13 research outputs found

    CONFLICTS IN THE MANAGEMENT OF RELIGIOUS SPONSORED PUBLIC SECONDARY SCHOOLS. EXPERIENCE FROM KENYA

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    Religious sponsors have in the past contributed immensely to the growth of education in Kenya. The purpose of this study was to find out the factors that lead to the management conflicts between religious sponsors and other stakeholders in public secondary schools in Nandi South Sub-County. The purpose of this study was to find out the factors that lead to the emerging conflicts between religious sponsors and head teachers, education officials, parents and schools’ Boards of Governors in the management of public secondary schools in Nandi South Sub-County. The survey research design was adopted for this study. The study population comprised of all the 38 religious sponsored Public Secondary Schools in Nandi South Sub-County, 38 Board of Governors’ Chairmen, 38 Parents and Teachers’ Association Chairmen, 38 head teachers and 342 teachers from the same schools, 6 education secretaries of the schools’ religious sponsors and 5 Assistant Education Officers. The saturated sampling technique was used by this study. Questionnaires and in-depth interviews were used to collect data. These instruments were first tested for reliability through a pilot study and the use of the coefficient of internal consistency of the split-half reliability method. Validity was established through the application of face validity procedures. Quantitative data were analyzed critically in themes as guided by study objectives to establish relationships among responses. The findings of the study indicated that most of the conflicts involved religious sponsors on one hand and other stakeholders. The study recommends that the Ministry of Education sensitizes the public secondary schools’ church sponsors, head teachers, Board of Governors and its field officers with regards to the correct interpretation of the Education Act as a tool in secondary schools’ management. The findings of this study would therefore provide a useful reference for educational administrators and managers.  Article visualizations

    Script acquisition : a crowdsourcing and text mining approach

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    According to Grice’s (1975) theory of pragmatics, people tend to omit basic information when participating in a conversation (or writing a narrative) under the assumption that left out details are already known or can be inferred from commonsense knowledge by the hearer (or reader). Writing and understanding of texts makes particular use of a specific kind of common-sense knowledge, referred to as script knowledge. Schank and Abelson (1977) proposed Scripts as a model of human knowledge represented in memory that stores the frequent habitual activities, called scenarios, (e.g. eating in a fast food restaurant, etc.), and the different courses of action in those routines. This thesis addresses measures to provide a sound empirical basis for high-quality script models. We work on three key areas related to script modeling: script knowledge acquisition, script induction and script identification in text. We extend the existing repository of script knowledge bases in two different ways. First, we crowdsource a corpus of 40 scenarios with 100 event sequence descriptions (ESDs) each, thus going beyond the size of previous script collections. Second, the corpus is enriched with partial alignments of ESDs, done by human annotators. The crowdsourced partial alignments are used as prior knowledge to guide the semi-supervised script-induction algorithm proposed in this dissertation. We further present a semi-supervised clustering approach to induce script structure from crowdsourced descriptions of event sequences by grouping event descriptions into paraphrase sets and inducing their temporal order. The proposed semi-supervised clustering model better handles order variation in scripts and extends script representation formalism, Temporal Script graphs, by incorporating "arbitrary order" equivalence classes in order to allow for the flexible event order inherent in scripts. In the third part of this dissertation, we introduce the task of scenario detection, in which we identify references to scripts in narrative texts. We curate a benchmark dataset of annotated narrative texts, with segments labeled according to the scripts they instantiate. The dataset is the first of its kind. The analysis of the annotation shows that one can identify scenario references in text with reasonable reliability. Subsequently, we proposes a benchmark model that automatically segments and identifies text fragments referring to given scenarios. The proposed model achieved promising results, and therefore opens up research on script parsing and wide coverage script acquisition.Gemäß der Grice’schen (1975) Pragmatiktheorie neigen Menschen dazu, grundlegende Informationen auszulassen, wenn sie an einem Gespräch teilnehmen (oder eine Geschichte schreiben). Dies geschieht unter der Annahme, dass die ausgelassenen Details bereits bekannt sind, oder vom Hörer (oder Leser) aus Weltwissen erschlossen werden können. Besonders beim Schreiben und Verstehen von Text wird Verwendung einer spezifischen Art von solchem Weltwissen gemacht, welches auch Skriptwissen genannt wird. Schank und Abelson (1977) erdachten Skripte als ein Modell menschlichen Wissens, welches im menschlichen Gedächtnis gespeichert ist und häufige Alltags-Aktivitäten sowie deren typischen Ablauf beinhaltet. Solche Skript-Aktivitäten werden auch als Szenarios bezeichnet und umfassen zum Beispiel Im Restaurant Essen etc. Diese Dissertation widmet sich der Bereitstellung einer soliden empirischen Grundlage zur Akquisition qualitativ hochwertigen Skriptwissens. Wir betrachten drei zentrale Aspekte im Bereich der Skriptmodellierung: Akquisition ition von Skriptwissen, Skript-Induktion und Skriptidentifizierung in Text. Wir erweitern das bereits bestehende Repertoire und Skript-Datensätzen in 2 Bereichen. Erstens benutzen wir Crowdsourcing zur Erstellung eines Korpus, das 40 Szenarien mit jeweils 100 Ereignissequenzbeschreibungen (Event Sequence Descriptions, ESDs) beinhaltet, und welches somit größer als bestehende Skript- Datensätze ist. Zweitens erweitern wir das Korpus mit partiellen ESD-Alignierungen, die von Hand annotiert werden. Die partiellen Alignierungen werden dann als Vorwissen für einen halbüberwachten Algorithmus zur Skriptinduktion benutzt, der im Rahmen dieser Dissertation vorgestellt wird. Wir präsentieren außerdem einen halbüberwachten Clusteringansatz zur Induktion von Skripten, basierend auf Ereignissequenzen, die via Crowdsourcing gesammelt wurden. Hierbei werden einzelne Ereignisbeschreibungen gruppiert, um Paraphrasenmengen und der deren temporale Ordnung abzuleiten. Der vorgestellte Clusteringalgorithmus ist im Stande, Variationen in der typischen Reihenfolge in Skripte besser abzubilden und erweitert damit einen Formalismus zur Skriptrepräsentation, temporale Skriptgraphen. Dies wird dadurch bewerkstelligt, dass Equivalenzklassen von Beschreibungen mit "arbiträrer Reihenfolge" genutzt werden, die es erlauben, eine flexible Ereignisordnung abzubilden, die inhärent bei Skripten vorhanden ist. Im dritten Teil der vorliegenden Arbeit führen wir den Task der SzenarioIdentifikation ein, also der automatischen Identifikation von Skriptreferenzen in narrativen Texten. Wir erstellen einen Benchmark-Datensatz mit annotierten narrativen Texten, in denen einzelne Segmente im Bezug auf das Skript, welches sie instantiieren, markiert wurden. Dieser Datensatz ist der erste seiner Art. Eine Analyse der Annotation zeigt, dass Referenzen zu Szenarien im Text mit annehmbarer Akkuratheit vorhergesagt werden können. Zusätzlich stellen wir ein Benchmark-Modell vor, welches Textfragmente automatisch erstellt und deren Szenario identifiziert. Das vorgestellte Modell erreicht erfolgversprechende Resultate und öffnet damit einen Forschungszweig im Bereich des Skript-Parsens und der Skript-Akquisition im großen Stil

    KenSwQuAD -- A Question Answering Dataset for Swahili Low Resource Language

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    The need for Question Answering datasets in low resource languages is the motivation of this research, leading to the development of Kencorpus Swahili Question Answering Dataset, KenSwQuAD. This dataset is annotated from raw story texts of Swahili low resource language, which is a predominantly spoken in Eastern African and in other parts of the world. Question Answering (QA) datasets are important for machine comprehension of natural language for tasks such as internet search and dialog systems. Machine learning systems need training data such as the gold standard Question Answering set developed in this research. The research engaged annotators to formulate QA pairs from Swahili texts collected by the Kencorpus project, a Kenyan languages corpus. The project annotated 1,445 texts from the total 2,585 texts with at least 5 QA pairs each, resulting into a final dataset of 7,526 QA pairs. A quality assurance set of 12.5% of the annotated texts confirmed that the QA pairs were all correctly annotated. A proof of concept on applying the set to the QA task confirmed that the dataset can be usable for such tasks. KenSwQuAD has also contributed to resourcing of the Swahili language.Comment: 17 pages, 1 figure, 10 table

    Rethinking Instructional Leadership Roles of the School Principal: Challenges and Prospects

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    In most schools, the individual charged with the responsibility for overseeing the general running of the programs and events is the principal. According to Lunenberg (1995), "the principal's job is to help the school achieve a high level of performance through utilization of its human and material resources. More simply, the principal's job is to get things done by working with and through other people" (p. 3). In this sense , he argued, principals are universal and are essential to schools of all types and sizes - wealthy, poor, rural, urban, large, and small.This article argues that the principal's tasks, especially those associated with instructional leadership, in meeting the needs and concerns of ever-changing schools are numerous, complex, and challenging. In this argument, the principal's instructional leadership roles, the major constraints in the ro le of the principal as an instructional leader, and the strategies for alleviating the problems are examined

    Acquiring Relational patterns from Wikipedia: A Case Study

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    This paper proposes the automatic acquisition of binary relational patterns (i.e. portions of text expressing a relation between two entities) from Wikipedia. There are a few advantages behind the use of Wikipedia: (i) relations are represented in the DBpedia ontology, which provides a repository of concepts to be used as semantic variables within patterns; (ii) most of the DBpedia relations appear in Wikipedia infoboxes, and are likely to be expressed in the corresponding pages, which increases the effectiveness of the extraction process; (iii) finally, as Wikipedia has pages in several languages, this opens the possibility for the acquisition of multilingual relational patterns. We show that a relatively simple methodology performs quite well on a set of selected DBpedia relations, for which a benchmark has been realized
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