Effect of the Knowledge Representation Form on the Efficiency of Knowledge Sharing

The goal of this thesis is to estimate the effect of the form of knowledge representation on the efficiency of knowledge sharing. The objectives include the design of an experimental framework which would allow to establish this effect, data collection, and statistical analysis of the collected data. The study follows the experimental quantitative design. The experimental questionnaire features three sample forms of knowledge: text, mind maps, concept maps. In the interview, these forms are presented to an interviewee, afterwards the knowledge sharing time and knowledge sharing quality are measured. According to the statistical analysis of 76 interviews, text performs worse in both knowledge sharing time and quality compared to visualized forms of knowledge representation. However, mind maps and concept maps do not differ in knowledge sharing time and quality, since this difference is not statistically significant. Since visualized structured forms of knowledge perform better than unstructured text in knowledge sharing, it is advised for companies to foster the usage of these forms in knowledge sharing processes inside the company. Aside of performance in knowledge sharing, the visualized structured forms are preferable due the possibility of their usage in the system of ontological knowledge management within an enterprise.

Sentence Compression with Supervised Machine Learning

The subject of the thesis is automatic sentence compression with machine learning, so that the compressed sentences remain both grammatical and retain their essential meaning. There are multiple possible uses for the compression of natural language sentences. In this thesis the focus is generation of television program subtitles, which often are compressed version of the original script of the program. The main part of the thesis consists of machine learning experiments for automatic sentence compression using different approaches to the problem. The machine learning methods used for this work are linear-chain conditional random fields and support vector machines. Also we take a look which automatic text analysis methods provide useful features for the task. The data used for machine learning is supplied by Lingsoft Inc. and consists of subtitles in both compressed an uncompressed form. The models are compared to a baseline system and comparisons are made both automatically and also using human evaluation, because of the potentially subjective nature of the output. The best result is achieved using a CRF - sequence classification using a rich feature set. All text analysis methods help classification and most useful method is morphological analysis. Tutkielman aihe on suomenkielisten lauseiden automaattinen tiivistäminen koneellisesti, niin että lyhennetyt lauseet säilyttävät olennaisen informaationsa ja pysyvät kieliopillisina. Luonnollisen kielen lauseiden tiivistämiselle on monta käyttötarkoitusta, mutta tässä tutkielmassa aihetta lähestytään television ohjelmien tekstittämisen kautta, johon käytännössä kuuluu alkuperäisen tekstin lyhentäminen televisioruudulle paremmin sopivaksi. Tutkielmassa kokeillaan erilaisia koneoppimismenetelmiä tekstin automaatiseen lyhentämiseen ja tarkastellaan miten hyvin erilaiset luonnollisen kielen analyysimenetelmät tuottavat informaatiota, joka auttaa näitä menetelmiä lyhentämään lauseita. Lisäksi tarkastellaan minkälainen lähestymistapa tuottaa parhaan lopputuloksen. Käytetyt koneoppimismenetelmät ovat tukivektorikone ja lineaarisen sekvenssin mallinen CRF. Koneoppimisen tukena käytetään tekstityksiä niiden eri käsittelyvaiheissa, jotka on saatu Lingsoft OY:ltä. Luotuja malleja vertaillaan Lopulta mallien lopputuloksia evaluoidaan automaattisesti ja koska teksti lopputuksena on jossain määrin subjektiivinen myös ihmisarviointiin perustuen. Vertailukohtana toimii kirjallisuudesta poimittu menetelmä. Tutkielman tuloksena paras lopputulos saadaan aikaan käyttäen CRF sekvenssi-luokittelijaa laajalla piirrejoukolla. Kaikki kokeillut teksin analyysimenetelmät auttavat luokittelussa, joista tärkeimmän panoksen antaa morfologinen analyysi.

Implicit and explicit functions in the acquisition of a phonics rule in the word recognition of learning disabled and non learning disabled students /

One group of 12 non learning disabled students and two groups of 12 learning disabled students between the ges of 10 and 12 were measured on implicit and explicit knowledge cquisition. Students in each group implicitly cquired knowledge bout I of 2 vocabulary rules. The vocabulary rules governed the pronunciation of 2 types of pseudowords. After completing the implicit acquisition phase, all groups were administered a test of implicit knowledge. The non learning disabled group and I learning disabled group were then asked to verbalize the knowledge acquired during the initial phase. This was a test of explicit knowledge. All 3 groups were then given a postlest of implicit knowledge. This tcst was a measure of the effectiveness of the employment of the verbalization technique. Results indicate that implicit knowledge capabilities for both the learning disabled and non learning disabled groups were intact. However. there were significant differences between groups on explicit knowledge capabilities. This led to the conclusion that implicit functions show little individual differences, and that explicit functions are affected by ability difference. Furthermore, the employment of the verbalization technique significantly increased POStlest scores for learning disabled students. This suggested that the use of metacognitive techniques was a beneficial learning tool for learning disabled students.

Self-directed learning, lifelong learning and transformative learning in the Society for Creative Anachronism

This study examines the connection between leisure group participation and learning activities undertaken by participants in the Society for Creative Anachronism (SCA), a medieval recreationist group. The thesis of this connection was developed through the researcher's observations during SCA participation. The intent of this study is to understand adult learning from the self-directed learning, lifelong learning, and -transformative learning components derived from participant's SCA experiences. This qualitative study was conducted by interviewing eight active SCA participants, two in each participation theme of historical research, artistic representation, performance, and martial skills. Informants' responses demonstrated an integration of their leisure activity with learning. The contextualization of learning a s both a primary activity and a necessary support to participation, places learning a t the heart of participants' SCA related activities. The positive descriptions of learning activities, descriptive terms of ownership, and situating learning as an enjoyable activity engaged for the pleasure of the experience, provides adult educators with a fascinating glimpse of willing and engaged adult learners pursuing lifelong learning outside of the traditional educational structure. Two themes emerged during the interviews. First, bonding with others provided the motivation to continue their activities. Secondly, a feeling of commitment and helonging defined their enjoyment and satisfaction with SCA participation. The clear implications are that adult educators can create effective learning communities by developing educational structures that engage adult learners wi th meaningful social interaction.

Towards Evaluating and Modelling the Impacts of Mobile-Based Augmented Reality Applications on Learning and Engagement

Mobile augmented reality applications are increasingly utilized as a medium for enhancing learning and engagement in history education. Although these digital devices facilitate learning through immersive and appealing experiences, their design should be driven by theories of learning and instruction. We provide an overview of an evidence-based approach to optimize the development of mobile augmented reality applications that teaches students about history. Our research aims to evaluate and model the impacts of design parameters towards learning and engagement. The research program is interdisciplinary in that we apply techniques derived from design-based experiments and educational data mining. We outline the methodological and analytical techniques as well as discuss the implications of the anticipated findings.

Conceptual knowledge discovery and data analysis

In this paper, we discuss Conceptual Knowledge Discovery in Databases (CKDD) in its connection with Data Analysis. Our approach is based on Formal Concept Analysis, a mathematical theory which has been developed and proven useful during the last 20 years. Formal Concept Analysis has led to a theory of conceptual information systems which has been applied by using the management system TOSCANA in a wide range of domains. In this paper, we use such an application in database marketing to demonstrate how methods and procedures of CKDD can be applied in Data Analysis. In particular, we show the interplay and integration of data mining and data analysis techniques based on Formal Concept Analysis. The main concern of this paper is to explain how the transition from data to knowledge can be supported by a TOSCANA system. To clarify the transition steps we discuss their correspondence to the five levels of knowledge representation established by R. Brachman and to the steps of empirically grounded theory building proposed by A. Strauss and J. Corbin.

ONTIC: A Knowledge Representation System for Mathematics

Ontic is an interactive system for developing and verifying mathematics. Ontic's verification mechanism is capable of automatically finding and applying information from a library containing hundreds of mathematical facts. Starting with only the axioms of Zermelo-Fraenkel set theory, the Ontic system has been used to build a data base of definitions and lemmas leading to a proof of the Stone representation theorem for Boolean lattices. The Ontic system has been used to explore issues in knowledge representation, automated deduction, and the automatic use of large data bases.

Representation and Detection of Shapes in Images

We present a set of techniques that can be used to represent and detect shapes in images. Our methods revolve around a particular shape representation based on the description of objects using triangulated polygons. This representation is similar to the medial axis transform and has important properties from a computational perspective. The first problem we consider is the detection of non-rigid objects in images using deformable models. We present an efficient algorithm to solve this problem in a wide range of situations, and show examples in both natural and medical images. We also consider the problem of learning an accurate non-rigid shape model for a class of objects from examples. We show how to learn good models while constraining them to the form required by the detection algorithm. Finally, we consider the problem of low-level image segmentation and grouping. We describe a stochastic grammar that generates arbitrary triangulated polygons while capturing Gestalt principles of shape regularity. This grammar is used as a prior model over random shapes in a low level algorithm that detects objects in images.

The UK Professional Standards Framework for teaching and supporting learning in higher education

The UK Professional Standards Framework (UK PSF) for teaching and supporting learning, launched in February 2006, is a flexible framework which uses a descriptor-based approach to professional standards. There are three standard descriptors each of which is applicable to a number of staff roles and to different career stages of those engaged in teaching and supporting learning. The standard descriptors are underpinned by areas of professional activity, core knowledge and professional values. The framework provides a reference point for institutions and individuals as well as supporting ongoing development within any one standard descriptor.

Introduction to Knowledge Representation

Focussing on Open Data and the need for cleaning data

The Minimum core for language and literacy : knowledge, understanding and personal skills.

Guía práctica sobre lenguaje y alfabetización para profesores en formación (nivel bachillerato). Les permite identificar y desarrollar sus propias habilidades lingüísticas y de alfabetización y al mismo tiempo apoyar la evolución de los alumnos. Contiene todas las áreas claves de conocimiento, compresión y habilidades personales, además de analizar en un contexto amplio cómo el lenguaje y la alfabetización se adquieren y se desarrollan a nivel personal, social y cultural. El contenido está adaptado para la obtención de los certificados QTLS (Qualified Teacher, Learning and Skills) y ATLS (Associate Teacher, Learning and Skills).

The Minimum core for information and communication technology : knowledge, understanding and personal skills.

Guía práctica sobre tecnologías de la información y la comunicación para profesores en formación (nivel bachillerato). Les permite identificar y desarrollar sus propias habilidades tecnológicas aplicadas a la enseñanza y al mismo tiempo apoyar la evolución de los alumnos. Contiene todas las áreas claves de conocimiento, compresión y habilidades personales, además de analizar en un contexto amplio cómo las habilidades tecnológicas en información y comunicación se adquieren y se desarrollan a nivel personal, social y cultural. El contenido está adaptado para la obtención de los certificados QTLS (Qualified Teacher, Learning and Skills) y ATLS (Associate Teacher, Learning and Skills).

Providing pervasive learning eXperiences by combining Internet of Things and e-Learning standard

Resumen basado en el de la publicaci??n

Didactics–promoting collaborative work and personal learning environment. Critical, creative and autonomous roles in a competitive society

School has evolved from a place where knowledge is provided to a place where learners are helped to develop their professional and social skills. Consequently, education must evolve through big challenges in order to face the changes of society in the XXIst century

Digitisation, representation, and formalisation - Digital libraries of mathematics

One of the main tasks of the mathematical knowledge management community must surely be to enhance access to mathematics on digital systems. In this paper we present a spectrum of approaches to solving the various problems inherent in this task, arguing that a variety of approaches is both necessary and useful. The main ideas presented are about the differences between digitised mathematics, digitally represented mathematics and formalised mathematics. Each has its part to play in managing mathematical information in a connected world. Digitised material is that which is embodied in a computer file, accessible and displayable locally or globally. Represented material is digital material in which there is some structure (usually syntactic in nature) which maps to the mathematics contained in the digitised information. Formalised material is that in which both the syntax and semantics of the represented material, is automatically accessible. Given the range of mathematical information to which access is desired, and the limited resources available for managing that information, we must ensure that these resources are applied to digitise, form representations of or formalise, existing and new mathematical information in such a way as to extract the most benefit from the least expenditure of resources. We also analyse some of the various social and legal issues which surround the practical tasks.