This study aims at modeling and visualizing students' behavior in a self- regulated and unguided learning environment with a focus on learning progression. Since the modeling approach is process-oriented and does not depend on specific mastery learning criteria, this paper provides a novel way to identify wheel-spinning in self-regulated learning solely based on activity monitoring. The study investigates the free and unsupervised engagement of junior high school students in solving mathematics exercises during summer vacation. During this period, a pool of exercises was provided on the LEAF online learning platform. Additionally, the students receive adaptive exercise recommendations as an add-on. Guided by the basic idea of wheel- spinning as persistent engagement without learning progression, we have designed a mathematical model and a graphical representation to capture and gauge the individual learning progression. Based on an expert questionnaire survey, we considered how this novel representation can serve as a basis to analytically characterize learning progression and specifically to identify wheel-spinning.

Work-process-orientation is a new approach to voca¬tional education and training (VET). The content and structure of a work-process-oriented curriculum (WPOC) are derived from a typical professional task in an occupation and based on work processes. Existing approaches and learning platforms relevant to WPOC provide insufficient support. This paper proposes a technical approach to systematically supporting learning activities in a work context compatible with WPOC through integrating a learning design platform with mixed-reality environments. Through implementation and exemplary usage of the platform, the feasibility of this technical approach and its usability have been demonstrated.

Digitization in vocational education and training (VET) offers new opportunities for integrating work processes and background knowledge through interactive media. This involves the design, testing and evaluation of innovative means of didactic and technical support. In the project “Digitized support for competence development in the workplace”, this task is approached from a combined psychological and computer science perspective. This paper reports on one usage scenario from the first year of the project examining how to embed learning videos in VET. The results include new findings on video-based learning, and inform the design and implementation of a prototypical online learning platform.

Establishing small learning groups in online courses is a possible way to foster collaborative knowledge building in an engaging and effective learning community. To enable group activities it is not enough to design collaborative tasks and to provide collaboration tools for online scenarios. Collaboration in such learning groups is prone to fail or even not to be initiated without explicit guidance. In the target situations, interventions and guiding mechanisms have to scale with a growing number of course participants. To achieve this under privacy constraints, we aim at identifying target indicators for well-functioning group work that do not rely on any kind of information about individual learners.

To conduct scientific experiments is a central aspect in science education in secondary schools. Online laboratories overcome a variety of deficits and obstacles that complicate in situ experiments, particularly regarding accessibility, availability, financial costs and preparation time. However, such a computer-supported learning approach still demands for motivating and playful scenarios to catch and engage students with a lower affinity to sciences. This gap is closed by "Fake or Real"-scenarios, in which students verify or falsify the authenticity of viral videos from the internet. We developed a web-based online lab along with inquiry-based learning scenarios for the (interactive) analysis of such videos by extracting physical parameters according to corresponding hypotheses. The work has been evaluated in a classroom experiment including 17 high school students in an interdisciplinary lesson.

Web-based learning environments such as the Go-Lab portal facilitate the structuring and scaffolding of inquiry processes and enable learners to create various types of knowledge artefacts (texts, concept maps, hypotheses). In this context, we have introduced semantic technologies to extract key concepts from heterogeneous learner-generated artefacts. Based on this approach, we propose an algorithm and a software application that forms heterogeneous groups. Semantic group formation creates groupings based on semantic diversity representing students' complementarity in knowledge. Finally, we compare this approach to a prior score-based approach.

In this integrated study of dynamics in MOOCs discussion forums, we analyze the interplay of temporal patterns, discussion content, and the social structure emerging from the communication using mixed methods. A special focus is on the yet under-explored aspect of time dynamics and influence of the course structure on forum participation. Our analyses show dependencies between the course structure (video opening time and assignment deadlines) and the over-all forum activity whereas such a clear link could only be partially observed considering the discussion content. For analyzing the social dimension we apply role modeling techniques from social network analysis. While the types of user roles based on connection patterns are relatively stable over time, the high fluctuation of active contributors lead to frequent changes from active to passive roles during the course. However, while most users do not create many social connections they can play an important role in the content dimension triggering discussions on the course subject. Finally, we show that forum activity level can be predicted one week in advance based on the course structure, forum activity history and attributes of the communication network which enables identification of periods when increased tutor supports in the forum is necessary.

Explicit visual representations of domain knowledge have the potential to support students engaged in scientific inquiry learning activities on an epistemic level. This can be facilitated using computational methods for the extraction of concepts from student generated knowledge artefacts such as hypotheses, concept maps, or wiki articles. We propose an application of this approach in the context of inquiry learning with online science laboratories. As a cognitive awareness tool, the "concept cloud" presents domain concepts and key phrases to the learners in order to help them reflect on their own learning and knowledge building. As part of a learning analytics toolset, the concept cloud also supports teachers in supervising their students' knowledge building from an epistemic perspective. The approach has been tested in a classroom scenario with 84 secondary high school students.

The recently finished EU project JuxtaLearn aimed at supporting students’ learning of STEM subjects through the creation, exchange and discussion of learner-made videos. The approach is based on an eight-stage activity cycle in the beginning of which teachers identify specific “stumbling blocks” for a given theme (or “tricky topic”). In JuxtaLearn, video comments were analyzed to extract information on the learners’ acquisition and understanding of domain concepts, especially to detect problems and misconceptions. These analyses were based on mapping texts to networks of concepts (“network-text analysis”) as a basis for further processing. In this article we use data collected from recent field trials to shed light on what is actually discussed when students share their own videos in science domains. Would the aspect of video-making dominate over activities related to a deepening of domain understanding? Our findings indicate that there are different ways of balancing both aspects and interventions will be needed to bring forth the desired blend.

Aiming at facilitating STEM learning through video-making, the JuxtaLearn project supports teachers in defining their own domain taxonomies as semantic building blocks for various learning activities. This paper reports on an evaluation with 17 teachers using a semantic recommender system for taxonomy building and lesson planning. Our results indicate that the system is perceived as supportive, but it also reveals problems caused by teachers’ individual preferences.

This paper describes the analysis of the social and semantic structure of discussion forums in massive open online courses (MOOCs) in terms of information exchange and user roles. To that end, we analyse a network of forum users based on information-giving relations extracted from the forum data. Connection patterns that appear in the information exchange network of forum users are used to define specific user roles in a social context. Semantic roles are derived by identifying thematic areas in which an actor seeks for information (problem areas) and the areas of interest in which an actor provides information to others (expertise). The interplay of social and semantic roles is analysed using a socio-semantic blockmodelling approach. The results show that social and semantic roles are not strongly interdependent. This indicates that communication patterns and interests of users develop simultaneously only to a moderate extent. In addition to the case study, the methodological contribution is in combining traditional blockmodelling with semantic information to characterise participant roles.

There is an underexploited potential in enhancing massive online learning courses through small-group learning activities. Size and diversity allow for optimizing group composition in small-group tasks. The purpose of this paper was to investigate how groups formed based on learner behavior affect productivity of students in a small-group task. Students classified as high, average and low were randomly assigned to homogeneous or heterogeneous groups. Results indicate that overall, heterogeneous groups were either similarly or a bit more productive than homogeneous groups. Yet, we found that homogeneous groups classified as high-level were as or more than heterogeneous groups. However, heterogeneous groups were still more productive than homogeneous-average and homogeneous-low groups suggesting heterogeneous groups are the best choice for the entire community. Students classified as low-level were more productive in homogeneous groups, suggesting that grouping less active students together, makes social loafing more difficult and students participate more.

In this demo paper we present a new visualization technique for dynamic networks. It displays the time slices of the dynamic network using two dimensional graph layouting algorithms and stacks these in the third dimension to show the development over time. The visualization ensures that the same node always has the same position in each time slice so that it is easy to follow its development. It also allows filtering data and influencing node appearance based on properties. Additionally we offer a two dimensional comparison view for two time slices which highlights changes in graph structure and (if available) in measures of nodes. The presented visualization technique is implemented using web technology and is available in a web-based analytics workbench. We demonstrate the benefits of these techniques by an analysis of a data set from a learning community.

This work explores methods to investigate the structure of knowledge exchange in discussion forums in massive open online courses (MOOCs) explicitly taking into account changing patterns over time. Various aspects of forum analysis combining different approaches are exemplified with a case of forum discussions from a Coursera MOOC.

In this paper, we propose a mathematical model to measure the visual stability of dynamic graph drawings. Our approach was validated through a study, which combined the use of questionnaires and an eye-tracking device. The participants of the study had to track members of a software development community over five periods of time in three different dynamic graph drawings. The results suggest that dynamic graph drawings making use of fixed positions are more efficient in the visual search but are limited in the recognition of single elements. On the other hand, dynamic graph drawings with the minimal changes or a constant structure improve the recognition of single elements but lose efficiency in the visual search.

In this paper we investigate patterns of resource usage for exam preparation based on a resource intensive blended learning course. To this end, we analyzed a blended learning, online course facilitated by Moodle. During the course, the students had to work individually and in teams. Furthermore, they were given access to a broad spectrum of learning resources such as videos, slides, wiki articles and quizzes. The logfiles obtained from Moodle were further processed and analyzed. Our analysis approach is based on association rule as well as sequential pattern mining. The results indicate that students’ activity with respect to resource usage follows common patterns during exam preparation either on the individual or the group level. These patterns also relate to the performance of students and to reflect their prior collaborative experience.

Problem-based learning (PBL) can be organized and conducted in a number of ways. Building a PBL application to support various PBL forms directly is difficult because the scope of variability cannot be completely known and there is a high cost in terms of time and efforts incurred. Existing PBL applications are developed usually to support a specific form of PBL. In this paper we propose a model-driven approach (MDA) to the development of an adaptive PBL application. We apply model-driven principles to enable the teacher to represent a PBL script in a PBL scripting language as a formal model and then use the model at run-time for managing the executions of the adaptation at a high level. As a consequence, the functions and the user interfaces of the PBL application can be adjusted according to the role of the users, the phases and the activities of a PBL process. The users of the PBL application, especially those who have no comprehensive knowledge about PBL, can be guided and constrained to do right thing at right time following a well-known PBL model or a best practice.

In this study, we explore the potential of (semi-) automated artifact analysis to identify and characterize students' comprehension problems around knowledge artifacts in the form of videos available on a web platform. Using the comments assigned to these learning videos as sources, we have applied available and tailor-made methods of text analysis to identify potential problems of understanding. In particular, we have used signal words and their relationship to domain concepts to indicate missing pre-knowledge or false beliefs. In future work, these results will be used to support monitoring processes for increasing conceptual awareness and supporting conceptual change.

In this paper we present a classroom learning scenario for assembling computers. This scenario is designed for computer science classes and teaches the functioning of a computer by relating the theoretical concepts to real-world technology with hands-on experience. The students are guided through a scenario using the Mobilogue app on a smartphone, which involves scanning QR codes attached to computer parts, reading background information, watching instructional videos and assembling the computer step by step. We report on the implementation of the scenario in two high school level classes and present evaluations results focused on knowledge gain from the presented scenario.

Computer programs are a specific type of knowledge artefacts that result from a creative process under strong formal restrictions. From an educational perspective, it has been argued that programming supports intellectual development and knowledge building. In this paper, we give a short overview of a system created to automatically detect the creativity of solutions to programming exercises that address general mathematical and algorithmic skills. A first step to make these artefacts susceptible to automatic analysis was the definition a descriptive feature set that captures both structural and procedural aspects of each solution. Secondly, machine learning techniques have been used to form higher-level metrics simulating expert judgments on a given set of solutions. It turned out that expert judgments of program creativity differ considerably and systematically. This also led to a classification of the experts.

Technology supported learning is nowadays often based on heterogeneous environments that encompass not only one application and also possibly involve different devices. This creates specific challenges for data analysis and thus for learning analytics. In this paper, we propose a framework to create reusable learning analytics components that are portable to different target platforms. In this approach, the logic of each analysis component is specified in a separate web-based visual environment (or "workbench") from where it is later exported to the target environments form of a gadget-based dashboard. We demonstrate this mechanism in the context of the Go-Lab portal for accessing remote laboratories in STEM learning scenarios. An example shows how such analytics gadgets can be used to support collaboration inside the classroom.

Problem-based learning (PBL) can be organized and conducted in a variety of forms. By adopting a Domain-Specific Modeling Language (DSML) approach we have developed a PBL scripting language, which provides natural concepts that teachers can understand and use in practical PBL. Based on this PBL scripting language, a web-based PBL authoring tool has been developed, which enables teachers to develop their own PBL strategies as PBL scripts.

This paper presents a web based serious game for medical students, which supports the training of patient-centered medical interviews. Phases of immersion (role playing) and reflection are differentiated to facilitate change of perspectives that is considered to be conducive for learning. Reflection is supported by the recording of the role play, which is enhanced by automated analysis results regarding the communication behavior of the player based on models of doctor-patient communication as well as general communication. The playability of this game was evaluated in a study with medical students.

The ongoing EU project JuxtaLearn aims at facilitating the acquisition of science concepts through the creation and sharing of videos on the part of the learners. For the specific learning targets threshold concepts are specified as key elements of knowledge. Content analysis techniques are used to extract learners’ concepts manifested in textual artifacts and to contrast these with the anticipated domain concepts (represented as ontology). Deviations between student concepts and the ontology can indicate problems of understanding, which may trigger a revision of the original curriculum. In two studies we explore the potential of (semi-)automated artifact analysis to identify and characterize the students’ comprehension problems around knowledge artifacts. In the first study, protocols from a “flipped classroom” style teacher-student workshop are analyzed. The second study analyses comments to videos from educational video platforms. Here, we have applied text analysis methods to identify potential problems of understanding. Also, we have used “signal words” and their relations to domain concepts to highlight potential information needs and problems of understanding.

Creativity techniques gain importance in education and business areas day by day. Beyond the well-known brainstorming, which focuses on divergent thinking, lateral thinking will encourage the individual to regard the situation from a variety of perspectives by breaking old mind patterns and forming new connections and perceptions. Examples like „Six Thinking Hats“ or „(Walt) Disney Method“ consist of group discussions, where specific roles are assigned to the participants to enforce a discourse with different perspectives. Electronic group discussion systems can compensate the deficits of verbal (face-to-face) discussions through motivating passive discussants to participate. Furthermore, a system can provide a persistent logging of contributions and an explicit representation of a contribution according to the perspective of the participant. We present a novel approach, which allows both authoring and performing such multi-perspective creativity methods. In addition, the participant’s user interface is optimized for mobile devices. Finally we show first results of usability evaluations covering authoring and performing of a created method.

Research supervision is an important type of support for advanced students when engaged in study projects or in writing their final theses. One of the most common complaints from research students is erratic or infrequent contact with supervisors, who might be too busy with other responsibilities or are not present frequently enough . High proliferation of mobile phones(i.e. 'mobile-rich') but no computer prevalence (i.e. 'computer-poor') in African countries calls for using mobile technologies to address this challenge. However, limitations of mobile devices (such as usage cost, memory capacity and small screen) are some of the barriers for mobile learning adoption. In this paper, we combine mobile learning with OER and Cloud Computing Services to enhance supervisors’ availability to their research students, who are in 'mobile-rich' but 'computer-poor ' learning settings typical for African universities.

As problem-based learning (PBL) is becoming more and more popular, there is also a growing interest in developing and using technologies in the implementation of PBL. However, teachers may have difficulties to design a pedagogically high-quality and technically executable, online or blended PBL process on their own, because they lack appropriate expertise in learning theories and design methods as well as a deeper understanding of the potential affordances of technologies. From this premise, we are committed to developing and testing methods and tools to support the design and delivery of online or hybrid PBL processes with high flexibility and a low threshold of usage requirements. As a first milestone towards this goal we have developed a web-based PBL authoring tool for facilitating teachers to design, represent, understand, communicate, customize and reuse online or blended PBL processes. This paper presents a technical approach to the PBL authoring tool and focuses on supporting the representation and management of PBL scripts, computational descriptions of PBL process. In comparison with other tools and technical approaches, it is concluded that a combined use of semi-structured data management and a unified data format appears to be a promising approach to effectively and efficiently support the representation and management of PBL scripts.

This paper presents an analysis of resource access patterns in a recently conducted master level university course. The specialty of the course was that it followed a new teaching approach by providing additional learning resources such as wikis, self-tests and videos. To gain deeper insights into the usage of the provided learning material we have built dynamic bipartite student -- resource networks based on event logs of resource access. These networks are analysed using methods adapted from social network analysis. In particular we uncover bipartite clusters of students and resources in those networks and propose a method to identify patterns and traces of their evolution over time.

The focus of this workshop is on the potential benefits and challenges of using specific computational methods to analyze interactions in networked learning environments, particularly with respect to integrating multiple analytic approaches towards understanding learning at multiple levels of agency, from individual to collective. The workshop is designed for researchers interested in analytical studies of collaborative and networked learning in socio-technical networks, using data-intensive computational methods of analysis (including social-network analysis, log-file analysis, information extraction and data mining). The workshop may also be of interest to pedagogical professionals and educational decision makers who want to evaluate the potential of learning analytics techniques to better inform their decisions regarding learning in technology-rich environments.

In this paper we introduce the concept of a web-based analytics workbench to support researchers of social networks in their analytic processes. Making explicit these processes allows for sound design, re-use, and automated execution using an authoring system for visual representations of these analytic workflows. The workbench is implemented according to a flexible technical framework in which external and newly-defined analytic components can be integrated and used in conjunction with other analytic components. As a showcase we discuss a complex analytic process.

CloudServices like Google Drive, Brainstormer, Doodle are meanwhile frequently used as tools for learning in various contexts. They provide storage facilities, production tools and particularly also coordination support. The management of these heterogeneous tools is a challenge for the individual users as well as for the usage in groups. This paper presents a mobile application to support the learners in the formation of informallearninggroups and integrates heterogeneous cloudservices to supportgroupformation and further group work in a campus environment. Furthermore, this paper tackles the ambiguity of the term cloud application and tries to provide a definition and discusses the process of bringing the Brainstormer Web application into the cloud for integration with the mobile application.

University freshmen have to cope with complex and heterogeneous information infrastructures typically found in nowadays universities. Usually learning management systems like Moodle or Blackboard are applied for lectures. Additionally, Cloud Services like Google Drive, Brainstormer, and Doodle are meanwhile frequently used as tools for learning in various contexts. They support storage, content production and particularly also coordination. The management of these heterogeneous tools is a challenge for the individual users as well as for the usage in groups. This paper presents a mobile application to support the learners in the formation of informal learning groups and integrates heterogeneous cloud services to support group formation and further group work in a campus environment.

Mobilogue is a tool to support educators and students in authoring and deploying learning support with location awareness and guidance to mobile devices. The application area of the framework covers informal learning settings like field trips, museum visits as well as formal classroom settings. The focus of the framework is on the simplicity and flexibility of the domain independent content authoring and content deployment. We present an authoring tool that uses a workflow-related, graph-based paradigm to model and author a path across different locations. Locations relate to physical places or artifacts through QR codes and provide supportive information. The guidance takes place by identifying the user’s location by scanning the QR codes and visualizing the appropriate information on the smartphone. Finally we describe possible scenarios for such informal learning settings and report on an evaluation of one scenario authored by students for a museum.

This paper provides an introduction to the scientometric method of main path analysis and its application to detecting idea flows in an online learning community using data from Wikiversity. We see this as a step forward in adapting and adopting network analysis techniques for analyzing the evolution of artifacts in knowledge building communities. The analysis steps are presented in detail including the description of a tool environment ("workbench") designed for flexible use by non-computer experts. Through the definition of directed acyclic graphs the meaningful interconnectedness of learning resources is made accessible to analysis in consideration of the temporal sequence of their creation during a collaborative process. The potential of the method is elaborated for analyzing the overall learning process of a community as well as the individual contributions of the participants.

This paper introduces an agglomerative method for detecting cohesive subgroups in networks based on geodesic distance. The algorithm starts with a set of nodes as "seed". Beginning with the seed nodes as initial clusters, the clusters grow by incorporating more nodes successively based on minimal average distance to the current members of the cluster as a criterion for cluster extension. This approach is combined with an optimization step to achieve high quality performance on subgroup detection. The resulting method for detecting discrepant cohesive subgroups has been tested on artificial benchmark graphs as well as real-world networks.

More and more communities use internet based services and infrastructure for communication and collaboration. All these activities leave digital traces that are of interest for research as real world data sources that can be processed automatically or semi-automatically. Since productive online communities (such as open source developer teams) tend to support the establishment of ties between actors who work on or communicate about the same or similar objects, social network analysis is a frequently used research methodology in this field. A typical application of SNA techniques is the detection of cohesive subgroups of actors (also called "community detection"). A relatively new method for detecting cohesive subgroups is the Clique Percolation Method (CPM), which allows for detecting overlapping subgroups. We have used CPM to analyze data from some open source developer communities (mailing lists and log files) and have compared the results for varied time windows of measurement. The influence of the time span of data capturing/aggregation can be compared to photography: A certain minimal window size is needed to get a clear image with enough "light" (i.e. dense enough interaction data), whereas for very long time spans the image will be blurred because subgroup membership will indeed change during the time span (corresponding to a moving target). In this sense, our target parameter is "resolution" of subgroup structures. We have identified several indicators for good resolution. Applying these indicators to the different CPM results shows the best resolution is a time span of around 2-3 months. In general, this value will vary for different types of communities with different communication frequency and behavior. Following our findings, an explicit analysis and comparison of the influence of time window for different communities may be used to better adjust analysis techniques for the communities at hand.

This paper describes the rationale behind a workshop on using data-intensive computational methods of analysis for empirical-analytical studies of collaborative and networked learning, with a particular focus on how learning takes place in the technically-mediated interplay between individual, small group and collective levels of agency. This workshop is primarily designed for researchers interested in empirical-analytical studies using data-intensive computational methods of analysis (including social-network analysis, log-file analysis, data mining, video analysis).

This paper presents a flexible approach to model and support inquiry learning processes in complex domains centered around emerging learning objects. It describes our work on applying educational process modeling techniques to provide an agenda-based tool for metacognitive scaffolding that supports students in regulative activities. A prototype has been developed as a pedagogical agent. Rather than presenting the suggested learning sequence directly, the pedagogical agent helps the students to reflect on and possibly re-plan their learning processes by monitoring and analyzing students’ actions and by using a predefined process model. The pedagogical agent has been tested and the initial test results demonstrate the technical feasibility of this approach.

Self-directed learning with learning management systems can be intelligently supported and enriched using available log data in combination with detailed competence ontologies. The approach described here implements a mechanism to adaptively generate quizzes for self-assessment in a Moodle environment. The underlying agent architecture uses a tuple space in the role of a blackboard. The approach has been worked out with a distance course on Genetics.

In this paper, we present work in progress on developing and integrating a mobile application for collecting numerical and multimedia data into a learning environment called SCY-Lab. This learning environment is currently being developed within the European SCY project on collaborative inquiry learning. In SCY, collaboration is centered around the sharing of "emerging learning objects" (ELOs) produced by the students themselves. The aim of this paper is to show how the ELO centered approach of SCY has been used to integrate mobile scenarios into the SCY system.

Skills and competence requirements in the IT and media sector are changing dynamically at a high rate. This makes the “manual” adjustment of domain ontologies for this area hardly feasible, so that there is a need for automatic or semi-automatic techniques to update such knowledge bases. Several data mining techniques have been applied to different collections of job offers from this field to test and exemplify the feasibility of this approach. The results are encouraging and will be used to support decisions in professional development.

Designing a computer-supported learning scenario involving a constructivist approach of learning lays on a paradox. On the one hand, learning flows must be precisely described - including role distribution, required resources, tools, and scaffolds - to be realized in computer-supported environments. On the other hand, a fine-grained formalization of learning flows diverges from the constructivist notion of learning that learners are responsible for their knowledge (co-)construction. This paper draws upon the fundaments of a new concept so called ldquolearning activity spacerdquo (LAS) aiming at realizing some necessary flexibility when designing learning scenarios. LAS is the basis of a graphical scenario modeling language intelligible for non-computer scientists but still rich enough in detail to describe a large set of computer-supported learning scenarios.

A crucial challenge for improving EMLs is to provide an intuitive notation to support educational practitioners to not only understand, but also describe a large number of flexible scenarios themselves. We present here the general outline of a graphical modeling language based on the concept of learning activity space (LAS) and its related editor so-called SCY-SE. The design stage of learning computer-supported scenarios can be facilitated by the use of LAS arrangements as improved in the context of an interdisciplinary European project named SCY (Science Created by You).

This paper presents an integration architecture and a technical framework for moderation of e-discussions, a specific type of scenario for collaborative learning. The approach for monitoring and moderating discussions is supported at a generic level and defines interfaces to integrate diverse discussion environments smoothly into the generic framework. The usage of the developed monitoring and moderation system has been tested practically with two different stand-alone discussion environments and first empirical results of the moderation approach have been collected. We conclude with future work on the framework system and additional discussion tools to be integrated into the architecture.

In the context of the CIEL activity within the European network of excellence kaleidoscope, a generic software architecture has been developed to integrate various heterogeneous applications for inquiry learning, including the definition of relevant data formats and interfaces. The general aim of this architecture is to provide a common software platform for various learning applications, facilitating interoperability by means of quasi-synchronous data exchange. Dynamically created learning objects comply with the LOM standard, thus enabling the re-use of these product in follow-up learning activities.

CIEL aims at integrating tools and scenarios for open types of learning in which learners engage in larger, realistic tasks, such as scientific inquiry or engineering. In these kinds of learning, a pivotal place is taken by the products that learners create during their work, such as artifacts, models, hypotheses, sets of data etc. By redefining the concept of learning object to also include these kinds of products, and by defining standards and an ontology for these kinds of learning objects, CIEL enables semantic and technical integration of different learning environments, opening the possibility for supporting larger, more realistic scenarios for collaborative inquiry and experiential learning. A first proof of concept in the domain of sampling is described.

To support the development of distributed learning environments with components programmed in different languages a blackboard architecture based on tuple spaces is proposed. The specific implementation in terms of the "Colmid" middleware supports inter-language communication by adding a Prolog interface to the Java based TSpaces platform. This approach is exemplified by a collaborative discussion environment coupled with an action analyzer written in Prolog.

Software for supporting pupils in learning reading and writing skills is very often less productive than expected. A main reason for this is that pupils who are not able to read and write do not succeed in using complex software environments which are furthermore very often designed like old-fashioned tutoring systems. Taking the results from the EU founded project NIMIS as a starting point for a Ph.D. thesis (A. Lingnau, 2005), in this paper an approach to analyse writing products of German first graders who use a phonetic based method to learn reading and writing skills was presented. From these analysis results a learner model is build which maps the knowledge level a child has reached in the process of phonetic writing

Recently many car driving simulators have been developed and used for educational purposes. They can provide special training opportunities that are not available frequently in reality. However, currently existing simulators often rely on predefined situations and scenarios. Training students to deal with spontaneously occurring dangerous traffic situations is difficult when using hard wired "emergency" situations that occur in a predictable manner. In this paper we present a new approach to provide special learning opportunities. We adopt intelligent agent technologies to develop the "problem creator", a pedagogical agent who can deliberately cause dangerous situations. Introducing the problem creator into our collaborative 3D virtual car driving environment makes it unpredictable when, where, and what type of abnormal situations the students will be confronted with. These irregularly occurring challenges model the reality of car driving well.

In this paper we present a communication and discussion toolkit based on sending short messages designed for use in schools. This toolkit is the result of a student's project at the University of Duisburg-Essen in collaboration with a local secondary school. Our approach uses PDAs in a wireless network to build an environment which emulates sending of short messages with mobile phones. The messages created by the students are collected in a database and establish a base for a discussion and analysis later on using Cool Modes, a graph based modeling and discussion system.

Today's learning and modeling environments mostly provide support for storing and presenting only results of learning and modeling processes, but not for the process itself. Since self-reflection, assessment, authoring and research are highly dependent on reporting this process information properly, we propose an intelligent approach for generating reports automatically based on the analysis of learning protocols.

The goal of this workshop is to discuss different facets of computer-based modelling tools and processes supported by these tools. This includes discussion of various types of modeling, representations of models, the role of visualizations and of executable models as well as intelligent support for the modeling process, reporting and documenting the process in single user environments and in collaborative, co-constructive environments.

The astronomy domain provides rich opportunities for learning about natural phenomena. It can involve and motivate a variety of mathematical and physical knowledge and skills. However it is difficult to connect astronomic observations to modelling and calculation tools and to embed them into educational scenarios. It is particularly this challenge which is focused in this paper. Concretely, we build on an existing collaborative modelling framework (Cool Modes) and extend it with specific representations to support learning activities in astronomy. A first field test has been conducted with these extensions.

We present an approach of enriching grown structures of teaching in German schools with innovative technology and collaborative software tools. Two applications for collaborative modelling and mind mapping will be introduced. Together with a community of secondary school teachers we have elaborated classroom experiments which give an added value but without redefining well suited pedagogic methods or changing the learning matters. We will present different experiences made by teachers and researchers in the domains of mathematics, biology and German language in secondary schools. We have found out that not only are teachers in science interested in computerised learning scenarios but there are several premises for a successful transfer of technology into schools.

A flexible communication model for multi-user interfaces is presented. It allows for coupling arbitrary user interface objects between heterogeneous applications dynamically. When coupled, UI objects are synchronized by broadcasting events and re-executing the corresponding actions in the different application environments. To be coupled, objects have to be compatible, but not necessarily identical. The communication mechanism is based on a centralized server. In addition to multiplexing callbacks, it also handles arbitrary remote procedure calls in a standardized way, thus allowing the transfer of internal state information between applications. Our communication mechanism is implemented as a set of primitives that extend an OSF/Motif-based UI toolbox library. It can be easily used to develop multi-user interfaces in very much the same way as single-user applications, or to extend single-user applications to multi-user ones.>

S.173-180

The EXPRESS system has been designed and implemented in order to explore methods for user assistance in accessing complexly structured factual databases, e.g. relational product databases. Terminological support in this area has to take into account that different controlled vocabularies may be used in a variety of attributes spread over several relations. In our approach, traditional thesaurus structures are extended in order to cope with these problems and to encode further domain-specific knowledge. User support in query reformulation is based on this enriched thesaurus as well as on the local evaluation of the retrieved data sets. Concepts for the representation of retrieval strategies in the form of plans and their potential use in future systems are discussed.

No abstract available.

In order to be able to show context-dependent responses to the user's actual needs, adaptive systems have to be provided with models of possible task contexts. Existing methods for the representation of tasks in HCI are insufficient for this purpose as they do not support task-oriented parsing (i.e. analysing the input stream in terms of higher level task units). This paper presents a Prolog implementation of a task-oriented parser (+ generator) based on a grammar notation called LEXITAS. As an application, an online coach for a UNIX-like file management system is described. Further applications, such as automated macro detection from given interaction protocols, are discussed.

For a Direct Manipulation interface, transfer of skill between text and graphics editing tasks has been investigated. A learning experiment has been carried out with two groups of novice users starting with a series of sessions in one task domain and then switching over to the other domain. The empirical results are discussed in the framework of the “cognitive complexity” theory of Polson and Kieras.