IntrospectiveViews: An Interface for Scrutinizing Semantic User Models

Bakalov, Fedor; König‐Ries, Birgitta; Nauerz, Andreas; Welsch, Martin

doi:10.1007/978-3-642-13470-8_21

Cited by 25 publications

(23 citation statements)

References 6 publications

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“…Furthermore, semantic web technologies were also linked to open user models. Bakalov et al (2010) developed an interface exploiting introspective views for scrutinising semantic user models. Within this research stream, the closest to STyLE-OLM was the work by Cena and Aroyo (2007) who developed a computational framework to enable a semanticsbased dialogue for interoperability of user-adaptive systems in an ubiquitous environment.…”

Section: Open Learner Modelling Approaches That Utilise Semantic Web mentioning

confidence: 99%

From Interactive Open Learner Modelling to Intelligent Mentoring: STyLE-OLM and Beyond

Dimitrova

Brna

2015

Int J Artif Intell Educ

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STyLE-OLM (Dimitrova 2003 International Journal of Artificial Intelligence in Education, 13, 35-78) presented a framework for interactive open learner modelling which entails the development of the means by which learners can inspect, discuss and alter the learner model that has been jointly constructed by themselves and the system. This paper outlines the STyLE-OLM framework and reflects on the key challenges it addressed: (a) the design of an appropriate communication medium; this was addressed by proposing a structured language using diagrammatic representations of conceptual graphs; (b) the management of the interaction with the learner; this was addressed by designing a framework for interactive open learner modelling dialogue utilising dialogue games; (c) the accommodation of different beliefs about the learner's domain model; this was addressed with a mechanism for maintaining different views about the learner beliefs which adapted belief modal logic operators; and (d) the assessment of any resulting improvements in learner model accuracy and learner reflection; this was addressed in a user study with an instantiation of STyLE-OLM for diagnosing a learner's knowledge of finance concept, as part of a larger project that developed an intelligent system to assist with learning domain terminology in a foreign language. Reviewing follow on work, we refer to projects by the authors' students and colleagues leading to further extension and adoption of STyLE-OLM, as well as relevant approaches in open learner modelling which have cited the STyLE-OLM framework. The paper points at outstanding research challenges and outlines future a research direction to extend interactive open learner modelling towards mentor-like intelligent learning systems.

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Section: Open Learner Modelling Approaches That Utilise Semantic Web mentioning

confidence: 99%

From Interactive Open Learner Modelling to Intelligent Mentoring: STyLE-OLM and Beyond

Dimitrova

Brna

2015

Int J Artif Intell Educ

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“…Such multi-model techniques have mostly focussed on instrumenting the usage during a domain-specific user session and are therefore less ambivalent or susceptible to noise. Moreover, as AH techniques are inherently based around structured conceptual models rather than unstructured keyword histories, the aforementioned scrutability and user control can be achieved more easily through the development of model manipulation interfaces (Bakalov et al, 2010).…”

Section: User Dimensionsmentioning

confidence: 99%

A comparative survey of Personalised Information Retrieval and Adaptive Hypermedia techniques

Steichen

Ashman

Wade

2012

Information Processing & Management

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Abstract.A key driver for next generation web information retrieval systems is becoming the degree to which a user's search and presentation experience is adapted to individual user properties and contexts of use. Over the past decades, two parallel threads of personalisation research have emerged, one originating in the document space in the area of Personalised Information Retrieval (PIR) and the other arising from the hypertext space in the field of Adaptive Hypermedia (AH).PIR typically aims to bias search results towards more personally relevant information by modifying traditional document ranking algorithms. Such techniques tend to represent users with simplified personas (often based on historic interests), enabling the efficient calculation of personalised ranked lists. On the other hand, the field of Adaptive Hypermedia (AH) has addressed the challenge of biasing content retrieval and presentation by adapting towards multiple characteristics. These characteristics, more typically called personalisation "dimensions", include user goals or prior knowledge, enabling adaptive and personalised result compositions and navigations.The question arises as to whether it is possible to provide a comparison of PIR and AH, where the respective strengths and limitations can be exposed, but also where potential complementary affordances can be identified. This survey investigates the key techniques and impacts in the use of PIR and AH technology in order to identify such affordances and limitations. In particular, the techniques are analysed by examining key activities in the retrieval process, namely (i) query adaptation, (ii) adaptive retrieval and (iii) adaptive result composition and presentation. In each of these areas, the survey identifies individual strengths and limitations. Following this comparison of techniques, the paper also illustrates an example of a potential synergy in a hybridised approach, where adaptation can be tailored in different aspects of PIR and AH systems. Moreover, the concerns resulting from interdependencies and the respective tradeoffs of techniques are discussed, along with potential future directions and remaining challenges.

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“…We investigate using an open social student modeling approach (which offers parallel views of multiple student models) to guide students to the most appropriate learning content. In this paper, we explore a specific implementation of the open social student modeling approach based on IntrospectiveViews [12] visualization. We do so in the context of a semester-long classroom study.…”

Section: Introductionmentioning

confidence: 99%

“…The implementation and functionalities of QuizJET were described in detail in [11]. The IntrospectiveViews visualization approach was first proposed for scrutinizing semantically-enriched user interest models in [12]. The interface visualizes user interests as a set of keywords displayed on a circular surface gradually painted in shades between red and blue, where the gradient colors denote different degrees of interest.…”

Section: Quizjet Meets Introspectiveviewsmentioning

confidence: 99%

Open Social Student Modeling: Visualizing Student Models with Parallel IntrospectiveViews

Hsiao

Bakalov²,

Brusilovsky

et al. 2011

User Modeling, Adaption and Personalization

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Abstract. This paper explores a social extension of open student modeling that we call open social student modeling. We present a specific implementation of this approach that uses parallel IntrospectiveViews to visualize models representing student progress with QuizJET parameterized self-assessment questions for Java programming. The interface allows visualizing not only the student's own model, but also displaying parallel views on the models of their peers and the cumulative model of the entire class or group. The system was evaluated in a semester-long classroom study. While the use of the system was non-mandatory, the parallel IntrospectiveViews interface caused an increase in all of the usage parameters in comparison to a regular portal-based access, which allowed the student to achieve a higher success rate in answering the questions. The collected data offer some evidence that a combination of traditional personalized guidance with social guidance was more effective than personalized guidance alone.

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IntrospectiveViews: An Interface for Scrutinizing Semantic User Models

Cited by 25 publications

References 6 publications

From Interactive Open Learner Modelling to Intelligent Mentoring: STyLE-OLM and Beyond

From Interactive Open Learner Modelling to Intelligent Mentoring: STyLE-OLM and Beyond

A comparative survey of Personalised Information Retrieval and Adaptive Hypermedia techniques

Open Social Student Modeling: Visualizing Student Models with Parallel IntrospectiveViews

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