To overcome constrained resources, firms can actively seek innovative opportunities from the external world. This innovation approach, called open innovation (Chesbrough 2003; Hippel 2005; Terwiesch and Ulrich 2009; Terwiesch and Xu 2008), is receiving more and more attention. Facilitated by the global Internet and emerging forms of information technology, it has become very easy for companies to generate large numbers of innovative solutions through the use of online open innovation contests or crowdsourcing contests (Archak and Sundararajan 2009; Terwiesch and Ulrich 2009; Terwiesch and Xu 2008; Yang et al. 2009).For an innovation project to succeed, it is necessary to generate not only a large number of good ideas or solutions, but also to identify those that are "exceptional" (Terwiesch and Ulrich 2009). This dissertation contains three studies that aim to improve our understanding of how best to use contests as a tool to aggregate external resources (collective intelligence) in the generation and evaluation of solutions. The first study views an innovation contest from the innovation seeker's perspective and provides insights on how to improve contest performance. The second study views an innovation contest from the innovation solver's perspective examining the characteristics and strategies of winners and solvers. Finally, in the third study, a new approach to the solution evaluation process is introduced, which is referred to as open evaluation. In this approach, a prediction market is used as an aggregation mechanism to coordinate the crowd in the evaluation of proposed solutions. These three studies make a number of contributions to the literature, addressing core issues in the area of online innovation contests. The analyses, which leverage large-scale empirical data, produce a number of profound results, which can help people to understand how best to use and design innovation contests in an online environment, for idea generation. Further, these studies present a variety of managerial implications associated with the aggregation of individual effort (collective intelligence) to evaluate the ideas that are generated by an innovation contest. We hope that our studies can help open innovation pioneers, such as Google, to systematically generate and identify exceptionally good ideas at much lower costs. By utilizing our findings, we expect that more firms will be able to adopt an open innovation strategy, both systematically and easily. / Business Administration/Management Information Systems

In supervised learning, it is usually assumed that true labels are readily available from a single annotator or source. However, recent advances in corroborative technology have given rise to situations where the true label of the target is unknown. In such problems, multiple sources or annotators are often available that provide noisy labels of the targets. In these multi-annotator problems, building a classifier in the traditional single-annotator manner, without regard for the annotator properties may not be effective in general. In recent years, how to make the best use of the labeling information provided by multiple annotators to approximate the hidden true concept has drawn the attention of researchers in machine learning and data mining. In our previous work, a probabilistic method (i.e., MAP-ML algorithm) of iteratively evaluating the different annotators and giving an estimate of the hidden true labels is developed. However, the method assumes the error rate of each annotator is consistent across all the input data. This is an impractical assumption in many cases since annotator knowledge can fluctuate considerably depending on the groups of input instances. In this dissertation, one of our proposed methods, GMM-MAPML algorithm, follows MAP-ML but relaxes the data-independent assumption, i.e., we assume an annotator may not be consistently accurate across the entire feature space. GMM-MAPML uses a Gaussian mixture model (GMM) and Bayesian information criterion (BIC) to find the fittest model to approximate the distribution of the instances. Then the maximum a posterior (MAP) estimation of the hidden true labels and the maximum-likelihood (ML) estimation of quality of multiple annotators at each Gaussian component are provided alternately. Recent studies show that it is not the case that employing more annotators regardless of their expertise will result in improved highest aggregating performance. In this dissertation, we also propose a novel algorithm to integrate multiple annotators by Aggregating Experts and Filtering Novices, which we call AEFN. AEFN iteratively evaluates annotators, filters the low-quality annotators, and re-estimates the labels based only on information obtained from the good annotators. The noisy annotations we integrate are from any combination of human and previously existing machine-based classifiers, and thus AEFN can be applied to many real-world problems. Emotional speech classification, CASP9 protein disorder prediction, and biomedical text annotation experiments show a significant performance improvement of the proposed methods (i.e., GMM-MAPML and AEFN) as compared to the majority voting baseline and the previous data-independent MAP-ML method. Recent experiments include predicting novel drug indications (i.e., drug repositioning) for both approved drugs and new molecules by integrating multiple chemical, biological or phenotypic data sources. / Computer and Information Science

Bacterial taxonomy is the science of classifying, naming, and identifying bacteria. The scope and practice of taxonomy has evolved through history with our understanding of life and our growing and changing needs in research, medicine, and industry. As in animal and plant taxonomy, the species is the fundamental unit of taxonomy, but the genetic and phenotypic diversity that exists within a single bacterial species is substantially higher compared to animal or plant species. Therefore, the current "type"-centered classification scheme that describes a species based on a single type strain is not sufficient to classify bacterial diversity, in particular in regard to human, animal, and plant pathogens, for which it is necessary to trace disease outbreaks back to their source. Here we discuss the current needs and limitations of classic bacterial taxonomy and introduce LINbase, a Web service that not only implements current species-based bacterial taxonomy but complements its limitations by providing a new framework for genome sequence-based classification and identification independently of the type-centric species. LINbase uses a sequence similarity-based framework to cluster bacteria into hierarchical taxa, which we call LINgroups, at multiple levels of relatedness and crowdsources users' expertise by encouraging them to circumscribe these groups as taxa from the genus-level to the intraspecies-level. Circumscribing a group of bacteria as a LINgroup, adding a phenotypic description, and giving the LINgroup a name using the LINbase Web interface allows users to instantly share new taxa and complements the lengthy and laborious process of publishing a named species. Furthermore, unknown isolates can be identified immediately as members of a newly described LINgroup with fast and precise algorithms based on their genome sequences, allowing species- and intraspecies-level identification. The employed algorithms are based on a combination of the alignment-based algorithm BLASTN and the alignment-free method Sourmash, which is based on k-mers, and the MinHash algorithm. The potential of LINbase is shown by using examples of plant pathogenic bacteria. / Doctor of Philosophy / Life is always easier when people talk to each other in the same language. Taxonomy is the language that biologists use to communicate about life by 1. classifying organisms into groups, 2. giving names to these groups, and 3. identifying individuals as members of these named groups. When most scientists and the general public think of taxonomy, they think of the hierarchical structure of “Life”, “Domain”, “Kingdom”, “Phylum”, “Class”, “Order”, “Family”, “Genus” and “Species”. However, the basic goal of taxonomy is to allow the identification of an organism as a member of a group that is predictive of its characteristics and to provide a name to communicate about that group with other scientists and the public. In the world of micro-organism, taxonomy is extremely important since there are an estimated 10,000,000 to 1,000,000,000 different bacteria species. Moreover, microbiologists and pathologists need to consider differences among bacterial isolates even within the same species, a level, that the current taxonomic system does not even cover. Therefore, we developed a Web service, LINbase, which uses genome sequences to classify individual microbial isolates. The database at the backend of LINbase assigns Life Identification Numbers (LINs) that express how individual microbial isolates are related to each other above, at, and below the species level. The LINbase Web service is designed to be an interactive web-based encyclopedia of microorganisms where users can share everything they know about micro-organisms, be it individual isolates or groups of isolates, for professional and scientific purposes. To develop LINbase, efficient computer programs were developed and implemented. To show how LINbase can be used, several groups of bacteria that cause plant diseases were classified and described.

No description available.

Natural Language Processing (NLP) is an interdisciplinary research field of Computer Science, Linguistics, and Pattern Recognition that studies, among others, the use of human natural languages in Human-Computer Interaction (HCI). Most of NLP research tasks can be applied for solving real-world problems. This is the case of natural language recognition and natural language translation, that can be used for building automatic systems for document transcription and document translation. Regarding digitalised handwritten text documents, transcription is used to obtain an easy digital access to the contents, since simple image digitalisation only provides, in most cases, search by image and not by linguistic contents (keywords, expressions, syntactic or semantic categories). Transcription is even more important in historical manuscripts, since most of these documents are unique and the preservation of their contents is crucial for cultural and historical reasons. The transcription of historical manuscripts is usually done by paleographers, who are experts on ancient script and vocabulary. Recently, Handwritten Text Recognition (HTR) has become a common tool for assisting paleographers in their task, by providing a draft transcription that they may amend with more or less sophisticated methods. This draft transcription is useful when it presents an error rate low enough to make the amending process more comfortable than a complete transcription from scratch. Thus, obtaining a draft transcription with an acceptable low error rate is crucial to have this NLP technology incorporated into the transcription process. The work described in this thesis is focused on the improvement of the draft transcription offered by an HTR system, with the aim of reducing the effort made by paleographers for obtaining the actual transcription on digitalised historical manuscripts. This problem is faced from three different, but complementary, scenarios: · Multimodality: The use of HTR systems allow paleographers to speed up the manual transcription process, since they are able to correct on a draft transcription. Another alternative is to obtain the draft transcription by dictating the contents to an Automatic Speech Recognition (ASR) system. When both sources (image and speech) are available, a multimodal combination is possible and an iterative process can be used in order to refine the final hypothesis. · Interactivity: The use of assistive technologies in the transcription process allows one to reduce the time and human effort required for obtaining the actual transcription, given that the assistive system and the palaeographer cooperate to generate a perfect transcription. Multimodal feedback can be used to provide the assistive system with additional sources of information by using signals that represent the whole same sequence of words to transcribe (e.g. a text image, and the speech of the dictation of the contents of this text image), or that represent just a word or character to correct (e.g. an on-line handwritten word). · Crowdsourcing: Open distributed collaboration emerges as a powerful tool for massive transcription at a relatively low cost, since the paleographer supervision effort may be dramatically reduced. Multimodal combination allows one to use the speech dictation of handwritten text lines in a multimodal crowdsourcing platform, where collaborators may provide their speech by using their own mobile device instead of using desktop or laptop computers, which makes it possible to recruit more collaborators. / El Procesamiento del Lenguaje Natural (PLN) es un campo de investigación interdisciplinar de las Ciencias de la Computación, Lingüística y Reconocimiento de Patrones que estudia, entre otros, el uso del lenguaje natural humano en la interacción Hombre-Máquina. La mayoría de las tareas de investigación del PLN se pueden aplicar para resolver problemas del mundo real. Este es el caso del reconocimiento y la traducción del lenguaje natural, que se pueden utilizar para construir sistemas automáticos para la transcripción y traducción de documentos. En cuanto a los documentos manuscritos digitalizados, la transcripción se utiliza para facilitar el acceso digital a los contenidos, ya que la simple digitalización de imágenes sólo proporciona, en la mayoría de los casos, la búsqueda por imagen y no por contenidos lingüísticos. La transcripción es aún más importante en el caso de los manuscritos históricos, ya que la mayoría de estos documentos son únicos y la preservación de su contenido es crucial por razones culturales e históricas. La transcripción de manuscritos históricos suele ser realizada por paleógrafos, que son personas expertas en escritura y vocabulario antiguos. Recientemente, los sistemas de Reconocimiento de Escritura (RES) se han convertido en una herramienta común para ayudar a los paleógrafos en su tarea, la cual proporciona un borrador de la transcripción que los paleógrafos pueden corregir con métodos más o menos sofisticados. Este borrador de transcripción es útil cuando presenta una tasa de error suficientemente reducida para que el proceso de corrección sea más cómodo que una completa transcripción desde cero. Por lo tanto, la obtención de un borrador de transcripción con una baja tasa de error es crucial para que esta tecnología de PLN sea incorporada en el proceso de transcripción. El trabajo descrito en esta tesis se centra en la mejora del borrador de transcripción ofrecido por un sistema RES, con el objetivo de reducir el esfuerzo realizado por los paleógrafos para obtener la transcripción de manuscritos históricos digitalizados. Este problema se enfrenta a partir de tres escenarios diferentes, pero complementarios: · Multimodalidad: El uso de sistemas RES permite a los paleógrafos acelerar el proceso de transcripción manual, ya que son capaces de corregir en un borrador de la transcripción. Otra alternativa es obtener el borrador de la transcripción dictando el contenido a un sistema de Reconocimiento Automático de Habla. Cuando ambas fuentes están disponibles, una combinación multimodal de las mismas es posible y se puede realizar un proceso iterativo para refinar la hipótesis final. · Interactividad: El uso de tecnologías asistenciales en el proceso de transcripción permite reducir el tiempo y el esfuerzo humano requeridos para obtener la transcripción correcta, gracias a la cooperación entre el sistema asistencial y el paleógrafo para obtener la transcripción perfecta. La realimentación multimodal se puede utilizar en el sistema asistencial para proporcionar otras fuentes de información adicionales con señales que representen la misma secuencia de palabras a transcribir (por ejemplo, una imagen de texto, o la señal de habla del dictado del contenido de dicha imagen de texto), o señales que representen sólo una palabra o carácter a corregir (por ejemplo, una palabra manuscrita mediante una pantalla táctil). · Crowdsourcing: La colaboración distribuida y abierta surge como una poderosa herramienta para la transcripción masiva a un costo relativamente bajo, ya que el esfuerzo de supervisión de los paleógrafos puede ser drásticamente reducido. La combinación multimodal permite utilizar el dictado del contenido de líneas de texto manuscrito en una plataforma de crowdsourcing multimodal, donde los colaboradores pueden proporcionar las muestras de habla utilizando su propio dispositivo móvil en lugar de usar ordenadores, / El Processament del Llenguatge Natural (PLN) és un camp de recerca interdisciplinar de les Ciències de la Computació, la Lingüística i el Reconeixement de Patrons que estudia, entre d'altres, l'ús del llenguatge natural humà en la interacció Home-Màquina. La majoria de les tasques de recerca del PLN es poden aplicar per resoldre problemes del món real. Aquest és el cas del reconeixement i la traducció del llenguatge natural, que es poden utilitzar per construir sistemes automàtics per a la transcripció i traducció de documents. Quant als documents manuscrits digitalitzats, la transcripció s'utilitza per facilitar l'accés digital als continguts, ja que la simple digitalització d'imatges només proporciona, en la majoria dels casos, la cerca per imatge i no per continguts lingüístics (paraules clau, expressions, categories sintàctiques o semàntiques). La transcripció és encara més important en el cas dels manuscrits històrics, ja que la majoria d'aquests documents són únics i la preservació del seu contingut és crucial per raons culturals i històriques. La transcripció de manuscrits històrics sol ser realitzada per paleògrafs, els quals són persones expertes en escriptura i vocabulari antics. Recentment, els sistemes de Reconeixement d'Escriptura (RES) s'han convertit en una eina comuna per ajudar els paleògrafs en la seua tasca, la qual proporciona un esborrany de la transcripció que els paleògrafs poden esmenar amb mètodes més o menys sofisticats. Aquest esborrany de transcripció és útil quan presenta una taxa d'error prou reduïda perquè el procés de correcció siga més còmode que una completa transcripció des de zero. Per tant, l'obtenció d'un esborrany de transcripció amb un baixa taxa d'error és crucial perquè aquesta tecnologia del PLN siga incorporada en el procés de transcripció. El treball descrit en aquesta tesi se centra en la millora de l'esborrany de la transcripció ofert per un sistema RES, amb l'objectiu de reduir l'esforç realitzat pels paleògrafs per obtenir la transcripció de manuscrits històrics digitalitzats. Aquest problema s'enfronta a partir de tres escenaris diferents, però complementaris: · Multimodalitat: L'ús de sistemes RES permet als paleògrafs accelerar el procés de transcripció manual, ja que són capaços de corregir un esborrany de la transcripció. Una altra alternativa és obtenir l'esborrany de la transcripció dictant el contingut a un sistema de Reconeixement Automàtic de la Parla. Quan les dues fonts (imatge i parla) estan disponibles, una combinació multimodal és possible i es pot realitzar un procés iteratiu per refinar la hipòtesi final. · Interactivitat: L'ús de tecnologies assistencials en el procés de transcripció permet reduir el temps i l'esforç humà requerits per obtenir la transcripció real, gràcies a la cooperació entre el sistema assistencial i el paleògraf per obtenir la transcripció perfecta. La realimentació multimodal es pot utilitzar en el sistema assistencial per proporcionar fonts d'informació addicionals amb senyals que representen la mateixa seqüencia de paraules a transcriure (per exemple, una imatge de text, o el senyal de parla del dictat del contingut d'aquesta imatge de text), o senyals que representen només una paraula o caràcter a corregir (per exemple, una paraula manuscrita mitjançant una pantalla tàctil). · Crowdsourcing: La col·laboració distribuïda i oberta sorgeix com una poderosa eina per a la transcripció massiva a un cost relativament baix, ja que l'esforç de supervisió dels paleògrafs pot ser reduït dràsticament. La combinació multimodal permet utilitzar el dictat del contingut de línies de text manuscrit en una plataforma de crowdsourcing multimodal, on els col·laboradors poden proporcionar les mostres de parla utilitzant el seu propi dispositiu mòbil en lloc d'utilitzar ordinadors d'escriptori o portàtils, la qual cosa permet ampliar el nombr / Granell Romero, E. (2017). Advances on the Transcription of Historical Manuscripts based on Multimodality, Interactivity and Crowdsourcing [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/86137

[ES] Esta investigación plantea la relación entre la orientación al mercado de las empresas y el aprendizaje continuo organizativo, así como la influencia de la utilización de las redes sociales online y el crowdsourcing como herramientas idóneas para la aplicación de la estrategia de orientación al mercado. La revisión de la literatura sobre los constructos proporciona una visión detallada de su importancia en la gestión empresarial. Esta revisión describe el nacimiento, desarrollo y situación actual de las redes sociales online y describe el crowdsourcing como herramienta para captar información sobre el mercado y colaborar en la creación de nuevos productos y servicios. De esta forma, se apoya la estrategia de orientación al mercado y se fomenta el aprendizaje continuo organizacional. La investigación de mercado se ha realizado en empresas turísticas españolas, ya que suponen un porcentaje muy relevante del PIB español. Para el estudio se han seleccionado hoteles de cuatro y cinco estrellas porque poseen mayores recursos para digitalizar sus empresas y, por lo tanto, son susceptibles de aportar una información de mayor calidad. Las conclusiones del estudio indican la importancia que tiene para los turistas, y para los clientes de las empresas en general, la utilización de las redes sociales online. Por lo tanto, las empresas tienen la obligación de invertir recursos para explotar estas fuentes de información y así mejorar la calidad del servicio ofrecida a los clientes. Esta inversión redundará en una mayor satisfacción e implicará la captación de nuevos clientes. Las conclusiones también recomiendan el uso generalizado del crowdsourcing como herramienta indispensable para solucionar problemas de la empresa, captar nuevas ideas de los internautas y obtener opiniones sobre productos y servicios, colaborando así en la innovación continua en las empresas. Ambas herramientas suponen una fuente de información muy importante para la estrategia de orientación al mercado que a su vez fomenta el aprendizaje continuo organizacional, consiguiendo que la empresa obtenga ventajas competitivas sostenibles en el tiempo. / [CA] Aquesta investigació planteja la relació entre l'orientació al mercat de les empreses i l'aprenentatge continu organitzacional, així com la influència de la utilització de les xarxes socials online i el crowdsourcing com a eines idònies per a l'aplicació de l'estratègia d'orientació al mercat. La revisió de la literatura sobre els constructes proporciona una visió detallada de la seua importància en la gestió empresarial. Aquesta revisió descriu el naixement, desenvolupament i situació actual de les xarxes socials online i descriu el crowdsourcing com a eina per a captar informació sobre el mercat i col·laborar en la creació de nous productes i serveis. D'aquesta forma, es dona suport a l'estratègia d'orientació al mercat i es fomenta l'aprenentatge continu organitzacional. La investigació de mercat s'ha realitzat en empreses turístiques espanyoles, ja que suposen un percentatge molt rellevant del PIB espanyol. Per a l'estudi s'han seleccionat hotels de quatre i cinc estreles perquè posseeixen majors recursos per a digitalitzar les seues empreses i, per tant, són susceptibles d'aportar una informació de major qualitat. Les conclusions de l'estudi indiquen la importància que té per als turistes, i per als clients de les empreses en general, la utilització de les xarxes socials online. Per tant, les empreses tenen l'obligació d'invertir recursos per a explotar aquestes fonts d'informació i així millorar la qualitat del servei oferit als clients. Aquesta inversió redundarà en una major satisfacció i implicarà la captació de nous clients. Les conclusions també recomanen l'ús generalitzat del crowdsourcing com a eina indispensable per a solucionar problemes de l'empresa, captar noves idees dels internautes i obtindre opinions sobre productes i serveis, col·laborant així en la innovació contínua en les empreses. Totes dues eines suposen una font d'informació molt important per a l'estratègia d'orientació al mercat que al seu torn fomenta l'aprenentatge continu organitzacional, aconseguint que l'empresa obtinga avantatges competitius sostenibles en el temps. / [EN] This investigation raises the relationship between market orientation of companies and organizational continuous learning, as well as the influence of the use of online social networks and crowdsourcing as ideal tools for the application of the market orientation strategy. Reviewing the literature on constructs provides a detailed insight into their importance in business management. This review describes the birth, development and current situation of online social networks and describes crowdsourcing as a tool to capture information about the market and collaborate in the creation of new products and services. In this way, the market orientation strategy is supported and continuous organizational learning is encouraged. Market research has been carried out in Spanish tourism companies, since they represent a very relevant percentage of Spanish GDP. Four and five star hotels have been selected for the study because they have greater resources to digitize their companies and, therefore, are capable of providing higher quality information. The conclusions of the study indicate the importance of the use of online social networks for tourists, and for business customers in general. Therefore, companies have the obligation to invest resources to exploit these sources of information and thus improve the quality of service offered to customers. This investment will result in greater satisfaction and will involve the acquisition of new customers. The conclusions also recommend the widespread use of crowdsourcing as an indispensable tool to solve company problems, capture new ideas from Internet users and obtain opinions about products and services, thus collaborating in continuous innovation in companies. Both tools are a very important source of information for the market orientation strategy, which in turn encourages continuous organizational learning, ensuring that the company obtains sustainable competitive advantages over time. / Guaita Monreal, E. (2023). La orientación al mercado y la influencia de las redes sociales online y el crowdsourcing en el aprendizaje continuo organizativo en empresas del sector hotelero [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/198884

隨著科技日新月異的發展，智慧型手機本身通訊與運算能力也隨著軟體和硬體的改善而不斷地增強，其便利性與高機動性的特色使得越來越多人持有智慧型手機，最後成為人們生活中不可或缺的部份。總觀來說，持有與使用率的上升，不知不覺的形成一種共享經濟與無所不在的行動運算網絡。 基於普及性與相對優秀的運算效能，我們設計與實作出Gnafuy，一個基於行動裝置下的分散式運算框架，希望借用世界上所有閒置行動運算裝置的資源來實行無所不在的運算。 我們發展出一套應用程式介面(API)供開發者依照自己的需求來撰寫自己的分散式運算程式，藉由遵循Gnafuy所制定的應用程式介面，開發者可只專注在演算法本身的開發，而不需要在意其演算法如何被分配到手機上以及待處理資料的分配情形。本篇文章還討論了Gnafuy所採用的分散式運算的程式模型，以及我們如何藉由一個手機應用程式將任務部署至自願者的智慧型手機中，我們發展出一套伺服器端的機制來增加訊息傳遞的成功率，以及偵測計算後回傳結果是否正確，排除被惡意程式污染的客戶端結果。

This paper analyzes and critically evaluates present music and video market functioning with emphasis to the sales of electronic format of this content which is preferred by current customers. It analyzes the widespread trend of content sharing via the Internet and specifies reasons why the trend is happening. It defines cases of behavior that are justifiable in the eyes of consumers and therefore legitimate (i.e. creation of backups, downloading and sharing legally unavailable content, downloading for personal use, etc.) and elements that reduce value of the legally distributed content for the customer (copy protection mechanisms or current licensing system). Furthermore, it analyzes new economic approaches that enable the utilization potential of the Internet (i.e. the Long Tail Theory) or of potential customers (Crowdsourcing, Word of Mouth, Gamification). The paper analyzes the functioning new services that use the Internet as a platform for their operation and offer users the experience they want. Proposal for this new system of audiovisual content distribution is proposed based on a synthesis of findings from the operation of these services, new theoretical approaches and author's own contribution. This new system rejects the idea of selling the content as goods (per items) and adopts an approach of access to the whole catalogue of content for a flat monthly fee. This newly born service has several tiers that differ qualitatively among themselves, also in terms of added value for users and finally in the price at which the layers are available. This system is very acceptable to customers as well as being an interesting long-term alternative to the current system for operators of the new system and copyright holders.

"A common problem shared amongst online tutoring systems is the time-consuming nature of content creation. It has been estimated that an hour of online instruction can take up to 100-300 hours to create. Several systems have created tools to expedite content creation, such as the Cognitive Tutors Authoring Tool (CTAT) and the ASSISTments builder. Although these tools make content creation more efficient, they all still depend on the efforts of a content creator and/or past historical. These tools do not take full advantage of the power of the crowd. These issues and challenges faced by online tutoring systems provide an ideal environment to implement a solution using crowdsourcing. I created the PeerASSIST system to provide a solution to the challenges faced with tutoring content creation. PeerASSIST crowdsources the work students have done on problems inside the ASSISTments online tutoring system and redistributes that work as a form of tutoring to their peers, who are in need of assistance. Multi-objective multi-armed bandit algorithms are used to distribute student work, which balance exploring which work is good and exploiting the best currently known work. These policies are customized to run in a real-world environment with multiple asynchronous reward functions and an infinite number of actions. Inspired by major companies such as Google, Facebook, and Bing, PeerASSIST is also designed as a platform for simultaneous online experimentation in real-time and at scale. Currently over 600 teachers (grades K-12) are requiring students to show their work. Over 300,000 instances of student work have been collected from over 18,000 students across 28,000 problems. From the student work collected, 2,000 instances have been redistributed to over 550 students who needed help over the past few months. I conducted a randomized controlled experiment to evaluate the effectiveness of PeerASSIST on student performance. Other contributions include representing learning maps as Bayesian networks to model student performance, creating a machine-learning algorithm to derive student incorrect processes from their incorrect answer and the inputs of the problem, and applying Bayesian hypothesis testing to A/B experiments. We showed that learning maps can be simplified without practical loss of accuracy and that time series data is necessary to simplify learning maps if the static data is highly correlated. I also created several interventions to evaluate the effectiveness of the buggy messages generated from the machine-learned incorrect processes. The null results of these experiments demonstrate the difficulty of creating a successful tutoring and suggest that other methods of tutoring content creation (i.e. PeerASSIST) should be explored."

Submitted by Mariana Dornelles Vargas (marianadv) on 2015-05-25T17:54:35Z No. of bitstreams: 1 wedode.pdf: 3627779 bytes, checksum: 55a6860ad06d61a754ba43bf34960367 (MD5) / Made available in DSpace on 2015-05-25T17:54:35Z (GMT). No. of bitstreams: 1 wedode.pdf: 3627779 bytes, checksum: 55a6860ad06d61a754ba43bf34960367 (MD5) Previous issue date: 2012 / Nenhuma / A presente pesquisa tem como proposta a estruturação de metodologia de projeto chamada de Open Strategic Design (OSD) que teve por base o acervo de conhecimento produzido pelo design estratégico, e por motivação a necessidade de que essa metodologia estivesse alinhada ao contexto social contemporâneo, marcado pela lógica de consumo, pela interação hiperconectada e pela natureza simbólica das representações. Compreende-se o design como retórica que organiza os elementos de contexto (cultura de consumo e mediação tecnológica) e de linguagem (projeto, inovação aberta e design estratégico), e que, como tal, pode formular percursos estratégicos diferenciados. Daí resultou a construção de uma plataforma digital de projeto aberto e coletivo, o wedode.com, base da realização da experiência de aplicação e teste da proposta de OSD. A coletividade que participou da experiência produziu material que possibilitou a crítica da metodologia de projeto e insumos para alteração na plataforma usada. / The present research has as purpose the structuring of design methodology called Open Strategic Design (OSD) that was based on the collection of knowledge produced by the estrategic design, and motivated by the need for this methodology to be aligned with the contemporaneous social context, marked by the logic of consumption, hyper connected interaction and the nature of symbolic representations. We understand design as rhetoric that organizes the context elements (consumer culture and technological mediation) and language (project, open innovation and strategic design), and, as such, may make differentiated strategic paths. This led to the construction of a digital platform design open and collective, wedode.com, foundation of the application experience and testing of the proposed OSD. The group that participated in the experiment produced material that allowed criticism of the project methodology and insights to be used to change the platform.