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Diss. Umeå : Umeå universitet, 2008.

Skolen er en institusjon der alle skal gis anledning til realistiske utfordringer og krav. I uterommet er det snakk om kontekstbasert læring, hvor elevene gis førstehåndserfaringer ved å bruke hele kroppen og utnytte flere sanser gjennom aktivitet. I denne mastergradsoppgaven er det presentert teori og empiriske studier som belyser temaet uterommet som læringsarena, fysisk aktivitet, holdninger og læring. Formålet med studien har vært å kartlegge bruken av uterommet som læringsarena i en kommune i Sør-Trøndelag, og hvilken betydning holdninger har i dette arbeidet. Dataene som er med i undersøkelsen er en del av en mer omfattende spørreundersøkelse, i samarbeid med NTNU og en kommune i Sør-Trøndelag. I min del av undersøkelsen har lærere, rektorer og elever fra 4.-10. trinn tatt stilling til en rekke påstander, der de har svart i henhold til en Likert-skala der 1 = «helt uenig» til 6 = «helt enig». Datamaterialet ble analysert ved bruk av versjon 20 av SPSS. Analysene ble gjort for helheten i utvalget, med separate analyser for lærere, rektorer og elever. Korrelasjonsanalyser og T – tester ble brukt for å finne eventuelle sammenhenger og forskjeller. I tillegg har jeg brukt effektmålene Cohens d og Cramers V. Analysene viser begrenset bruk av uterommet som læringsarena, men lærere som ønsker mer kunnskap om tema. Det er en klar sammenheng mellom lærernes holdning til uterommet, og hvor mye de bruker uterommet. Det er også en klar sammenheng mellom lærernes holdning til uterommet og hvor fornøyde de er med arbeidsmiljøet i uterommet, samt hvorvidt lærerne ser positive konsekvenser for elevene som resultat av denne arbeidsmåten. Uteområdene på skolene er til dels fysisk tilrettelagt elever med funksjonsnedsettelser, men har nesten ingen naturlekeplasser. / At school everyone is supposed to meet realistic challenges and expectations. The outdoor environment provides context-based learning, and the students are given first hand experiences by using their whole body and exploiting their senses through activities. Relevant theory and research has been presented in this thesis, enlightening the subjects of teaching outdoors, physical activities, attitudes and learning. The main aim has been to chart the use of outdoor teaching in a Norwegian county in Sør-Trøndelag, and what extent attitude has in this teaching method. The data from this survey is a part of a more extensive project in co operation with NTNU and a Norwegian county. In my part of the survey, teachers, principals and 4th – 10th graders concider different propositions in a survey, based on a Likert scale, from 1 = “fully wrong” to 6 = “fully right”. The material was analyzed using SPSS version 20. The analysis was done for the sample in its totality, with separate analysis for teachers, principals and students. Correlation analysis and T-tests was used to find coherence and compare means. In addition I used Cohens d and Cramers V for effect sizing. The analysis indicated little use of the outdoor environment, and teachers that want more knowledge on this subject. There is correlation between teacher’s attitude towards working with the outdoor as a learning environment and how often they use the outdoors as a learning environment. There is also correlation between teachers attitude towards working with the outdoors as a learning environment and the positive consequences teachers can see affects the pupils, as well as how satisfied the teachers are with the working environment in the outdoors. The outdoor areas at the schools are to a certain degree arranged for students with mobility dysfunctions, but nature playgrounds are missing. Keywords: teaching outdoors, attitude, outdoor environment, learning, physical activity, senses, school.

<p>This work studies constraint mechanisms in frame-based knowledge representation systems with the aim of improving the knowledge modelling abilities of the TrollCreek system. TrollCreek is an implementation of Creek, an architecture for case based reasoning (CBR) that uses an explicit frame-based knowledge model to guide the CBR process. The objective of this project is to develop a constraint mechanism for TrollCreek. In doing this the earlier Lisp implementation of Creek and four other frame-based systems are examined with emphasize on their constraint mechanisms. Based on these systems a constraint mechanism for TrollCreek is discussed and specified. The part of the mechanism considered most central is implemented and evaluated.</p>

<p>In testing the viability of automatic knowledge-acquisition, using simple techniques and brute force on the Internet, a system was implemented in Java. Techniques from both multi-agent system and swarm intelligence paradigms were used to structure the system, improve searches, increase stability and increase modularity. The system presented relies on using existing search-engines to find texts on the World Wide Web, containing a user-specified key-word. Knowledge is identified in the texts using key-sentences, terms related to the key-word becomes new key-words in an incremental search. The result is expressed as sentences in a KR-language. The answers from a run were often interesting and surprising, and gave information beyond an encyclopedic scope, even if the answers often contained false information. The results of the implemented system verified the viability of both the designed framework and the theory behind it.</p>

<p>The work in this thesis is about natural language processing and understanding, within the context of artificial intelligence research. What was attempted to achieve here was to investigate how meaning is contained in language, particularly with respect to how that information is encoded and how it can be decoded, or extracted. The aspects deemed most relevant for this quest was automated processing of the syntactic structure of sentences, and their semantic components. Artificial neural networks was chosen as the tool to perform the research with, and as such part of the goal became research on connectionist methods. A side-goal of interest was to look into the possibility of using insight into neural networks to gain deeper understanding of how the human brain processes information, particularly language. This area was not explicitly focussed on during the research. The methodology selected for achieving the goals was to design and implement a framework for developing neural network models, and further to implement NLP and NLU systems within this framework. The systems selected to explore and implement were: a parser for handling the syntactic structure and a symbol grounding system for dealing with the semantic component. A third system was also implemented for investigation into an evolutionary-based communication model on the development of a shared vocabulary between autonomous agents. All implementations were based on recent research and results by others.</p>

<p>The emergence of complex data objects that must to be indexed and accessed in databases has created a need for access methods that are both dynamic and efficient. Lately, metric tree structures have become a popular way of handling this because of the advantages they have compared to traditional methods based on spatial indexing. The most common way to handle indexing is to build tree structures and then prune out branches of the trees during search, and for a dynamic indexing structure it is important that these trees stay balanced in order to keep the worst case search time as low as possible. Normally, this is done based on complex criteria and reshuffling operations. Another way to handle balancing is General Balanced Trees (GBT), proposed by Arne Andersson (Journal of Algorithms 30, 1999), which uses simple, global criteria for rebalancing binary search trees by using total and partial rebuilding. This thesis explores if it is possible to apply this to metric tree structures, and especially two static metric tree structures called the Vantage Point Tree and the Multiple Vantage Point Tree. It discusses how to best make these into dynamic tree structures and how to apply balancing by using GBT paradigms on them. The results of the performance of the new tree structures are analyzed, and the results are compared against already existing structures. The results shows that this works for balancing the trees, and that the structures perform reasonably well compared to already existing structures.</p>