810 resultados para Learning context
Resumo:
The long short-term memory (LSTM) is not the only neural network which learns a context sensitive language. Second-order sequential cascaded networks (SCNs) are able to induce means from a finite fragment of a context-sensitive language for processing strings outside the training set. The dynamical behavior of the SCN is qualitatively distinct from that observed in LSTM networks. Differences in performance and dynamics are discussed.
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My goal for this research project was to explore the levels of mentoring within a disability-focused service learning context known as the Special Needs Activity Program (SNAP). At present, research on mentoring within specific service learning contexts remains largely unexamined. In an effort to assess service learning and mentoring, I completed a comparative case study across three distinct years of SNAP. Undergraduate student leaders, known as coordinators, organize and implement SNAP as a thesis project. I focused specifically on the mentoring experience of particular coordinators of SNAP. My thesis presents and describes the findings of several levels of analysis across three SNAP coordinator cohorts. The analysis focused on key words, idiomatic expressions, patterns and dissonances. In my conclusion, I offer three metaphors that describe mentoring within the SNAP experience and relate these to my discussion about how mentoring functions as a component of service learning.
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The goal of this paper is to show the results of an on-going experience on teaching project management to grade students by following a development scheme of management related competencies on an individual basis. In order to achieve that goal, the students are organized in teams that must solve a problem and manage the development of a feasible solution to satisfy the needs of a client. The innovative component advocated in this paper is the formal introduction of negotiating and virtual team management aspects, as different teams from different universities at different locations and comprising students with different backgrounds must collaborate and compete amongst them. The different learning aspects are identified and the improvement levels are reflected in a rubric that has been designed ad hoc for this experience. Finally, the effort frameworks for the student and instructor have been established according to the requirements of the Bologna paradigms. This experience is developed through a software-based support system allowing blended learning for the theoretical and individual?s work aspects, blogs, wikis, etc., as well as project management tools based on WWW that allow the monitoring of not only the expected deliverables and the achievement of the goals but also the progress made on learning as established in the defined rubric
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The current study aimed to investigate and provide furthering evidence of individual differences as determinants of task performance. This research focused on the effects of the personality traits Openness to Experience and Neuroticism, and two goal orientation traits. Learning Orientation and Avoid Orientation, on task performance. The hypotheses addressed the predictability of the traits, the differential effects of personality and goal orientation traits, and the mediating effects of goal orientation on the relationship between personality and performance. The results were based on questionnaire responses completed by a sample of 103 students. Scores on a computerised Air Traffic Control (ATC) decision-making task were used as a measure of task performance. Learning Orientation was found to be a significant predictor of performance, whilst the effect of Neuroticism was 'approaching' significance. Results indicated strong support for the differential relationship between personality traits and corresponding goal orientation traits. The mediating relationship between Openness to Experience, Learning Orientation and performance was also found to be 'approaching' significance. Results were indicative of the influences of personality and goal orientation on consequent performance outcomes. Implications were discussed, as well as suggestions for possible future directions in research assessing the predictabilit)' of individual differences in learning contexts.
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The importance of learning context has stirred debates in the field of second language acquisition over the past two decades since studying a second language (L2) abroad is believed to provide authentic opportunities that facilitate L2 acquisition and development. The present paper examines whether language performance of learners studying English in a formal language classroom context at home (AH) is different from performance of learners who study English abroad (SA) where they would have to use English for a range of communicative purposes. The data for this comparative study is part of a larger corpus of L2 performance of 100 learners of English, 60 in Tehran and 40 in London, on four oral narrative tasks. The two groups’ performances are compared on a range of different measures of fluency, accuracy, syntactic complexity and lexical diversity. The results of the analyses indicate that learners in the two contexts are very similar with respect to the grammatical accuracy and aspects of the oral fluency of their performance. However, the SA group appears to have benefited from living and studying abroad in producing language of higher syntactic complexity and lexical diversity. These results have significant implications for language teaching in AH contexts.
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Despite the wealth of valuable information that has been generated by motivation studies to date, there are certain limitations in the common approaches. Quantitative and psychometric approaches to motivation research that have dominated in recent decades provided epiphenomenal descriptions of learner motivation within different contexts. However, these approaches assume homogeneity within a given group and often mask the variation between learners within the same, and different, contexts. Although these studies have provided empirical data to form and validate theoretical constructs, they have failed to recognise learners as individual ‘people’ that interact with their context. Learning context has become increasingly explicit in motivation studies, (see Coleman et al. 2007 and Housen et al. 2011), however it is generally considered as a background variable which is pre-existing and external to the individual. Stemming from the recent ‘social turn’ (Block 2003) in SLA research from a more cognitive-linguistic perspective to a more context-specific view of language learning, there has been an upsurge in demand for a greater focus on the ‘person in context’ in motivation research (Ushioda 2011). This paper reports on the findings of a longitudinal study of young English learners of French as they transition from primary to secondary school. Over 12 months, the study employed a mixed-method approach in order to gain an in-depth understanding of how the learners’ context influenced attitudes to language learning. The questionnaire results show that whilst the learners displayed some consistent and stable motivational traits over the 12 months, there were significant differences for learners within different contexts in terms of their attitudes to the language classroom and their levels of self-confidence. A subsequent examination of the qualitative focus group data provided an insight into how and why these attitudes were formed and emphasised the dynamic and complex interplay between learners and their context.
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Abstract The ultimate problem considered in this thesis is modeling a high-dimensional joint distribution over a set of discrete variables. For this purpose, we consider classes of context-specific graphical models and the main emphasis is on learning the structure of such models from data. Traditional graphical models compactly represent a joint distribution through a factorization justi ed by statements of conditional independence which are encoded by a graph structure. Context-speci c independence is a natural generalization of conditional independence that only holds in a certain context, speci ed by the conditioning variables. We introduce context-speci c generalizations of both Bayesian networks and Markov networks by including statements of context-specific independence which can be encoded as a part of the model structures. For the purpose of learning context-speci c model structures from data, we derive score functions, based on results from Bayesian statistics, by which the plausibility of a structure is assessed. To identify high-scoring structures, we construct stochastic and deterministic search algorithms designed to exploit the structural decomposition of our score functions. Numerical experiments on synthetic and real-world data show that the increased exibility of context-specific structures can more accurately emulate the dependence structure among the variables and thereby improve the predictive accuracy of the models.
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In Costa Rica, many secondary students have serious difficulties to establish relationships between mathematics and real-life contexts. They question the utilitarian role of the school mathematics. This fact motivated the research object of this report which evidences the need to overcome methodologies unrelated to students’ reality, toward new didactical options that help students to value mathematics, reasoning and its applications, connecting it with their socio-cultural context. The research used a case study as a qualitative methodology and the social constructivism as an educational paradigm in which the knowledge is built by the student; as a product of his social interactions. A collection of learning situations was designed, validated, and implemented. It allowed establishing relationships between mathematical concepts and the socio-cultural context of participants. It analyzed the impact of students’socio-cultural context in their mathematics learning of basic concepts of real variable functions, consistent with the Ministry of Education (MEP) Official Program. Among the results, it was found that using students’sociocultural context improved their motivational processes, mathematics sense making, and promoted cooperative social interactions. It was evidenced that contextualized learning situations favored concepts comprehension that allow students to see mathematics as a discipline closely related with their every-day life.
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Recent work by Siegelmann has shown that the computational power of recurrent neural networks matches that of Turing Machines. One important implication is that complex language classes (infinite languages with embedded clauses) can be represented in neural networks. Proofs are based on a fractal encoding of states to simulate the memory and operations of stacks. In the present work, it is shown that similar stack-like dynamics can be learned in recurrent neural networks from simple sequence prediction tasks. Two main types of network solutions are found and described qualitatively as dynamical systems: damped oscillation and entangled spiraling around fixed points. The potential and limitations of each solution type are established in terms of generalization on two different context-free languages. Both solution types constitute novel stack implementations - generally in line with Siegelmann's theoretical work - which supply insights into how embedded structures of languages can be handled in analog hardware.
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23rd SPACE AGM and Conference from 9 to 12 May 2012 Conference theme: The Role of Professional Higher Education: Responsibility and Reflection Venue: Mikkeli University of Applied Sciences, Mikkeli, Finland
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This paper presents a collaborative virtual learning environment, which includes technologies such as 3D virtual representations, learning and content management systems, remote experiments, and collaborative learning spaces, among others. It intends to facilitate the construction, management and sharing of knowledge among teachers and students, in a global perspective. The environment proposes the use of 3D social representations for accessing learning materials in a dynamic and interactive form, which is regarded to be closer to the physical reality experienced by teachers and students in a learning context. A first implementation of the proposed extended immersive learning environment, in the area of solid mechanics, is also described, including the access to theoretical contents and a remote experiment to determine the elastic modulus of a given object.These instructions give you basic guidelines for preparing camera-ready papers for conference proceedings. Use this document as a template if you are using Microsoft Word 6.0 or later. Otherwise, use this document as an instruction set. The electronic file of your paper will be formatted further. Define all symbols used in the abstract. Do not cite references in the abstract.