O papel do e-professor na plataforma de e-learning e-raízes : redes

Relatório de estágio apresentado para obtenção do grau de mestre em Educação e Comunicação Multimédia

Construção da plataforma de e-Learning do Instituto Politécnico de Santarém

Relatório de estágio apresentado para obtenção do grau de mestre em Educação e Comunicação Multimédia.

VirRAD: A New Paradigm for Technology Enhanced Learning

In most e-learning scenarios, communication and on-line collaboration is seen as an add-on feature to resource based learning. This paper will endeavour to present a pedagogical framework for inverting this view and putting communities of practice as the basic paradigm for e-learning. It will present an approach currently being used in the development of a virtual Radiopharmacy community, called VirRAD, and will discuss how theory can lead to an instructional design approach to support technologically enhanced learning.(DIPF/Orig.)

Ohjaus ja oppilaiden urapohdinta. Turkulaisten peruskoulun päättöluokkalaisten ohjauskokemukset urapohdinnan selittäjinä

Tutkimuksessa selvitetään turkulaisten peruskoulun päättöluokkalaisten urapohdintaeroja ja sitä, miten oppilaiden arviot opettajien ja oppilaanohjaajien toteuttamasta ohjauksesta ovat yhteydessä heidän urapohdintaansa. Tutkimuksen kohdejoukkona ovat ensi sijassa yleisopetusta antavien suomenkielisten peruskoulujen yhdeksäsluokkalaiset. Tutkimus on poikkileikkaustutkimus, jossa tarkastellaan oppilaiden kokemuksia ohjauksen saatavuudesta ja hyödyllisyydestä sekä urapohdinnasta peruskoulun päättyessä. Tutkimusaineisto koottiin yhteishaun jälkeen huhti–toukokuussa 2014. Vuoden 2004 perusopetuksen opetussuunnitelman perusteista johdettujen väittämien avulla selitetään urapohdinta-mittarin sisältämien muuttujien vaihtelua. Taustamuuttujina käytetään oppilaiden koti- ja koulutaustaa. Urapohdinta-mittari on johdettu CIP-teoriasta (Cognitive Information Processing) ja muokattu CTI-mittarista (Career Thoughts Inventory). Tutkimusaineisto (N = 887) on koottu Webropol-kyselyn avulla. Oppilaiden urapohdintaa mitattiin neljän summamuuttujien avulla. Mittariston 48 väittämästä muodostettiin urapohdinta-summamuuttuja. Tämän lisäksi urapohdinnan osa-alueita arvioitiin sitoutuminen-, epävarmuus- ja konflikti-summamuuttujan avulla. Sitoutuminen-summamuuttuja mittasi sitä, miten vaikeaksi oppilas koki yhteen ura- ja jatkokoulutusvalintaan sitoutumisen. Epävarmuus-summamuuttuja mittasi päätöksenteon epävarmuutta ja konflikti-summamuuttuja vaikeutta tasapainoilla omien ajatusten ja toisaalta merkittäviksi koettujen läheisten ajatusten välillä. Kaikkien opettajien ohjaustyön näkökulmasta parhaiten hyvää urapohdintatulosta, jatkokoulutukseen sitoutumista ja päätöksentekovarmuutta ennustivat oppilaan hyvät kokemukset yhteistoiminnasta, hänen myönteinen suhtautumisensa koulunkäyntiin ja opintosuoritukset. Myös itseohjautuvuus oli tilastollisesti merkitsevässä yhteydessä urapohdintaan. Itseohjautuvuus-summamuuttuja mittasi sitä, oliko oppilas kokenut, että ohjaukselle asetetut tavoitteet saavutettiin. Opettajien tulisi kiinnittää ohjauksessaan huomiota hiljaisiin ja vähän huomiota vaativiin oppilaisiin ja tukea kaikkien oppilaiden toimintakykyä. Opinto-ohjaajan taas tulisi panostaa oppilaan itsetuntemuksen kehittämiseen ja valmiuteen toimia suunnitelmallisesti. Toisen asteen nivelvaiheohjauksen painopiste tulisi siirtää päättöluokkaa varhaisemmaksi. Tutkimustulos ei tue ajatusta, että tehostettu oppilaanohjaus kohdennettaisiin opintomenestyksen mukaan, koska heikkoja urapohtijoita oli kaikissa keskiarvosanaluokissa. Opinto-ohjaajien tulisi panostaa tieto- ja viestintätekniikan hyödyntämiseen ja tehostaa koko koulun työelämäyhteistyötä.

Receção estética do texto e promoção da educação literária : trabalho colaborativo interdisciplinar

Dissertação apresentada à Escola Superior de Educação do Instituto Politécnico de Castelo Branco para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Supervisão e Avaliação Escolar.

Construção da plataforma de e-Learning do Instituto Politécnico de Santarém

Relatório de estágio apresentado para obtenção do grau de mestre em Educação e Comunicação Multimédia.

Computational Foundations for Safe and Efficient Human-Robot Collaboration in Assembly Cells

Human and robots have complementary strengths in performing assembly operations. Humans are very good at perception tasks in unstructured environments. They are able to recognize and locate a part from a box of miscellaneous parts. They are also very good at complex manipulation in tight spaces. The sensory characteristics of the humans, motor abilities, knowledge and skills give the humans the ability to react to unexpected situations and resolve problems quickly. In contrast, robots are very good at pick and place operations and highly repeatable in placement tasks. Robots can perform tasks at high speeds and still maintain precision in their operations. Robots can also operate for long periods of times. Robots are also very good at applying high forces and torques. Typically, robots are used in mass production. Small batch and custom production operations predominantly use manual labor. The high labor cost is making it difficult for small and medium manufacturers to remain cost competitive in high wage markets. These manufactures are mainly involved in small batch and custom production. They need to find a way to reduce the labor cost in assembly operations. Purely robotic cells will not be able to provide them the necessary flexibility. Creating hybrid cells where humans and robots can collaborate in close physical proximities is a potential solution. The underlying idea behind such cells is to decompose assembly operations into tasks such that humans and robots can collaborate by performing sub-tasks that are suitable for them. Realizing hybrid cells that enable effective human and robot collaboration is challenging. This dissertation addresses the following three computational issues involved in developing and utilizing hybrid assembly cells: - We should be able to automatically generate plans to operate hybrid assembly cells to ensure efficient cell operation. This requires generating feasible assembly sequences and instructions for robots and human operators, respectively. Automated planning poses the following two challenges. First, generating operation plans for complex assemblies is challenging. The complexity can come due to the combinatorial explosion caused by the size of the assembly or the complex paths needed to perform the assembly. Second, generating feasible plans requires accounting for robot and human motion constraints. The first objective of the dissertation is to develop the underlying computational foundations for automatically generating plans for the operation of hybrid cells. It addresses both assembly complexity and motion constraints issues. - The collaboration between humans and robots in the assembly cell will only be practical if human safety can be ensured during the assembly tasks that require collaboration between humans and robots. The second objective of the dissertation is to evaluate different options for real-time monitoring of the state of human operator with respect to the robot and develop strategies for taking appropriate measures to ensure human safety when the planned move by the robot may compromise the safety of the human operator. In order to be competitive in the market, the developed solution will have to include considerations about cost without significantly compromising quality. - In the envisioned hybrid cell, we will be relying on human operators to bring the part into the cell. If the human operator makes an error in selecting the part or fails to place it correctly, the robot will be unable to correctly perform the task assigned to it. If the error goes undetected, it can lead to a defective product and inefficiencies in the cell operation. The reason for human error can be either confusion due to poor quality instructions or human operator not paying adequate attention to the instructions. In order to ensure smooth and error-free operation of the cell, we will need to monitor the state of the assembly operations in the cell. The third objective of the dissertation is to identify and track parts in the cell and automatically generate instructions for taking corrective actions if a human operator deviates from the selected plan. Potential corrective actions may involve re-planning if it is possible to continue assembly from the current state. Corrective actions may also involve issuing warning and generating instructions to undo the current task.

'Explicit Learning: an Effort towards Human Scheduling Algorithms'

Abstract Scheduling problems are generally NP-hard combinatorial problems, and a lot of research has been done to solve these problems heuristically. However, most of the previous approaches are problem-specific and research into the development of a general scheduling algorithm is still in its infancy. Mimicking the natural evolutionary process of the survival of the fittest, Genetic Algorithms (GAs) have attracted much attention in solving difficult scheduling problems in recent years. Some obstacles exist when using GAs: there is no canonical mechanism to deal with constraints, which are commonly met in most real-world scheduling problems, and small changes to a solution are difficult. To overcome both difficulties, indirect approaches have been presented (in [1] and [2]) for nurse scheduling and driver scheduling, where GAs are used by mapping the solution space, and separate decoding routines then build solutions to the original problem. In our previous indirect GAs, learning is implicit and is restricted to the efficient adjustment of weights for a set of rules that are used to construct schedules. The major limitation of those approaches is that they learn in a non-human way: like most existing construction algorithms, once the best weight combination is found, the rules used in the construction process are fixed at each iteration. However, normally a long sequence of moves is needed to construct a schedule and using fixed rules at each move is thus unreasonable and not coherent with human learning processes. When a human scheduler is working, he normally builds a schedule step by step following a set of rules. After much practice, the scheduler gradually masters the knowledge of which solution parts go well with others. He can identify good parts and is aware of the solution quality even if the scheduling process is not completed yet, thus having the ability to finish a schedule by using flexible, rather than fixed, rules. In this research we intend to design more human-like scheduling algorithms, by using ideas derived from Bayesian Optimization Algorithms (BOA) and Learning Classifier Systems (LCS) to implement explicit learning from past solutions. BOA can be applied to learn to identify good partial solutions and to complete them by building a Bayesian network of the joint distribution of solutions [3]. A Bayesian network is a directed acyclic graph with each node corresponding to one variable, and each variable corresponding to individual rule by which a schedule will be constructed step by step. The conditional probabilities are computed according to an initial set of promising solutions. Subsequently, each new instance for each node is generated by using the corresponding conditional probabilities, until values for all nodes have been generated. Another set of rule strings will be generated in this way, some of which will replace previous strings based on fitness selection. If stopping conditions are not met, the Bayesian network is updated again using the current set of good rule strings. The algorithm thereby tries to explicitly identify and mix promising building blocks. It should be noted that for most scheduling problems the structure of the network model is known and all the variables are fully observed. In this case, the goal of learning is to find the rule values that maximize the likelihood of the training data. Thus learning can amount to 'counting' in the case of multinomial distributions. In the LCS approach, each rule has its strength showing its current usefulness in the system, and this strength is constantly assessed [4]. To implement sophisticated learning based on previous solutions, an improved LCS-based algorithm is designed, which consists of the following three steps. The initialization step is to assign each rule at each stage a constant initial strength. Then rules are selected by using the Roulette Wheel strategy. The next step is to reinforce the strengths of the rules used in the previous solution, keeping the strength of unused rules unchanged. The selection step is to select fitter rules for the next generation. It is envisaged that the LCS part of the algorithm will be used as a hill climber to the BOA algorithm. This is exciting and ambitious research, which might provide the stepping-stone for a new class of scheduling algorithms. Data sets from nurse scheduling and mall problems will be used as test-beds. It is envisaged that once the concept has been proven successful, it will be implemented into general scheduling algorithms. It is also hoped that this research will give some preliminary answers about how to include human-like learning into scheduling algorithms and may therefore be of interest to researchers and practitioners in areas of scheduling and evolutionary computation. References 1. Aickelin, U. and Dowsland, K. (2003) 'Indirect Genetic Algorithm for a Nurse Scheduling Problem', Computer & Operational Research (in print). 2. Li, J. and Kwan, R.S.K. (2003), 'Fuzzy Genetic Algorithm for Driver Scheduling', European Journal of Operational Research 147(2): 334-344. 3. Pelikan, M., Goldberg, D. and Cantu-Paz, E. (1999) 'BOA: The Bayesian Optimization Algorithm', IlliGAL Report No 99003, University of Illinois. 4. Wilson, S. (1994) 'ZCS: A Zeroth-level Classifier System', Evolutionary Computation 2(1), pp 1-18.

Movement Sonification: Effects on Motor Learning beyond Rhythmic Adjustments

Motor learning is based on motor perception and emergent perceptual-motor representations. A lot of behavioral research is related to single perceptual modalities but during last two decades the contribution of multimodal perception on motor behavior was discovered more and more. A growing number of studies indicates an enhanced impact of multimodal stimuli on motor perception, motor control and motor learning in terms of better precision and higher reliability of the related actions. Behavioral research is supported by neurophysiological data, revealing that multisensory integration supports motor control and learning. But the overwhelming part of both research lines is dedicated to basic research. Besides research in the domains of music, dance and motor rehabilitation, there is almost no evidence for enhanced effectiveness of multisensory information on learning of gross motor skills. To reduce this gap, movement sonification is used here in applied research on motor learning in sports. Based on the current knowledge on the multimodal organization of the perceptual system, we generate additional real-time movement information being suitable for integration with perceptual feedback streams of visual and proprioceptive modality. With ongoing training, synchronously processed auditory information should be initially integrated into the emerging internal models, enhancing the efficacy of motor learning. This is achieved by a direct mapping of kinematic and dynamic motion parameters to electronic sounds, resulting in continuous auditory and convergent audiovisual or audio-proprioceptive stimulus arrays. In sharp contrast to other approaches using acoustic information as error-feedback in motor learning settings, we try to generate additional movement information suitable for acceleration and enhancement of adequate sensorimotor representations and processible below the level of consciousness. In the experimental setting, participants were asked to learn a closed motor skill (technique acquisition of indoor rowing). One group was treated with visual information and two groups with audiovisual information (sonification vs. natural sounds). For all three groups learning became evident and remained stable. Participants treated with additional movement sonification showed better performance compared to both other groups. Results indicate that movement sonification enhances motor learning of a complex gross motor skill-even exceeding usually expected acoustic rhythmic effects on motor learning.

Offen werden für demokratiepolitische Themen. Politische Bewusstseinsbildung in verpflichtenden Gender-Trainings trotz persönlichen Widerstands

Wie kann in Seminaren zu Genderkompetenz Offenheit erzeugt werden, wenn die Teilnehmenden sich nicht freiwillig für den Besuch entschieden haben und daher mit Desinteresse oder Widerwillen reagieren? Der vorliegende Beitrag beschreibt ein didaktisches Vorgehen, das den persönlichen Widerstand von Teilnehmenden aufzulösen vermag und letztlich ein Problembewusstsein für soziale Ungleichheit initiiert. Zentral sind hierfür die Reflexion persönlicher Erfahrungen und ideologischer Diskussionen, die Ungleichheitsthemen meist mit sich bringen. Das vorgestellte didaktische Vorgehen im Gender Training, das u.a. Kompetenzerwartungen an Führungskräfte im Bildungsbereich entlang Geschlechterstereotypien aufdeckt, ist auch für andere Themen der politischen Bildung einsetzbar. Um also ein politisches Bewusstsein über Hierarchisierungs- und Diskriminierungsprozesse zu befördern, ist es wichtig, Ausschließungsprozesse im Alltag erlebbar zu machen und zu erkennen, wer vom Ausschluss anderer profitiert, wer die Ausschlusskriterien festlegt und dass unterschiedliche Kriterien dafür geeignet sind. (DIPF/Orig.)

Proces prekaryzacji pracy - nowe kierunki zmian społeczno-gospodarczych w świecie

Wydział Nauk Politycznych i Dziennikarstwa

Learning strategies implemented by the students of Advanced Intensive English I courses for improving oral discourse in the Bachelor of Arts in English Teaching, Department of Foreign Languages, University of El Salvador, year 2014.

There are many learning strategies some, more successful than others when they are applied in a correct way. “Strategies are most successful when they are implemented in a system that encourages collaboration among staff and students, and in which each is a part of a well-planned whole system” (Johns Hopkins, 2000). Additionally, Learning strategies have become an effective instrument in the field of education because students can make use of several strategies in order to enhance their English level in terms of communication. To communicate in a meaningful way, it is important to express ideas inside and outside the classroom; it is part of the development and improvement of speaking.

Relatório de Estágio

O presente relatório surge no âmbito da unidade curricular de Integração Curricular: Prática Educativa e Relatório de Estágio, inserida no plano de estudos do Mestrado em Ensino do 1.º e 2.º Ciclo do Ensino Básico. Este documento valida a obtenção do grau mestre, habilitando para a docência em 1.º e 2.º ciclo do Ensino Básico. Neste sentido, apresenta o percurso individual de formação, com opções fundamentadas e em contexto, articuladas entre os saberes teóricos e os saberes práticos construídos e aplicados ao longo da formação académica da mestranda. No desenvolvimento da Prática Educativa, a metodologia de investigação-ação foi a base de todo o trabalho desenvolvido pela professora estagiária. O seu processo cíclico faseado em quatro fases: observação, planificação, ação e reflexão, permitiu a construção de conhecimentos sólidos que sustentam a prática docente. A par desta metodologia, a supervisão pedagógica assenta num momento importante e insubstituível de aprendizagem na formação docente, uma vez que motiva à reflexão partilhada. A reflexão em colaboração com o par pedagógico, com os orientadores cooperantes e com os supervisores institucionais permite a partilha de saberes e de vivências com o objetivo de modificar e melhorar práticas de ensino. O rumo deste Relatório de Estágio desencadeia, ainda a reflexão crítica sobre todas instâncias da escola e da comunidade educativa, através da implementação de projetos contextualizados, que leva ao desenvolvimento de um processo ativo na construção pessoal, profissional e social do profissional de educação.

Relatório de Estágio

O presente relatório de estágio afigura-se como o produto final de um 2.º ciclo de estudos no mestrado profissionalizante em Ensino do 1.º e 2º Ciclo do Ensino Básico, materializando-se na unidade curricular de Integração Curricular: Prática Educativa e Relatório de Estágio. Este documento constitui a evidência do percurso individual de formação da mestranda através da fundamentação e contextualização das opções realizadas em contexto de prática educativa e numa perspetiva teórica, procurando uma articulação entre estas duas dimensões. Em termos estruturais este relatório obedece às normas institucionais e inicia-se por um enquadramento teórico e legal, numa perspetiva académica e profissional, em que se mobilizam os conhecimentos adquiridos ao longo dos anos de formação e que sustentaram a componente prática da unidade curricular. Esta componente surge, desta forma, como uma oportunidade de colocar em prática os conhecimentos adquiridos ao longo da formação académica. Numa segunda parte, retrata-se, refletida e sustentadamente, as experiências educativas vivenciadas em contexto de estágio, em diferentes dimensões. O processo cíclico de observação, ação e reflexão pós-ação, que caracterizou a prática educativa e que permitiu refletir sobre a ação, tendo em vista uma melhoria efetiva, é também objeto de análise. Em conjugação com o processo de supervisão que orientou toda a prática, destaca-se a colaboração entre a mestranda e os professores cooperantes que a acompanharam assim como a partilha de saberes entre o grupo de estágio e de onde resultou a postura crítica-reflexiva e consciente de orientações fundamentais para o desenvolvimento pessoal e profissional da professora em formação.