20 research outputs found

    A new approach to automatically evaluate problems that are solved using diagrams

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    Automatic correction of problems that are solved using diagrams through educational platforms is of great importance, especially in the field of engineering studies. In this paper, we present a new strategy to automatically assess diagrams. The proposed approach is described in detail as well as its application to assess entity/relationship diagrams used in the conceptual design of databases. The results indicate that the differences between manual and automatic assessment is less than 075 points over a total of ten which confirms the validity of the proposed approach. As a conclusion, the validity of the proposed method to assess entity/relationship diagrams reducing teacher correction time and unifying applied correction criteria is corroborated

    Automatic Feedback for UML Modeling Exercises as an Extension of INLOOP

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    In recent years, e-learning systems have become an important part of normal and university education. One reason for this is the growth in student numbers. INLOOP is an assessment system for object-oriented programming and is used in a beginner software engineering course of the TU Dresden. Unfortunately, for the course, there is no assessment system for object-oriented modeling. This thesis extends the INLOOP concept with functionality to assess object-oriented modeling. For that, it introduces INLOOM as a constraint-based model assessment system that works well with the architecture and workflow of INLOOP. It is based on a two-stage system that generates constraint-based test sets out of expert solution models and uses these to generate feedback and a score for a student's solution model. The system was designed by first surveying the literature on model assessment systems and then creating a design that is easy to include into INLOOP. To assess the new INLOOM system, a proof-of-concept realization for analysis UML class models is introduced. For evaluation, this realization is used to assess student solutions for tasks of multiple exams. The results of the assessment system are then compared with the assessments of human instructors. It could be shown that the INLOOM system works as well as other comparable systems. In conclusion, the INLOOM system can be used alongside INLOOP to improve the student feedback in the beginner software engineering course

    A Similarity Based Concordance Approach to Word Sense Disambiguation

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    This study attempts to solve the problem of Word Sense Disambiguation using a combination of statistical, probabilistic and word matching algorithms. These algorithms consider that words and sentences have some hidden similarities and that the polysemous words in any context should be assigned to a sense after each execution of the algorithm. The algorithm was tested with sufficient sample data and the efficiency of the disambiguation performance has proven to increase significantly after the inclusion of the concordance methodology

    A Similarity Based Concordance Approach to Word Sense Disambiguation

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    This study attempts to solve the problem of Word Sense Disambiguation using a combination of statistical, probabilistic and word matching algorithms. These algorithms consider that words and sentences have some hidden similarities and that the polysemous words in any context should be assigned to a sense after each execution of the algorithm. The algorithm was tested with sufficient sample data and the efficiency of the disambiguation performance has proven to increase significantly after the inclusion of the concordance methodology

    Model-Agnostic process modelling

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    Modeling techniques in Business Process Management often suffer from low adoption due to the variety of profiles found in organizations. This project aims to provide a novel alternative to BPM documentation, ATD, based on annotated process descriptions in natural language

    Framework to manage labels for e-assessment of diagrams

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    Automatic marking of coursework has many advantages in terms of resource benefits and consistency. Diagrams are quite common in many domains including computer science but marking them automatically is a challenging task. There has been previous research to accomplish this, but results to date have been limited. Much of the meaning of a diagram is contained in the labels and in order to automatically mark the diagrams the labels need to be understood. However the choice of labels used by students in a diagram is largely unrestricted and diversity of labels can be a problem while matching. This thesis has measured the extent of the diagram label matching problem and proposed and evaluated a configurable extensible framework to solve it. A new hybrid syntax matching algorithm has also been proposed and evaluated. This hybrid approach is based on the multiple existing syntax algorithms. Experiments were conducted on a corpus of coursework which was large scale, realistic and representative of UK HEI students. The results show that the diagram label matching is a substantial problem and cannot be easily avoided for the e-assessment of diagrams. The results also show that the hybrid approach was better than the three existing syntax algorithms. The results also show that the framework has been effective but only to limited extent and needs to be further refined for the semantic stage. The framework proposed in this Thesis is configurable and extensible. It can be extended to include other algorithms and set of parameters. The framework uses configuration XML, dynamic loading of classes and two design patterns namely strategy design pattern and facade design pattern. A software prototype implementation of the framework has been developed in order to evaluate it. Finally this thesis also contributes the corpus of coursework and an open source software implementation of the proposed framework. Since the framework is configurable and extensible, its software implementation can be extended and used by the research community.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

    Bridging the gap between textual and formal business process representations

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    Tesi en modalitat de compendi de publicacionsIn the era of digital transformation, an increasing number of organizations are start ing to think in terms of business processes. Processes are at the very heart of each business, and must be understood and carried out by a wide range of actors, from both technical and non-technical backgrounds alike. When embracing digital transformation practices, there is a need for all involved parties to be aware of the underlying business processes in an organization. However, the representational complexity and biases of the state-of-the-art modeling notations pose a challenge in understandability. On the other hand, plain language representations, accessible by nature and easily understood by everyone, are often frowned upon by technical specialists due to their ambiguity. The aim of this thesis is precisely to bridge this gap: Between the world of the techni cal, formal languages and the world of simpler, accessible natural languages. Structured as an article compendium, in this thesis we present four main contributions to address specific problems in the intersection between the fields of natural language processing and business process management.A l’era de la transformació digital, cada vegada més organitzacions comencen a pensar en termes de processos de negoci. Els processos són el nucli principal de tota empresa i, com a tals, han de ser fàcilment comprensibles per un ampli ventall de rols, tant perfils tècnics com no-tècnics. Quan s’adopta la transformació digital, és necessari que totes les parts involucrades estiguin ben informades sobre els protocols implantats com a part del procés de digitalització. Tot i això, la complexitat i biaixos de representació dels llenguatges de modelització que actualment conformen l’estat de l’art sovint en dificulten la seva com prensió. D’altra banda, les representacions basades en documentació usant llenguatge natural, accessibles per naturalesa i fàcilment comprensibles per tothom, moltes vegades són vistes com un problema pels perfils més tècnics a causa de la presència d’ambigüitats en els textos. L’objectiu d’aquesta tesi és precisament el de superar aquesta distància: La distància entre el món dels llenguatges tècnics i formals amb el dels llenguatges naturals, més accessibles i senzills. Amb una estructura de compendi d’articles, en aquesta tesi presentem quatre grans línies de recerca per adreçar problemes específics en aquesta intersecció entre les tecnologies d’anàlisi de llenguatge natural i la gestió dels processos de negoci.Postprint (published version

    A Corpus-Based Analysis of Cohesion in L2 Writing by Undergraduates in Ecuador

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    In finding out the nature of cohesion in L2 writing, the present study set out to address three research questions: (1) What types of cohesion relations occur in L2 writing at the sentence, paragraph, and whole-text levels? (2) What is the relationship between lexico-grammatical cohesion features and teachers’ judgements of writing quality? (3) Do expectations of cohesion suggested by the CEFR match what is found in student writing? To answer those questions, a corpus of 240 essays and 240 emails from college- level students learning English as a foreign language in Ecuador enabled the analysis of cohesion. Each text included the scores, or teachers’ judgements of writing quality aligned to the upper-intermediate level (or B2) as proposed by the Common European Framework of Reference for learning, teaching, and assessing English as a foreign language. Lexical and grammatical items used by L2 students to build relationships of meaning in sentences, paragraphs, and the entire text were considered to analyse cohesion in L2 writing. Utilising Natural Language Processing tools (e.g., TAACO, TextInspector, NVivo), the analysis focused on determining which cohesion features (e.g., word repetition/overlap, semantical similarity, connective words) predicted the teachers’ judgements of writing quality in the collected essays and emails. The findings indicate that L2 writing is characterised by word overlap and synonyms occurring at the paragraph level and, to a lesser degree, cohesion between sentences and the entire text (e.g., connective words). Whilst these cohesion features positively and negatively predicted the teachers’ scores, a cautious interpretation of these findings is required, as many other factors beyond cohesion features must have also influenced the allocation of scores in L2 writing
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