Conference ICL2008
September 24 -26, 2008 Villach, Austria
Representing Knowledge of a Concept Map Assessment and Learning Environment: An Ontological Approach
Irene Kilanioti, Evangelia Gouli, Agoritsa Gogoulou, Maria Grigoriadou Department of Informatics and Telecommunications, University of Athens
Key words: assessment, feedback, concept mapping, ontologies Abstract: In this paper, a brief description of the concept mapping assessment and learning environment referred to as COMPASS is given, focusing on its main features. Exploiting the benefits of using web ontologies to represent the knowledge of the system (domain knowledge and student model), this paper describes how Semantic Web technologies can be applied to the COMPASS environment.
1 Introduction Many researchers assert that educational assessment can play a significant role in helping learners learn if it is interweaved with the teaching and learning process instead of being postponed at the end of the instruction [7]. Moreover, feedback has long been regarded as a key aspect of learning and instruction [5]. In educational settings, concept maps have become a valuable tool of a teaching, assessment and learning toolbox, as they provide an explicit and overt representation of learners’ knowledge structure, enhance learning and promote reflection, creativity and meaningful learning [6]. In this context and having as an objective to support the learning process and to assess learner’s understanding, we developed an adaptive concept mapping learning environment, referred to as COMPASS (COncept MaP ASSessment and learning environment) [2], [3]. The discriminative characteristics of COMPASS are (i) the possibility of students to work out various concept mapping activities, which employ different concept mapping tasks, (ii) the analysis of students’ map and the application of an assessment scheme for the qualitative and quantitative estimation of their knowledge, (iii) the provision of different forms of feedback and feedback components, (iv) the adaptivity of the feedback process, (v) the learner control over the feedback process, and (vi) the teacher-expert support through the CAT tool (COMPASS Authoring Tool), which enables teachers to design/author activities and feedback components, to define the assessment scheme applied and to monitor students’ progress. Current research efforts focus on ontologies and metadata standards for the web, aiming to achieve personalization and reuse of content in educational environments. In this line of research, this paper proposes an ontological approach to represent the knowledge of COMPASS, providing flexibility and adaptability of the content and interoperability among different concept mapping learning and assessment environments.
2 An Overview of COMPASS COMPASS (http://hermes.di.uoa.gr/compass) is a discipline-independent concept mapping learning environment. The domain knowledge is based on the notion of a learning goal that 1(4)
Conference ICL2008
September 24 -26, 2008 Villach, Austria
student can select. A goal corresponds to a fundamental topic of the subject matter and is further analysed to specific learning outcomes, which are realised through various learning concept mapping activities. Depending on the outcomes, the activities may employ various concept mapping tasks, which provide a different perspective of student’s understanding, such as the construction of a map, the evaluation/correction, the extension of a given map. Depending on the attributes of the activity, student’s concept map may be assessed either automatically by COMPASS or by teacher through the CAT tool. A scheme has been developed for the assessment of concept maps and subsequently for the evaluation of student’s knowledge level on the central concept of the map. The scheme adopts the relational method by examining the accuracy and completeness of the presented propositions on student’s map and taking into account the missing ones, with respect to the propositions represented on the expert map [2]. The results of the map analysis are presented to students in an appropriate form during the feedback process. The feedback in COMPASS aims to (i) inform students about their performance and their “current” state, (ii) guide and tutor students in order to identify their false beliefs, focus on specific errors, reconstruct their knowledge and achieve specific learning outcomes addressed by the activity/task, and (iii) support reflection in terms of encouraging students to “stop and think” and giving them hints on what to think about [3]. Different forms of feedback (i.e. textbased, graphical-based and dialogue-based form) are supported with respect to the addressed learning outcomes and students’ preferences and multiple Informative, Tutoring and Reflective Feedback Components (ITRFC) are available during the feedback process. The ITRFC are structured in multiple layers and their stepwise presentation supports the gradual provision of feedback and enables students to elaborate on the feedback information and return to their map in order to correct any errors. The adaptive functionality of COMPASS is reflected to the personalization of the provided feedback in order to accommodate a diversity of students’ individual characteristics and is implemented through (i) the technology of adaptive presentation that supports the provision of various alternative forms of feedback and feedback components, and (ii) the stepwise presentation of the feedback components in the dialogue-based form of feedback. Specific student’s characteristics (i.e. knowledge level, preferences, interaction behaviour), which are maintained in student model and recorded either through student’s interaction with the environment or defined by the student explicitly, are used as a source of adaptation. Moreover, COMPASS gives students the possibility to (i) personalize the feedback process by accessing and initiating/updating their student model in terms of the feedback presentation parameters, and (ii) have control over the feedback presentation process at any time during their interaction with the environment by selecting the preferred form of feedback and feedback component.
3 Using Ontologies in COMPASS Ontology is a formal specification of knowledge in a domain, which formalizes conceptualisations [4], and is one of the popular knowledge representation techniques in AI. In a simplified sense, ontology provides an extendable and shareable framework to capture the common vocabulary in a domain. It includes machine-interpretable definitions of basic concepts in the domain and the relations that exist among them. Formally, ontology consists of entities, relationships, properties, instances, functions, constraints, rules, and other inference procedures. Regarding the exploitation of ontologies in education [1], from the technological perspective, ontologies can be used for the semantic annotation of learning objects, authoring activities, and instructional activities and for the ontology-driven architectures and services, which can contribute as a mechanism of knowledge sharing, reuse and interoperability. From the application perspective, ontologies can be used as a cognitive tool for knowledge construction, externalisation, communication and assessment. 2(4)
Conference ICL2008
September 24 -26, 2008 Villach, Austria
The incorporation of ontologies mechanism can improve the current state-of-the-art in a learning and assessment environment as (i) ontologies can interrelate information about the resources that can be reused to support learning captured from various educational systems and tools, (ii) semantic annotation (based on domain ontologies) can function as a mean of relating different kinds of learning artifacts (e.g. lessons, tests, chat messages), and (iii) rules and reasoning can function as means for generating feedback out of the available (semantic) data. Thus, the incorporation of ontologies mechanism in COMPASS will provide (i) flexibility and adaptability of content, aiming at facilitating its reusability and providing support for personalized learning, (ii) interoperability among COMPASS and other concept mapping systems/tools to the level of activities, assessment of concept maps and feedback provided, and (iii) modularity, since different kinds of learning related ontologies can be used (student model ontology, content knowledge ontology, domain ontologies).
Figure 1 The Content Knowledge Ontology for COMPASS
Figure 2 The Data Storage of COMPASS using ontologies
Our proposed architecture is based on the notion of ontologies and in particular application ontologies to both represent the knowledge about the student model and store explicit metadata modeling knowledge about the educational content of the system, called Student Ontology (SO) and Content Knowledge Ontology (CKO) respectively. We also used a domain ontology to represent the domain being learned, called Domain Ontology (DO). The DO classes concern learning goals, concept mapping activities and feedback components. The CKO depicted in Figure 1 describes the actual pieces of educational content and includes the rules to correctly assemble them (e.g. prerequisite rules defined as properties of the DO classes). Qualified links, such as apply, defines, part of, relate CKO elements to DO ones indicating how each piece of the educational content maps to DO classes. The SO models the main properties that characterize the student’s model (e.g. knowledge level on the underlying learning goals, preferences, interaction behaviour). In Figure 2, a representation of the knowledge (data storage) of COMPASS is given, following the abovementioned ontologies. 3(4)
Conference ICL2008
September 24 -26, 2008 Villach, Austria
During the authoring process with the CAT tool, the author can consult the DO and the CKO to be aware of existing learning objects to eventually reuse them. The CKO is being populated through an Automatic Metadata Generation mechanism that converts the xml/html file received from CAT to the appropriate RDF file to represent Learning Objects Metadata (LOM) (i.e. LOM is a metadata standard to be used in descriptions concerning objects for learning purposes). Each time new content is authored, the Automatic Metadata Generation wrapper generates its fundamental metadata as RDF descriptions that are instances of the CKO. The student’s interaction with the environment updates the SO (that is, generates automatically instances of SO).
4 Summary and Further Research Towards the direction of using ontologies, this paper proposed an approach for incorporating ontologies in the COMPASS environment to represent the domain knowledge and the student model. Our near future plans include the redesign of COMPASS functionalities in order to comply with the proposed ontological approach.
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Dicheva, D.; Sosnovsky, S.; Gavrilova, T.; Brusilovsky, P. : Ontological Web Portal for Educational Ontologies. Workshop on Semnatic Web in E-Learning, 12th International Conference on Artificial Intelligence in Education, Amsterdam, The Netherlands, 2005. Gouli, E.; Gogoulou, A.; Papanikolaou, K.; Grigoriadou, M.: Evaluating learner’s knowledge level on concept mapping tasks. In P. Goodyear, D. Sampson, D. Yang, Kinshuk, T. Okamoto, R. Hartley, & N-S. Chen (Eds.), Proceedings of the 5th IEEE International Conference on Advanced Learning Technologies (ICALT 2005), Kaohsiung, Taiwan, 424-428, 2005. Gouli, E.; Gogoulou, A. ; Tsakostas, C. ; Grigoriadou, M. : How COMPASS supports multi-feedback forms and components adapted to learner’s characteristics. In A. Cañas, & J. Novak (Eds.), Concept Maps: Theory, Methodology, Technology, Proceedings of the Second International Conference on Concept Mapping, San José, Costa Rica, Vol.1, 255-262, 2006. Gruber. T.: A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition, 5(2):199-200, 1993. Mory, E.: Feedback research. In D. H. Jonassen (Ed.), Handbook of research for educational communications and technology. New York: Simon & Schuster Maxmillan, 919-956, 1996. Novak, J.; Gowin, B.: Learning How to Learn. New York: Cambridge University Press, 1984. Pellegrino, J.; Chudowsky, N.; Glaser, R. (eds): Knowing what students know: The Science and Design of Educational Assessment. National Academy of Sciences. Washington DC: National Academy Press, 2001.
Author(s): Irene, Kilanioti, Phd Student,
[email protected] Evangelia, Gouli, Dr., Research Fellow,
[email protected] Agoritsa, Gogoulou, Dr., Research Fellow,
[email protected] Maria, Grigoriadou, Associate Professor,
[email protected] University of Athens, Department of Informatics and Telecommunications Panepistimiopolis, TYPA Buildings, GR 15771 Athens 4(4)
