competences: Un langage graphique pour concevoir et apprendre, Presse de ... [14] L.-S. Vygotski, Pensée et langage, 3ème édition, La. Dispute, Paris ...
Holistic, Evolving and Multi-viewpoints Learner Model Lucie Moulet Olga Marino Richard Hotte TÉLUQ – Université du Québec TÉLUQ – Université du TÉLUQ – Université du À Montréal, Université Paris 5 Québec À Montréal Québec À Montréal {lucie.moulet; olga.marino; richard.hotte}@licef.teluq.uqam.ca
Abstract In this paper, we present our proposal of a learner model for the personalization of learning in distance and on line learning environments.1 The current researches on semantic referential with ontologies and the semantic web allow us to believe in the importance of the integration of semantic in actor modeling. We propose a learner model that is competency oriented and that integrates the learner ePortfolio. The model needs also to be holistic and evolving. It should reflect the perception of the learner that the different actors of the process may have. We will first describe the model static structure. We then explain the notion and interest of multi-viewpoints in the context of learner modeling. Finally, we discuss the issues related to the model evolution and we explain how our model integrates these notions.
1. Introduction The need for life long learning and the development of information technologies use explain the major role of distance learning. The issues around this thematic are multiple: the semantic web [1], ontologies, learning objects repositories… We are interested in the issue of distance learning personalization. Adding semantic on learning objects is a favorable framework for a more relevant personalization. A lot of work is done in the area of semantic referencing of learning objects, like for example the Learning Object Meta-data (LOM) standard from IEEE. We want to shift here the attention form the resources to the actor, with the assumption that relevant personalization is possible 1
This research takes place in the scope of the LORNET research project partially financed by CRSNG. Lucie Moulet has a Ph.D. scholarship from CRSH.
through actor modeling. We focus thus on the learner model. We must then respond to this question: How to model, create, update and use a learner model to personalize his/her learning in the context of an open rich distance and on line environment? We propose to use a competency driven approach for the creation of a holistic, evolving and multi-viewpoints learner model. The second section of this paper is a literature review of different learner model uses. We study four domains in which learner model are used for different purposes. These domains are intelligent tutoring system (ITS), adaptive hypermedia (AH), ePortfolio, and competency oriented model. The third section set out our learner model proposition. In section four, we will discuss problematic born from the multiviewpoints characteristic of our model. Issues related to the model evolution are exposed in the fifth section. We end with some conclusions and future work.
2. Different modeling
approaches
to
learner
We found different names for user modeling in the literature: user, learner or student, model or profile. We will use in this paper the term learner model: learner because we are interested in the users who use the system to learn (either academic student or adults living e-learning situations in their working environments); Model for our approach here is to define a generic model that can host different learner profiles. In this section, we present four uses of learner model. First, we present the domain oriented learner model used in intelligent tutoring system. Second, we explain interface oriented learner model in adaptive hypermedia. Then, we discuss productions oriented learner model such as ePortfolios. Finally, we explore the competency oriented model.
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2.1. Learner model in intelligent tutoring systems In intelligent tutoring systems, ITS, the learner model is domain oriented; it contains learner’s knowledge about a particular domain or sub-domain. John Self [2] defines the student model in ITS as a 4tuple containing procedural knowledge, conceptual knowledge, individual traits and the student history. He explains that the model is used by an ITS to answer questions about the student using the system. In ITS, the learner model is thus a cognitive model representing the learner’s knowledge and is used to adapt the system to the learner particular needs. There are different kinds of model; the most frequently used is the overlay model. It contains learner’s knowledge for a particular domain and the learner model is a sub-model of the expert knowledge. Only correct knowledge is represented. Other model types contain this correct knowledge but also misconceptions. The ITS adapts itself to a particular learner to correct his misconceptions. However, the learner knowledge model is always compared to a particular domain knowledge model.
2.2. Learner model in adaptive hypermedia Adaptive hypermedia, AH, use also learner models to personalize their learning [3]. Brusilovsky [4] state that in AH a model of the goals, the preferences and the knowledge of each learner is built and used during the interactions with the user to adapt the system to the needs of this learner. We have found in AH literature two types of adaptation [5]: adaptive presentation and adaptive navigation support. Adaptive presentation is made for resource presentation. And navigation adaptation is the adaptation of the navigational structure of the resource released to the learner. The navigation adaptation is the most commonly used in education [4]. We can see in the literature that researches on personalization head for more advanced adaptation functionalities (more semantic and cognitive), often based on the technology offered by the semantic web. For example, Dagger and al. [6] are making a research which challenge is to extend adaptation axes not only on content, but also on pedagogical model, communication and learning activity. The emerging idea in learning personalization is the semantic referencing of learning objects and of actors. But this kind of research are at an early stage and do not represent most researches in the AH field.
2.3. ePortfolio A new way for collecting, organizing and sharing student’s productions is the ePortfolio. We have analyzed ePortfolio definitions found in the literature and we conclude that there is no consensus about the content nor the uses of an ePortfolio [7]. Never the less, all definitions agree on seeing an ePortfolio as a collection of digitalized learner’s productions. Regarding the content, we will adopt IMS global learning consortium ePortfolio definition [8], which states that ePortfolios are “collections of personal information about a learner that represent accomplishments, goals, experiences, and other personalized records that a learner can present to schools, employers, or other entities”. Concerning the uses, four major uses have been identified; ePortfolio are used to: (1) describe and demonstrate, (2) plan, (3) reflect, and (4) share the content of the ePortfolio. We identify three types of ePortfolio in the literature [8, 9]. Personal ePortfolio are made for self-reflection, they can be used to journal experiences, they allow to organize materials from classes and activities and they help students recognize skills and make decisions. The second type is learning ePortfolio. They are used to showcase student learning; they provide a framework for assessing academic progress and they demonstrate how skills have been developed over time. The third type is professional ePortfolios, which can help to make career decisions, to demonstrate that one has met program or certification requirements; they can also be used to present skills and accomplishments for employment and to review professional development for career advancement.
2.4. Competency oriented model Another way to model a learner is the competency approach. We can find in the literature a lot of competency definitions but there is some consensus: a competency is a complex know-how integrating skill and knowledge, referring to cognitive, affective, social or psychomotor skills and which is specific to a particular context [10]. The term "integration" is important because it underlines the necessity of the existence of links between the different competency artifacts. Gilbert Paquette [11] defines a competency as a relation between actor, skill, knowledge and context. This definition is illustrated on figure 1.
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productions oriented (with the ePortfolio concept). The next section describes in detail our learner model proposition.
Competency
Actor Knowledge
Context Skill
Figure 1. The competency concept Knowledge can be a concept, a procedure, a principle or a fact. Skills describe processes that can be applied to knowledge in a specific context. Skills are then at a meta-cognitive state because they are knowledge about knowledge. Paquette suggests also a skills taxonomy which allows us to classify skills according to their cognitive complexity. The creation of this taxonomy is born from the integration of the work, among others, of Bloom, Romiszowski, Krathwohl, Merill, who have created taxonomies for different learning domains (cognitive, affective, meta-cognitive and psychomotor). For example, To plan is a high level skill: we can plan a project’s execution. We identified two kinds of competencies: domain competencies and core competencies. IMS Global Learning Consortium [12] proposes also a competency definition. They use the term competency in a large sense, including skills, knowledge, tasks, and learning outcomes. The definition contains four elements: (1) an identifier (a unique label that identifies the competency), (2) a title (a text label), (3) a description (optional, text label interpretable only by humans), and (4) a definition. Definition is the most interesting element. It can be composed by statements that we can see as attributes. Paquette’s competency definition can easily be made compatible with IMS competency definition. Skill and knowledge elements of the competency definition will be statements in the IMS definition. The first two uses of learner model identified in the literature, in ITS and in AH, don’t respond to the needs of our project. More precisely, using learner model for presentation and navigation adaptation, like in AH is out of the scope of our project. And concerning ITS, we need a model of the cognitive state of a learner but we need to have this model for more than one sub-domain. We don’t want a learner model for a particular learning domain; we need a model representing all of the students’ learning. We propose to create a learner model integrating two different learner modeling approaches: domain oriented (with the competency approach) and
3. Holistic learner model Our goal is to model the learner in distance and on line situations to adapt, improve and personalize his/her learning. We have thus to model someone who is going to learn in different domains and contexts; we call this kind of model: holistic learner model. We choose a competency approach for this modeling of learner cognitive state. We also integrate an ePortfolio in our model as well as learner's personal and professional information. Figure 2 illustrates our model proposition. Domains competencies
PPI ePortfolio
Core competencies
Figure 2. Learner model Competencies are the heart of our learner model. We will work with Paquette's competency definition [11]. Since we are modeling the learner actor, we will concentrate our reflection on the three other elements of the competency definition that is knowledge, skill and context. We choose this competency approach because it offers a strong semantic referencing to link the learner model with the learning objects. We assume that semantic referencing on competencies is stronger than semantic referencing on knowledge to link the learner model with the pedagogical scenario, the resources and the other actors. Stronger because we have information about the knowledge but also about the skill associated with this knowledge and about the context in which the knowledge is used at a particular level of skill. The semantic referencing is stronger because it is composed of different elements: knowledge, skill and context. We believe that this semantic referencing is essential for a pertinent personalization according to learner expectations and needs. Semantic referencing may occur for example if the knowledge element of a competency definition is linked with a particular ontology. The second component of our model is the ePortfolio. It contains learner productions.
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According to the ePortfolio study presented earlier, we use here a learning ePortfolio (to showcase student learning, and to demonstrate how skills have been developed over time). Integrating an ePortfolio in our learner model allow students to reflect on their own learning and to be involved in their training by participating in its organization. An ePortfolio contains also proof of learner’s progresses. Personal and professional information, PPI, is the learner link to his or her broad world. Learning is a continuous process which occurs in a specific context. This context may vary. Learning is built in universities but also in professional environment. PPI will allow us to gain information about learners; more especially it will help us to collect competencies developed in professional and personal contexts. This information may be particularly important in the case of continuing education. The personal and professional information are linked to domains and core competencies achieved by a learner in his/her personal and professional environments. Likewise, learner productions contained in the ePortfolio can illustrate domains or core competencies. A production can illustrate none, one or more competencies and a competency can be illustrated by none, one or more productions. By making this link explicit, we address a problem identified by Eyssautier-Bavay [13] regarding ePortfolios. Eyssautier-Bavay identifies a difficulty concerning competencies evaluation through ePortfolio content. Effectively, productions don’t necessarily permit to infer generalized competencies. We resolve this problematic by integrating competencies model and ePortfolio in a same learner model. We limited the problem to the more precise question: Who add this information in the model? We will explore this issue later in this paper. This learner model is also made to represent a person who is learning simultaneously in his/her different contexts and not to represent a person who is learning in a specific sub-domain. That's why it's a holistic learner model. It's made to follow a learner during all his/her learning in different contexts. We have presented an isolated picture of the learner model. But this model is situated in a rich learning context. As Figure 3 illustrates, learning is a social process where different actors are involved [14]. Five roles have been identified: (1) the learner, (2) peer learners, (3) professors, (4) tutors, and (5) others (for example a member of the administrative staff). These different actors can execute different tasks (add, modify, delete or certify) on different elements of the model (productions, competencies, links…).
LU Ext.
LU Univ.
Professor Learner Domains competencies
LU Univ.
LU Ext. PPI ePortfolio
Core competencies
Other Mentor
Learner / Peer
LU Univ.
Figure 3. Contextual learner model Hansen and McCalla [15] assert that opening the learner model to learners and peers supports reflection on learning. We also think that it is important that different users can access the model. The model is linked with learning units (LU) issued from universities or enterprises and with different actors.
4. Multi-viewpoints learner model We have already stated that learning takes place in the learner’s different learning situations and through social interactions. Different units of learning as well as actors interact with the learner and should be allowed to register the result of these interactions in the learner model. The learner model is thus seen from different viewpoints. A viewpoint is “A mental position from which things are viewed” [16]. As described in Marino and al. [17] a viewpoint establishes a partial view of the observed object; depending on the observer some, but probably not all, of the observed attributes are concerned in a viewpoint. Moreover, as noted by Dieng and al. [18], several viewpoints on a same object or knowledge may be either consensual of conflicting2. By 2
Dieng and al. identify two other notions: correspondence and contrast which refer to differences in the semantic notation of concepts and which, for us, are either resolved using a common competency referential model either in clear conflict. Thus they end corresponding to our two main categories: consensus and conflict.
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consensual viewpoints we mean that if two or more observers look at a same set of attributes, they will see the same values. In the context of our work, consensual viewpoints means that if two actors or units of learning have something to say about one learner’s competency or production in a particular moment in time, their statements will be the same: they agree on the student’s competency value. Conflicting viewpoints, on the contrary, appear when two observers regarding a same object in a same moment in time state different values for some of these objects attributes. In the case of a competency oriented learner model, we should expect conflicts to arise quite often; indeed, competency assessment or evaluation is a complex task, especially for core competencies. Just imagine a system, a tutor, a learner and his/her peers having to assess some learner’s collaboration skills. Our learner model is a multi-viewpoints model composed of the core learner model and the related learner model viewpoints. The core learner model corresponds to the intersection of all viewpoints. In other words, it holds all the learner information that has the consensus of the different human and machine actors. This information includes the personal and professional information (PPI) as well as the learner ePortfolio productions. For the competencies and the links between these competencies and the ePortfolio and the PPI, only those competencies and links accepted by all actors are kept in the core model. Linked to this core learner model, there are as many viewpoints as there are differentiated observers allowed to modify the learner model (tutors, professors, peers, learning units, etc.) Those viewpoints are not pre-established but settled by the learning context of the learner. Thus for instance, while one university may be interested in defining one viewpoint per teacher teaching the learner, another one might have a single viewpoint representing the staff record of the learner competencies. The structure of a learner model viewpoint is similar to the structure of the core learner model. It contains domain and core competencies and links between those competencies and the learner PPI and ePortfolio in the core model. It is worth noticing that the list of domain competencies of a viewpoint (for instance the management professor’s viewpoint) might be different from the list of domain competencies of another viewpoint (for instance the computer science professor’s viewpoint). Domain competencies in the core learner model include all competencies referred to by the different viewpoints.
When a learner model competency or link modification is proposed by one of the actors in the system, the viewpoint corresponding to this actor is updated with the modification and a modification proposal mechanism is launched. This modification proposal mechanism is defined outside from the model and takes into account organizational hierarchies and conflict solving strategies. For instance, a tutor evaluation on a domain competency may be delivered for approval to the course professor but probably not to the other students of the class (peer group). Regardless of whom will be asked for approval, the mechanism gets a modification proposal from an actor and delivers a modification status which can be of three kinds: a) widely accepted, b) rejected by , c) in conflict with existing core model data . This final case may occur, for instance, when trying to give lower competency levels to one already evaluated competency. If the modification is widely accepted, it is reflected in the core model. If not, a conciliation mechanism may be launched to get a consensus. If no consensus is attained, the modification is kept only in the proponent viewpoint and not propagated to the core model.
5. Evolving learner model Cognitivist approach considers learning as an information processing. ITS are based on this understanding of the learning process. For us, learning is a knowledge building process proceeding from interaction between a learner and his/her environment [19]. From this environment the learner pull off his learning conditions. Thus we can consider learning as a social act which evolves taking into account interaction with this environment. That makes it a dynamic learning process. A learner model has to reflect this characteristic and must then be evolving too. An evolving learner model updates itself according to the learning progress. McCalla and al. [20] also propose a dynamic learner model in their active open learner modelling approach. But our approach differs from theirs because we propose a holistic and global model and not a model computed just-in-time for a specific purpose. When exploring our learner model evolution, we have to ask us three questions: (1) what is the nature of the exchanged information? (2) when takes place the information exchange? and (3) who is involved in the information exchange? Concerning the first question, we identify five information types: (1) a learner production, (2) a
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competency, (3) a link between a competency and a PPI or a production, (4) a production, a competency and the link between them, and (5) traces of the interaction of the learner with the learning system. The structure of our model can easily support the first four information types. For the last one, an analysis has to be done to interpret the collected information before updating the learner model. Concerning the "when" question, two actors can trigger a modification of the model: the learning system and the human actors. The learning system can intervene at four granularity levels. The model evolution can take place: (1) at the end of a training, (2) at the end of a course, (3) at the end of a learning activity (included in a course), and (4) after a resource’s use. The choice of using one or the other of these granularity levels can depend on institutional constraints. For example, in universities if a student has a course module competencies, he will be ask to take the whole course. Conversely, in professional world, the employee can take only modules that he needs. The actors can also be at the head of an evolution by adding information at any moment. To deal with this evolution dimension, the learner model proposed in the preceding section will be extended to include different learner model versions. The strategy proposed here is to create a token with the information of the actor proposing the modification, the moment of the proposal and its context. A copy of the learner model is made. The modification is registered according to the validation process described in section four in this copy which becomes the current learner model. By this mechanism we keep the trace of the model evolution. The model can then be searched by viewpoint or by version and the evolution of a competency can be tracked in the time.
6. Conclusion We have designed a learner model that is based on both a competency approach and the learner ePortfolio. This model proposes a holistic view of the learning process: it takes into account the learner learning situations as well as his/her social interactions. Moreover, the different viewpoints of the actors participating in the learning process are being represented as well as their consensus and conflict. Finally, being convinced that learning is a permanent process, the proposed learner model is an evolving model that reflects the learner progression. We expect that, once integrated in a semantically referenced e-learning environment, this model will
allow for personalization, self-reflection and evaluation. It will also allow the learner to make significant learning choices. The evolutive aspect of the model will provide for a source of analysis and diagnosis of learners and learning situations. On the other hand, viewpoints offer the possibility of stating conflicts as a first step of the negotiation of a consensus and as a rich source of learning.
7. References [1] T. Berners-Lee, J. Handler, and O. Lassila, “The Semantic Web”, Scientific American, 2001. [2] J.A. Self, Student models: what use are they?, In P. Ercoli and R. Lewis, Artificial Intelligence Tools in Education, Amsterdam, North-Holland, 1988. [3] S. Garlatti and Y. Prié, “Adaptation et personnalisation dans le web sémantique”, Revue i3.org, 2004. [4] P. Brusilovsky, “Adaptive navigation support in educational hypermedia: The role of student knowledge level and the case for meta-adaptation”, British Journal of Educational Technology, 2003, pp. 487-497. [5] P. Brusilovsky, “Adaptive hypermedia”, User Modeling and User Adaptated Interaction, 2001, pp. 87-110. [6] D. Dagger, V. Wade, and O. Conlan, “Developing Active Learning Experiences for Adaptive Personalised eLeraning”, International Conference Adaptive Hypermedia, 2004. [7] L. Moulet, “Revue de littérature de l’ePortfolio : Définitions, contenus et usages. Visant à l’intégration d’un ePortfolio dans le modèle de l’apprenant d’un système d’apprentissage en ligne.”, Note de recherche LICEF2006002, LICEF, Télé-université, Montréal, 2006. [8] IMS, “IMS ePortfolio Best Practice and implementation Guide, Version 1.0 Final Specification”, IMS Global Learning Consortium, 2004. [9] ePortConsortium, Electronic Portfolio White Paper, ePortConsortium, 2003. [10] F. Lasnier, Réussir la formation par compétences, Guérin, Montréal, 2000. [11] G. Paquette, Modélisation des connaissances et des competences: Un langage graphique pour concevoir et apprendre, Presse de l’Université du Québec, Ssinte-Foy, Québec, 2002. [12] IMS, “IMS Reusable Definition of Competency or Educational Objective – Information Model, Version 1.0
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Final Specification”, IMS Global Learning Consortium, 2002. [13] C. Eyssautier-Bavay, “Le portfolio en éducation, concept et usages”, Actes du colloque TICE Méditérannée, Nice, France, novembre 2004. [14] L.-S. Vygotski, Pensée et langage, 3ème édition, La Dispute, Paris, 1934-1997. [15] C. Hansen and G. McCalla, “Active Open Learner Modelling”, Proceedings of AIED2003, 2003. [16] Viewpoint. (n.d.). WordNet® 2.0. Retrieved September 06, 2006, from Dictionary.com website: http://dictionary.reference.com/search?q=viewpoint&x=0& y=0
[17] O. Mariño, F. Rechenmann and P. Uvietta, “Multiple Perspectives and Classification mechanism in objectoriented representation”, 9th.European Conference on Artificial Intelligence ECAI, Estocolmo, 1990. [18] R. Dieng-Kuntz, O. Corby, F. Grandon, A. Giboin, J. Golebiowska, N. Matta and M. Ribière, Méthodes et outils pour la gestion des connaissances, chapitre 6: Gestion de multiples points de vue, Dunod, Paris, 2000. [19] E. De Vries and J. Baillé, Apprentissage: référents théoriques pour les EIAH. In M. GrandBastien and J.-M. Labat, Environnements informatiques pour l’apprentissage humain, Hermès/Lavoisier, Paris, pp. 27-46, 2006. [20] G. McCalla, J. Vassileva, J. Greer, and S. Bull, “Active Learner Modelling”, Proceedings of ITS 2000: Intelligent Tutoring Systems, Montréal, QC, Canada. Springer-Verlag: Berlin, Germany, June 2000, pp. 53-62.
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