588 resultados para Online Collaborative Learning


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MOOC (as an acronym for Massive Open Online Courses) are a quite new model for the delivery of online learning to students. As “Massive” and “Online”, these courses are proposed to be accessible to many more learners than would be possible through conventional teaching. As “Open” they are (frequently) free of charge and participation is not limited by the geographical situation of the learners, creating new learning opportunities in Higher Education Institutions (HEI). In this paper we describe a recently started project “Matemática 100 STRESS” (Math Without STRESS) integrated in the e-IPP project | e-Learning Unit of Porto’s Polytechnic Institute (IPP) which has created its own MOOC platform and launched its first course – Probabilities and Combinatorics – in early June/2014. In this MOOC development were involved several lecturers from four of the seven IPP schools.

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MOOC (as an acronym for Massive Open Online Courses) are a quite new model for the delivery of online learning to students. As “Massive” and “Online”, these courses are proposed to be accessible to many more learners than would be possible through conventional teaching. As “Open” they are (frequently) free of charge and participation is not limited by the geographical situation of the learners, creating new learning opportunities in Higher Education Institutions (HEI). In this paper we describe a recently started project “Matemática 100 STRESS” (Math Without STRESS) integrated in the e-IPP project | e-Learning Unit of Porto’s Polytechnic Institute (IPP) which has created its own MOOC platform and launched its first course – Probabilities and Combinatorics – in early June/2014. In this MOOC development were involved several lecturers from four of the seven IPP schools.

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Teaching and learning computer programming is as challenging as difficult. Assessing the work of students and providing individualised feedback to all is time-consuming and error prone for teachers and frequently involves a time delay. The existent tools and specifications prove to be insufficient in complex evaluation domains where there is a greater need to practice. At the same time Massive Open Online Courses (MOOC) are appearing revealing a new way of learning, more dynamic and more accessible. However this new paradigm raises serious questions regarding the monitoring of student progress and its timely feedback. This paper provides a conceptual design model for a computer programming learning environment. This environment uses the portal interface design model gathering information from a network of services such as repositories and program evaluators. The design model includes also the integration with learning management systems, a central piece in the MOOC realm, endowing the model with characteristics such as scalability, collaboration and interoperability. This model is not limited to the domain of computer programming and can be adapted to any complex area that requires systematic evaluation with immediate feedback.

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Massive Open Online Courses (MOOC) are gaining prominence in transversal teaching-learning strategies. However, there are many issues still debated, namely assessment, recognized largely as a cornerstone in Education. The large number of students involved requires a redefinition of strategies that often use approaches based on tasks or challenging projects. In these conditions and due to this approach, assessment is made through peer-reviewed assignments and quizzes online. The peer-reviewed assignments are often based upon sample answers or topics, which guide the student in the task of evaluating peers. This chapter analyzes the grading and evaluation in MOOCs, especially in science and engineering courses, within the context of education and grading methodologies and discusses possible perspectives to pursue grading quality in massive e-learning courses.

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Dissertação para obtenção do Grau de Doutor em Ciências da Educação Especialidade em Tecnologias, Redes e Multimédia na Educação e Formação

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(Excerto) Olhando para o percurso do RadioActive, há uma ideia que parece ser transversal a todo o projeto. Referimo-nos a um princípio que chamaríamos de “identificação” e que foi determinante – é determinante – nos processos de investigação participativa. Falamos da identificação dos investigadores com os princípios da investigação-ação, da identificação das intervenções com as particularidades de cada contexto. Da imprescindível e progressiva identificação dos participantes com o projeto. Na verdade, sem esta multifacetada identificação é impossível pensar em resultados sustentáveis e persistentes. Investigadores e demais participantes têm de sentir que o projeto é “seu”, que os objetivos são “seus”, embora o façam necessariamente a velocidades diferentes. A aprendizagem, neste âmbito, expande-se sempre de dentro para fora, emerge dos interesses do sujeito e não de uma estrutura pré-concebida e imposta pelos que chegam (Ravenscroft et al., 2011), neste caso, os investigadores. Uma das diferenças das pesquisas participativas em relação às tradicionais é, precisamente, a atuação coletiva e não solitária do investigador. Os pesquisadores fazem parte de um processo participatório em que estão envolvidos numa estrutura (Cammarota & Fine, 2008: 5). Paulo Freire é o autor primordial em todos os projetos e países onde a RA101 foi aplicada. As suas concepções em torno da investigação-ação participativa tentam apontar sempre para uma ação e também para uma reflexão sobre os processos.

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Reinforcement learning (RL) is a very suitable technique for robot learning, as it can learn in unknown environments and in real-time computation. The main difficulties in adapting classic RL algorithms to robotic systems are the generalization problem and the correct observation of the Markovian state. This paper attempts to solve the generalization problem by proposing the semi-online neural-Q_learning algorithm (SONQL). The algorithm uses the classic Q_learning technique with two modifications. First, a neural network (NN) approximates the Q_function allowing the use of continuous states and actions. Second, a database of the most representative learning samples accelerates and stabilizes the convergence. The term semi-online is referred to the fact that the algorithm uses the current but also past learning samples. However, the algorithm is able to learn in real-time while the robot is interacting with the environment. The paper shows simulated results with the "mountain-car" benchmark and, also, real results with an underwater robot in a target following behavior

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Aquest article pretén descriure el procés metodològic d'identificació i mesurament de les competències TIC dels professors i com a formadors en les TIC en un entorn d'aprenentatge en línia en l'Educació Superior portat a terme en el marc del Projecte Europeu Elene-TLC.La revisió de la recerca en les competències en línia del professor demostra que, en primer lloc, el mètode més utilitzat per a identificar aquestes competències és el focus group. En segon lloc, la tècnica Delphi és la tècnica més utilitzada per reunir el consens d'experts sobre quines són les competències principals per al professor en línia entre els que s'indiquen.La proposta metodològica descrita en aquest document consisteix en la creació de 7 grups de discussió en línia, l'objectiu dels quals era identificar les competències formatives dels professors en línia i les dels professos en línia. La llista de competències obtingudes posteriorment es va oferir als experts europeus que participaven en l'aplicació de la tècnica Delphi. A aquests experts se'ls va demanar que ordenessin les competències d'acord amb el seu grau d'importància.Els resultats mostren que els grups de discussió en línia i el mètode Delphi són les metodologies apropiades per a identificar les competències TIC dels professors universitaris en els entorns d'aprenentatge en línia.

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Online learning provides the opportunity to work on academic tasks at any time at the same time as doing other activities, such as using in web 2.0 tools. This study identifies factors that contribute to success in online learning from the students¿ perspective and their relationship with time patterns. A survey of learning outputs was used to find relationships between students¿ satisfaction, knowledge acquisition and knowledge transfer with time for working on academic tasks. In this study, 199 students from a university in Mexico completed the survey. Findings suggest that knowledge transfer has a significant association with the number of hours online per day, hours spent on social networks and the use made of e-learning during working hours. Learner satisfaction has a strong relationship with the time in years a learner has been using the Internet and the number of hours devoted to the course per week. The findings of this research will be helpful for faculty and instructional designers for implementing learning strategies.

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The recognition of prior experiential learning (RPEL) involves the assessment ofskills and knowledge acquired by an individual through previous experience, which isnot necessarily related to an academic context. RPEL practices are far from generalisedin higher education, and there is a lack of specific guidelines on how to implement RPLprograms in particular settings, such as management education or online programs. TheRPEL pilot program developed in a Spanish virtual university is used throughout thearticle as the basis for further reflection on the design and implementation of RPEL inonline postgraduate education in the business field. The role of competences as a centraltheoretical foundation for RPEL is explained, and the context and characteristics of theRPEL program described. Special attention is paid to the key elements of the program¿sdesign and to the practical aspects of its implementation. The results of the program areassessed and general conclusions and suggestions for further research are discussed.

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Peer-reviewed