1,720,996 research outputs found
A Deep Learning Approach to Concept Maps Similarity
No full textConcept maps are graphic tools to organize, represent and share knowledge. In particular, a concept map can explicitly express the knowledge of a person or group, about a given domain of interest. Concept maps are used effectively to support learning of any topic, at any level: from Primary School to University, and to professional/vocational training, it can stimulate and unveil the occurrence of meaningful learning. In an educational context, having the possibility to compare Concept Maps coming from different students, also by means of an automated computation of map similarity, can reveal to be a great asset for a teacher. And this is so much more true when the number of students is very high, like in Massive Open Online Course. Here we propose a similarity measure based on two deep learning techniques that produce embeddings of the single structures that make up a concept map. We also report about a preliminary experiment, having encouraging results
A social network-based teacher model to support course construction
Full text linkOn line education is a student centred activity, and most of the research in this field focuses on students; yet the quality of teaching is undoubtedly the basic ingredient for a successful learning. In particular, fostering new forms of collaboration between students and teachers, i.e. pursuing co-learning aspects of e-learning, probably needs giving teachers new means of collaboration, also among themselves. In this paper, we tackle the aim of providing the teacher with social collaboration tools, to support the process of course construction. Such a process comprises several distinct steps, from concept mapping, through selection of suitable learning material, to the final stages of delivery in a Learning Management System. It is an heavy process, through which teachers have to spend a lot of time to build or to retrieve the right learning material from local databases or from specialized repositories on the web. The support we foresee should exploit the knowledge of the whole teaching community, in which the teacher acts, to help her/him in doing the above described job. By "knowledge" we mean basically a representation of the ways of usage of learning materials, by the teachers in the community for their courses. To start on a solid footing, here we address the topic of modeling the teacher. The model we define aims to give teachers a personalized support, encompassing consideration for their own pedagogy, teaching styles, and teaching experience during course creation. It is deemed to consider all those issues in a dynamic way and to guide the teacher towards the best didactic choices
Evaluation of Programming Skills via Peer Assessment and IRT Estimation Techniques
No full textIn whatever study program where Computer Science is taught (as a support subject matter, or as the main one) the analysis of students' programming skills is a complex and crucial endeavour. Peer assessment (PA) can be used to expose students (peers) to a very effective educational methodology, to spur competence, and to evaluate skills in a wide range of subject matters, including Computer Science and programming. An important feature is in that data from PA sessions can be used to model the students, and support the inference of automated grading. In this paper we analyse the data coming from experiments where several PA sessions were conducted, with students having to produce programs, and evaluate their peers' programs. The main aim is to see how methods of the Item Response Theory (IRT) can be applied in the PA framework, to model the students effectively. The results seem encouraging, allowing to foresee the enrichment of more traditional automated grading techniques by the IRT methods
Estimating Ability of Programming Skills using IRT based Peer Assessments
No full textHere we analyze data coming from several peer assessment activities, conducted in the framework of a course on basics in Computer Science, for an undergraduate program in Computer Engineering. The peer assessment data are basically the grades given by the peers to the artifacts produced by other peers, while accomplishing a task related to Computer Programming. We analyze the experimental data using an item response theory (IRT) based generalized many-facet Rasch model (GMFRM). Though the peer ratings in five separated sessions of peer assessment were sparse (due to unstable - non mandatory - participation in the activities), the estimated ability and rating characteristics for all participants were extracted. The estimated ability strongly correlates with teacher's rating of the artifacts, and with the final grade obtained by the students in a separate final examination
A recommendation module to help teachers build courses through the Moodle Learning Management System
Full text linkIn traditional e-learning, teachers design sets of Learning Objects (LOs) and organize their sequencing; the material implementing the LOs could be either built anew or adopted from elsewhere (e.g. from standard-compliant repositories) and reused. This task is applicable also when the teacher works in a system for personalized e-learning. In this case, the burden actually increases: for instance, the LOs may need adaptation to the system, through additional metadata. This paper presents a module that gives some support to the operations of retrieving, analyzing, and importing LOs from a set of standard Learning Objects Repositories, acting as a recommending system. In particular, it is designed to support the teacher in the phases of (i) retrieval of LOs, through a keyword-based search mechanism applied to the selected repositories; (ii) analysis of the returned LOs, whose information is enriched by a concept of relevance metric, based on both the results of the searching operation and the data related to the previous use of the LOs in the courses managed by the Learning Management System; and (iii) LO importation into the course under construction
Supporting mediated peer-evaluation to grade answers to open-ended questions
Full text linkWe show an approach to semi-automatic grading of answers given by students to open ended questions (open answers). We use both peer-evaluation and teacher evaluation. A learner is modeled by her Knowledge and her assessments quality (Judgment). The data generated by the peer- and teacher- evaluations, and by the learner models is represented by a Bayesian Network, in which the grades of the answers, and the elements of the learner models, are variables, with values in a probability distribution. The initial state of the network is determined by the peer-assessment data. Then, each teacher’s grading of an answer triggers evidence propagation in the network. The framework is implemented in a web-based system. We present also an experimental activity, set to verify the effectiveness of the approach, in terms of correctness of system grading, amount of required teacher's work, and correlation of system outputs with teacher’s grades and student’s final exam grade
Wiki course builder: A system for retrieving and sequencing didactic materials from Wikipedia
No full textThe designing and delivering of a new online course is a crucial task for teachers that have to face two main problems: building, or retrieving, and sequencing learning materials. Retrieving learning materials requires a great effort and a waste of time, while sequencing them requires an accurate didactic project. On the other hand, thanks to the Internet, teachers and instructional designers today can search and retrieve learning materials from Learning Objects Repositories freely available on the Web, such as Mertlot or Ariadne. In this paper we investigate the possibility of using the Wikipedia free encyclopedia, that is the biggest repository of educational material which is visited daily by about sixty million people with its 49 millions of registered people. It is a matter of facts that teachers consult this encyclopedia to arrange, integrate or enrich their courses. So here we propose a system, now at its early stage of development, aiming at supporting teachers to build courses basing on Wikipedia only. The system retrieves learning materials form Wikipedia and sequences them on the basis of the links embedded in the Wikipedia HTML pages, following a course building process based on the Grasha teaching styles and on a social didactic approach. A first questionnaire has been submitted to a sample of teachers with encouraging results
Exploiting wikipedia for discovering prerequisite relationships among learning objects
No full textIdentifying the pre-requisite relationships among learning objects is a crucial step for faculty and instructional designers when they try to adapt them for delivery in their education distance courses. It results in one of the most relevant constraint to check for ensuring that if a learning object references another, the referenced one is also in the course positioned before the former. This paper reports about a project under development aiming at facilitating this step. In particular, a content-based approach supported by semantic analysis techniques identifies pre-requisite relationships between text-based learning objects without effort by the user
A Case-Based Approach to Adaptive Hypermedia Navigation
No full textHypermedia, with its combination of multimedia and non-linear organization of links among informative nodes, provides a highly interactive environment. In structured domains such as Web-based Educational Systems, the complexity of the learning domain often requires a large set of learning nodes and conceptual interrelationships that can cause several issues, e.g.: lack of comprehension, disorientation and inefficacious learning strategies. In this article we propose a new approach to guided navigation in hypermedia-based domains, suitable for helping users in structured and complex learning environments such as cultural heritage domains. Our proposal draws inspiration from the Case-Based Reasoning paradigm associated with a hypermedia structural analysis. In particular, our presentation highlights the use of a hybrid architecture for Adaptive Navigation Support, where the indexing problem of the case-based reasoner is solved by way of a sub-symbolic approach. A case study in the Neo-Realist Italian Cinema domain is discussed along with a formal and controlled evaluation that proves the advantages of the proposed approach
A Content-Based Approach for Supporting Teachers in Discovering Dependency Relationships Between Instructional Units in Distance Learning Environments
No full texteLearning courses are usually built in such a way that training resources are organized for making the learning process effective. In most cases, the top-level learning objective will have prerequisites which must be satisfied. Those prerequisites should be formally identified by a hierarchy of dependencies built accordingly. We evaluate a series of hypotheses for understanding the feasibility of automating this task by means of a general-purpose content-based approach that exploits semantic analysis techniques. © Springer International Publishing Switzerland 2015
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