conejo, Guzman & Millán, 2004) and QuizGuide(Sosnovsky, Brusilovsky & Shcherbinina, 2004) evaluate student knowledge more precisely withless questions. Adaptive class monitoring systems (Oda, Satoh & Watanabe, 1998) give theteachers much better chances to notice students that are lagging behind. Adaptive collaborationsupport systems (Constantino Gonzalez, Suthers & Escamilla de los Santos, 2003) can enforcethe power of collaborative learning. It seems obvious that the problem of modern adaptivesystems is not their performance, but their inability to answer the needs of practical Web-enhances education. The challenge of integrating adaptive hypermedia technologies into theregular educational process has defined the current third generation of adaptive educationalhypermedia research.

Different research groups stress different reasons for the domination of LMS and pursuedifferent research directions. One of the research streams focused on LMS’s versatilityattempting to provide in one system as many teacher and learner support features (from contentauthoring to quizzes to discussion forums) as provided by a modern LMS - plus an ability toadapt to the user (Specht et al., 2002a; Weber et al., 2001). A different stream addressed anothersuperior feature of an LMS - an ability to integrate open corpus Web content. The systems of thisstream explored several approaches to integrating open corpus content in an adaptive hypermediasystem while providing adaptive guidance to this content (Brusilovsky, Chavan & Farzan, 2004;Carmona et al., 2002; Henze & Nejdl, 2001). Most recent projects, however, choose not tocompete with present-day LMS, but instead to focus on adaptive features of the cominggeneration of Web-based educational systems. This new generation that is coming to replacemodern LMS will be based on system interoperability and reusability of content to be supportedby a number of emerging standards including the most often cited SCORM (ADLI, 2003; ADLI,2004). A number of research teams are trying now to integrate existing adaptive hypermediatechnologies with the ideas of standard-based reusability (Bollin, Mittermeir & Wohlfahrt, 2002;Conlan, Dagger & Wade, 2002a; Conlan et al., 2002b; Delestre, PÈcuchet & Barry-GrÈboval,1999; Dolog et al., 2003; Fischer, 2001; Karagiannidis, Sampson & Cardinali, 2002; Specht etal., 2002a) though other teams argue that the current generation of standards is not able tosupport the ideas of adaptive learning (Brusilovsky, 2004; Mödritscher et al., 2004). Other teamsfocus on related issues that are not covered by standards yet, such as resource discoveryarchitectures (Manouselis & Sampson, 2002; Nejdl et al., 2002; Simon et al., 2003; Specht et al.,2002b). Yet another direction of work attempts to explore the ideas of the Semantic Web forcontent representation and resource discovery and capitalise on the standards such as RDF andTopic Maps (Dichev, Dicheva & Aroyo, 2004; Dolog et al., 2003; Jacquiot, Bourda & Popineau,2004; Nejdl et al., 2002).

Our work on 3rd generation adaptive hypermedia has focused on three topics. We started ourquest for practical AH systems in 1998 with the exploration of advanced indexing techniques.We expected that advanced content indexing approaches that include content typing andintroducing multiple concept roles will help in dealing with large volumes of educational contentwhile providing better guidance precision. We have successfully implemented advancedindexing ideas in two projects - ADAPTS and CoCoA. ADAPTS, a performance support systemfor avionics technicians (Brusilovsky & Cooper, 1999; Brusilovsky & Cooper, 2002) hasintegrated an AI-based intelligent aircraft diagnosis with an adaptive hypermedia personalizedinformation access. ADAPTS has demonstrated that an elaborated approach to content indexingcan be used for advanced adaptive presentation and adaptive navigation support in a huge

volume of hypermedia content. CoCoA (Brusilovsky, 2000) was developed during my work forCarnegie Technology Education, a non-profit company founded by Carnegie Mellon University.A part of my mandate and my major motivation was to develop an innovative platform forpractical personalized Web-based education. However, due to the need to deliver content throughnon-adaptive LMS, we have focused on a different practical use of advanced content indexing -content checking (Brusilovsky & Vassileva, 2003). The reality of practical Web-based educationhas demonstrated that classic closed corpus adaptive hypermedia based on manual contentindexing has a limited applicability in the context of modern Web-enhanced education that has todeal with large volumes of diverse and poorly indexed educational material. While in someapplication areas (such as aircraft maintenance explored in ADAPTS) it is feasible to have ateam of experts to encode the content knowledge about thousands and thousands of availableresources, the economics of practical education cannot afford it. Even in the best educationalDigital Libraries, content metadata are insufficient for the needs of adaptive guidance and aremost often incomplete and incoherent.

After joining the School of Information Sciences at the University of Pittsburgh in 2000, Ifocused my adaptive hypermedia research on two goals: developing technologies for “opencorpus adaptive hypermedia” and developing a component-based architecture for assemblingadaptive Web-based educational systems. Working on the first goal, we have developed theKnowledge Sea (Brusilovsky & Rizzo, 2002a; Brusilovsky & Rizzo, 2002b) and Knowledge SeaII (Brusilovsky et al., 2004) systems for browsing-based access to external resources usingKohonen self-organized maps. Knowledge Sea has explored several techniques that are able toorganize open corpus educational content and to provide some form of adaptive navigationsupport without manual context indexing. Working on the second goal, we have developed anopen architecture KnowledgeTree (Brusilovsky, 2004) that allows us to assemble a versatileadaptive educational system from re-usable components developed by different teams.

Overall, I hope that the work on the 3rd generation adaptive educational hypermedia willeventually lead to deeper and deeper integration of adaptive technologies into the process ofeveryday Web-enhancing learning thus maximizing the ability of every student to achieve his ofher learning goals.

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