A integração do tutorial interativo TryLogic via IMS Learning Tools Interoperability: construindo uma infraestrutura para o ensino de Lógica através de estratégias de demonstração e refutação

Logic courses represent a pedagogical challenge and the recorded number of cases of failures and of discontinuity in them is often high. Amont other difficulties, students face a cognitive overload to understand logical concepts in a relevant way. On that track, computational tools for learning are resources that help both in alleviating the cognitive overload scenarios and in allowing for the practical experimenting with theoretical concepts. The present study proposes an interactive tutorial, namely the TryLogic, aimed at teaching to solve logical conjectures either by proofs or refutations. The tool was developed from the architecture of the tool TryOcaml, through support of the communication of the web interface ProofWeb in accessing the proof assistant Coq. The goals of TryLogic are: (1) presenting a set of lessons for applying heuristic strategies in solving problems set in Propositional Logic; (2) stepwise organizing the exposition of concepts related to Natural Deduction and to Propositional Semantics in sequential steps; (3) providing interactive tasks to the students. The present study also aims at: presenting our implementation of a formal system for refutation; describing the integration of our infrastructure with the Virtual Learning Environment Moodle through the IMS Learning Tools Interoperability specification; presenting the Conjecture Generator that works for the tasks involving proving and refuting; and, finally to evaluate the learning experience of Logic students through the application of the conjecture solving task associated to the use of the TryLogic

Teacher-learning process based on an immersive and interactive environment

This paper explores the benefits of using immersive and interactive multiprojection environments (CAVE) to visualize molecules, and how it improves users’ understanding. We have proposed and implemented a tool for teachers to manipulate molecules and another to edit molecules and assist students at home. The contribution of the present research project are these tool that allows investigating structures, properties and dynamics of a molecular system which are extremely complex and comprises millions of atoms. The experience is enriched through multimedia information associated with parts of the model; for example, videos and text can be linked to specific molecule, demonstrating some detail. This solution is based on a teaching-learning process.

Frequency and precision of feedback and the adaptive process of learning a dual motor task

This work investigated the effects of frequency and precision of feedback on the learning of a dual-motor task. One hundred and twenty adults were randomly assigned to six groups of different knowledge of results (KR), frequency (100%, 66% or 33%) and precision (specific or general) levels. In the stabilization phase, participants performed the dual task (combination of linear positioning and manual force control) with the provision of KR. Ten non-KR adaptation trials were performed for the same task, but with the introduction of an electromagnetic opposite traction force. The analysis showed a significant main effect for frequency of KR. The participants who received KR in 66% of the stabilization trials showed superior adaptation performance than those who received 100% or 33%. This finding reinforces that there is an optimal level of information, neither too high nor too low, for motor learning to be effective.

Teaching and learning stance in specialized English for computing. A corpus linguistics approach

[EN]The use of large corpora in the study of languages is a well established tradition. In the same vein, scholarship is also well represented in the case of the study of corpora for making grammars of languages. This is the case of the COBUILD grammar and dictionary and the case of the Longman Grammar of Spoken and Written English. This means that corpora have been analyzed in order to identify patterns in languages that can be later practised by learners following those patterns described and exemplified with real instances.

Structure learning of graphical models for task-oriented robot grasping

In the collective imaginaries a robot is a human like machine as any androids in science fiction. However the type of robots that you will encounter most frequently are machinery that do work that is too dangerous, boring or onerous. Most of the robots in the world are of this type. They can be found in auto, medical, manufacturing and space industries. Therefore a robot is a system that contains sensors, control systems, manipulators, power supplies and software all working together to perform a task. The development and use of such a system is an active area of research and one of the main problems is the development of interaction skills with the surrounding environment, which include the ability to grasp objects. To perform this task the robot needs to sense the environment and acquire the object informations, physical attributes that may influence a grasp. Humans can solve this grasping problem easily due to their past experiences, that is why many researchers are approaching it from a machine learning perspective finding grasp of an object using information of already known objects. But humans can select the best grasp amongst a vast repertoire not only considering the physical attributes of the object to grasp but even to obtain a certain effect. This is why in our case the study in the area of robot manipulation is focused on grasping and integrating symbolic tasks with data gained through sensors. The learning model is based on Bayesian Network to encode the statistical dependencies between the data collected by the sensors and the symbolic task. This data representation has several advantages. It allows to take into account the uncertainty of the real world, allowing to deal with sensor noise, encodes notion of causality and provides an unified network for learning. Since the network is actually implemented and based on the human expert knowledge, it is very interesting to implement an automated method to learn the structure as in the future more tasks and object features can be introduced and a complex network design based only on human expert knowledge can become unreliable. Since structure learning algorithms presents some weaknesses, the goal of this thesis is to analyze real data used in the network modeled by the human expert, implement a feasible structure learning approach and compare the results with the network designed by the expert in order to possibly enhance it.

Content and English Language Integrated Learning: The use of Moodle in Aircraft Maintenance Training Programs

The aim of this work is to develop a prototype of an e-learning environment that can foster Content and Language Integrated Learning (CLIL) for students enrolled in an aircraft maintenance training program, which allows them to obtain a license valid in all EU member states. Background research is conducted to retrace the evolution of the field of educational technology, analyzing different learning theories – behaviorism, cognitivism, and (socio-)constructivism – and reflecting on how technology and its use in educational contexts has changed over time. Particular attention is given to technologies that have been used and proved effective in Computer Assisted Language Learning (CALL). Based on the background research and on students’ learning objectives, i.e. learning highly specialized contents and aeronautical technical English, a bilingual approach is chosen, three main tools are identified – a hypertextbook, an exercise creation activity, and a discussion forum – and the learning management system Moodle is chosen as delivery medium. The hypertextbook is based on the technical textbook written in English students already use. In order to foster text comprehension, the hypertextbook is enriched by hyperlinks and tooltips. Hyperlinks redirect students to webpages containing additional information both in English and in Italian, while tooltips show Italian equivalents of English technical terms. The exercise creation activity and the discussion forum foster interaction and collaboration among students, according to socio-constructivist principles. In the exercise creation activity, students collaboratively create a workbook, which allow them to deeply analyze and master the contents of the hypertextbook and at the same time create a learning tool that can help them, as well as future students, to enhance learning. In the discussion forum students can discuss their individual issues, content-related, English-related or e-learning environment-related, helping one other and offering instructors suggestions on how to improve both the hypertextbook and the workbook based on their needs.

Phonological and Syntactic Problems faced by Speakers of Bafoussam-Bamileke as L1 in Learning English as L2

Carrying out this research on the difficulties encountered by Bafoussam-Bamileke's native speakers learning English as their L2 helps to unveil many syntactic and phonological problems that require a great interest no only to teachers but also to learners in order to reach an acceptable level of accuracy and fluency. We have also provided some ways to solve those problems efficiently.

Incidental task sequence learning: perceptual rather than conceptual?

In four experiments we investigated whether incidental task sequence learning occurs when no instructional task cues are available (i.e. with univalent stimuli). We manipulated task sequence by presenting three simple binary-choice tasks (colour, form or letter case decisions) in regular repeated or random order. Participants were required to use the same two response keys for each of the tasks. We manipulated response sequence by ordering the stimuli so as to produce either a regular or a random order of left versus right-hand key presses. When sequencing in both, or either, separate stream (i.e. task sequence and/or response sequence) was changed to random, only those participants who had processed both sequences together showed evidence of sequence learning in terms of significant response time disruption (Experiments 1-3). This effect disappeared when the sequences were uncorrelated (Experiment 4). The results indicate that only the correlated integration of task sequence and response sequence produced a reliable incidental learning effect. As this effect depends on the predictable ordering of stimulus categories, it suggests that task sequence learning is perceptual rather than conceptual in nature.