KM and WEB 2.0 methods for project-based learning. MESHAT : a monitoring and experience sharing tool

Our work aims at studying tools offered to learners and tutors involved in face-to-face or blended project-based learning activities. To understand better the needs and expectations of each actor, we are especially interested in the specific case of project management training. The results of a course observation show that the lack of monitoring and expertise transfer tools involves important dysfunctions in the course organisation and therefore dissatisfaction for tutors and students (in particular about the acquisition of knowledge and expertise). So as to solve this problem, we propose a personalised platform (according to the actor: project group, student or tutor), which gives information to monitor activities and supports the acquisition and transfer of expertise. This platform is based on Knowledge Management (KM) and Web 2.0 concepts to support the dynamic building of knowledge. KM is used to define the learning process (based on the experiential learning theory) and the way the individual knowledge building is monitored (based on metacognitive concepts). Web 2.0 is used to define the way the experience is shared. We make the hypothesis that this approach improves the acquisition of complex skills (e.g. management, communication and collaboration), which requires a behavioural evolution. We aim at making the students become able 'to learn to learn' and evolve according to contexts. We facilitate their ability to have a critical analysis of their actions according to the situations they encounter.Comment: arXiv admin note: substantial text overlap with arXiv:0911.031

Voices' inter-animation detection with ReaderBench. Modelling and assessing polyphony in CSCL chats as voice synergy

International audienceStarting from dialogism in which every act is perceived as a dialogue, we shift the perspective towards multi-participant chat conversations from Computer Supported Collaborative Learning in which ideas, points of view or more generally put voices interact, inter-animate and generate the context of a conversation. Within this perspective of discourse analysis, we introduce an implemented framework, ReaderBench, for modeling and automatically evaluating polyphony that emerges as an overlap or synergy of voices. Moreover, multiple evaluation factors were analyzed for quantifying the importance of a voice and various functions were experimented to best reflect the synergic effect of co- occurring voices for modeling the underlying discourse structure

Voices' inter-animation detection with ReaderBench. Modelling and assessing polyphony in CSCL chats as voice synergy

International audienceStarting from dialogism in which every act is perceived as a dialogue, we shift the perspective towards multi-participant chat conversations from Computer Supported Collaborative Learning in which ideas, points of view or more generally put voices interact, inter-animate and generate the context of a conversation. Within this perspective of discourse analysis, we introduce an implemented framework, ReaderBench, for modeling and automatically evaluating polyphony that emerges as an overlap or synergy of voices. Moreover, multiple evaluation factors were analyzed for quantifying the importance of a voice and various functions were experimented to best reflect the synergic effect of co- occurring voices for modeling the underlying discourse structure

Enhancing Programming Learning with AI-Generated Contextual Examples in Digital Creativity

Programming concepts are challenging for new learners to grasp. This is especially the case for creative arts students who are typically unfamiliar with computing concepts and the associated vocabulary at enrolment. One means to enhance their learning is to situate examples in a relatable disciplinary context and to adapt learning material accordingly. However, this can be onerous and time-consuming to prepare; particularly in diverse modules that include learners from a wide range of different disciplines. This position paper proposes the use of large language models to automate tailoring the content of adaptive hypermedia systems such as personalised wikis. These tools can re-situate examples into many contexts that learners are already familiar with. A pilot study using ChatGPT (using GPT-4) for a first-stage undergraduate Digital Creativity module is presented. Generative artificial intelligence changes the examples used to illustrate programming concepts according to a student’s course. These examples are evaluated by academic colleagues drawn from the different course teams to rate the generated analogies. Initial results are encouraging, illustrating a high degree of face validity. Further work in 2023-24 will evaluate whether this improves learning during the module

Meshat: Monitoring and Experience Sharing Tool for Project-Based Learning

Our work aims at studying tools offered to learners and tutors involved in face-to-face or blended project-based learning activities. To understand better the needs and expectations of each actor, we are especially interested in the specific case of project management training. The results of a course observation show that the lack of monitoring and expertise transfer tools involves important dysfunctions in the course organisation and therefore dissatisfaction for tutors and students (in particular about the acquisition of knowledge and expertise). So as to solve this problem, we propose a personalised platform (according to the actor: project group, student or tutor) which gives information to monitor activities and supports the acquisition and transfer of expertise. This platform is meant for the complex educational context of project-based learning. Indeed, as for the majority of project-based learning activities, the articulation conceptualisation-experiment is an important part of the process. The originality of our approach relies on also supporting the articulation between action (experiment or conceptualisation) and reflection. This approach so improves the acquisition of complex skills (e.g. management, communication and collaboration), which requires a behavioural evolution. We aim at making the students become able ?to learn to learn' and evolve according to contexts. We facilitate their ability to have a critical analysis of their actions according to the situations they encounter.Comment: 8

Resolving the Problem of Intelligent Learning Content in Learning Management Systems

Current e-learning standardization initiatives have put much effort into easing interoperability between systems and the reusability of contents. For this to be possible, one of the most relevant areas is the definition of a run-time environment, which allows Learning Management Systems to launch, track and communicate with learning objects. However, when dealing with intelligent content, these environments show important restrictions. In this article, we study these restrictions, comparing several standardized run-time environments with nonstandardized solutions that aim to overcome these constraints

User context and personalized learning: a federation of contextualized attention metadata

Nowadays, personalized education is a very hot topic in technology enhanced learning (TEL) research. To support students during their learning process, the first step consists in capturing the context in which they evolve. Users typically operate in a heterogeneous environment when learning, including learning tools such as Learning Management Systems and non-learning tools and services such as e-mails, instant messaging, or web pages. Thus, user attention in a given context defines the Contextualized Attention Metadata (CAM). Various initiatives and projects allow capturing CAMs in a knowledge workers’ environment not only in the TEL area, but also in other domains like Knowledge Work Support, Personal Information Management and Information Retrieval. After reviewing main existing approaches according to some specific criteria that are of main interest for capturing and sharing user contexts, we present in this paper a framework able to gather CAMs produced by any tool or computer system. The framework is built on the Web-Based Enterprise Management (WBEM) standard dedicated to system, network and application management. Attention information specific to heterogeneous tools are represented as a unified and extensible structure, and stored into a central repository compliant with the above-mentioned standard. To facilitate access to this attention repository, we introduced a middleware layer composed of two dynamic services: the first service allows users to define the attention data they want to collect, whereas the second service is dedicated to receive and retrieve the traces produced by computer systems. An implementation for collecting and storing CAM data generated by the Ariadne Finder and Moodle validates our approach

Social network analysis for technology-enhanced learning: review and future directions

Sie, R. L. L., Ullmann, T. D., Rajagopal, K., Cela, K., Bitter-Rijpkema, M., & Sloep, P. B. (2012). Social network analysis for technology-enhanced learning: review and future directions. International Journal of Technology Enhanced Learning, 4(3/4), 172-190.By nature, learning is social. The interactions by which we learn from others inherently form a network of relationships among people, but also between people and resources. This paper gives an overview of the potential social network analysis (SNA) may have for social learning. It starts with an overview of the history of social learning and how SNA may be of value. The core of the paper outlines the state-of-art of SNA for technology-enhanced learning (TEL), by means of four possible types of SNA applications: visualisation, analysis, simulation, and interventions. In an outlook, future directions of SNA research for TEL are provided