146 research outputs found

    Enforcing Customization in e-Learning Systems: an ontology and product line-based approach

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    In the era of e-Learning, educational materials are considered a crucial point for all the stakeholders. On the one hand, instructors aim at creating learning materials that meet the needs and expectations of learners easily and effec-tively; On the other hand, learners want to acquire knowledge in a way that suits their characteristics and preferences. Consequently, the provision and customization of educational materials to meet the needs of learners is a constant challenge and is currently synonymous with technological devel-opment. Promoting the personalization of learning materials, especially dur-ing their development, will help to produce customized learning materials for specific learners' needs. The main objective of this thesis is to reinforce and strengthen Reuse, Cus-tomization and Ease of Production issues in e-Learning materials during the development process. The thesis deals with the design of a framework based on ontologies and product lines to develop customized Learning Objects (LOs). With this framework, the development of learning materials has the following advantages: (i) large-scale production, (ii) faster development time, (iii) greater (re) use of resources. The proposed framework is the main contribution of this thesis, and is char-acterized by the combination of three models: the Content Model, which addresses important points related to the structure of learning materials, their granularity and levels of aggregation; the Customization Model, which con-siders specific learner characteristics and preferences to customize the learn-ing materials; and the LO Product Line (LOPL) model, which handles the subject of variability and creates matter-them in an easy and flexible way. With these models, instructors can not only develop learning materials, but also reuse and customize them during development. An additional contribution is the Customization Model, which is based on the Learning Style Model (LSM) concept. Based on the study of seven of them, a Global Learning Style Model Ontology (GLSMO) has been con-structed to help instructors with information on the apprentice's characteris-tics and to recommend appropriate LOs for customization. The results of our work have been reflected in the design of an authoring tool for learning materials called LOAT. They have described their require-ments, the elements of their architecture, and some details of their user inter-face. As an example of its use, it includes a case study that shows how its use in the development of some learning components.En la era del e¿Learning, los materiales educativos se consideran un punto crucial para todos los participantes. Por un lado, los instructores tienen como objetivo crear materiales de aprendizaje que satisfagan las necesidades y ex-pectativas de los alumnos de manera fácil y efectiva; por otro lado, los alumnos quieren adquirir conocimientos de una manera que se adapte a sus características y preferencias. En consecuencia, la provisión y personaliza-ción de materiales educativos para satisfacer las necesidades de los estudian-tes es un desafío constante y es actualmente sinónimo de desarrollo tecnoló-gico. El fomento de la personalización de los materiales de aprendizaje, es-pecialmente durante su desarrollo, ayudará a producir materiales de aprendi-zaje específicos para las necesidades específicas de los alumnos. El objetivo fundamental de esta tesis es reforzar y fortalecer los temas de Reutilización, Personalización y Facilidad de Producción en materiales de e-Learning durante el proceso de desarrollo. La tesis se ocupa del diseño de un marco basado en ontologías y líneas de productos para desarrollar objetos de aprendizaje personalizados. Con este marco, el desarrollo de materiales de aprendizaje tiene las siguientes ventajas: (i) producción a gran escala, (ii) tiempo de desarrollo más rápido, (iii) mayor (re)uso de recursos. El marco propuesto es la principal aportación de esta tesis, y se caracteriza por la combinación de tres modelos: el Modelo de Contenido, que aborda puntos importantes relacionados con la estructura de los materiales de aprendizaje, su granularidad y niveles de agregación, el Modelo de Persona-lización, que considera las características y preferencias específicas del alumno para personalizar los materiales de aprendizaje, y el modelo de Línea de productos LO (LOPL), que maneja el tema de la variabilidad y crea ma-teriales de manera fácil y flexible. Con estos modelos, los instructores no sólo pueden desarrollar materiales de aprendizaje, sino también reutilizarlos y personalizarlos durante el desarrollo. Una contribución adicional es el modelo de personalización, que se basa en el concepto de modelo de estilo de aprendizaje. A partir del estudio de siete de ellos, se ha construido una Ontología de Modelo de Estilo de Aprendiza-je Global para ayudar a los instructores con información sobre las caracterís-ticas del aprendiz y recomendarlos apropiados para personalización. Los resultados de nuestro trabajo se han plasmado en el diseño de una he-rramienta de autor de materiales de aprendizaje llamada LOAT. Se han des-crito sus requisitos, los elementos de su arquitectura, y algunos detalles de su interfaz de usuario. Como ejemplo de su uso, se incluye un caso de estudio que muestra cómo su empleo en el desarrollo de algunos componentes de aprendizaje.En l'era de l'e¿Learning, els materials educatius es consideren un punt crucial per a tots els participants. D'una banda, els instructors tenen com a objectiu crear materials d'aprenentatge que satisfacen les necessitats i expectatives dels alumnes de manera fàcil i efectiva; d'altra banda, els alumnes volen ad-quirir coneixements d'una manera que s'adapte a les seues característiques i preferències. En conseqüència, la provisio' i personalitzacio' de materials edu-catius per a satisfer les necessitats dels estudiants és un desafiament constant i és actualment sinònim de desenvolupament tecnològic. El foment de la personalitzacio' dels materials d'aprenentatge, especialment durant el seu desenvolupament, ajudarà a produir materials d'aprenentatge específics per a les necessitats concretes dels alumnes. L'objectiu fonamental d'aquesta tesi és reforçar i enfortir els temes de Reutilització, Personalització i Facilitat de Producció en materials d'e-Learning durant el procés de desenvolupament. La tesi s'ocupa del disseny d'un marc basat en ontologies i línia de productes per a desenvolupar objec-tes d'aprenentatge personalitzats. Amb aquest marc, el desenvolupament de materials d'aprenentatge té els següents avantatges: (i) produccio' a gran esca-la, (ii) temps de desenvolupament mes ràpid, (iii) major (re)ús de recursos. El marc proposat és la principal aportacio' d'aquesta tesi, i es caracteritza per la combinacio' de tres models: el Model de Contingut, que aborda punts im-portants relacionats amb l'estructura dels materials d'aprenentatge, la se-ua granularitat i nivells d'agregació, el Model de Línia de Producte, que ges-tiona el tema de la variabilitat i crea materials d'aprenentatge de manera fàcil i flexible. Amb aquests models, els instructors no solament poden desenvolu-par materials d'aprenentatge, sinó que també poden reutilitzar-los i personalit-zar-los durant el desenvolupament. Una contribucio' addicional és el Model de Personalitzacio', que es basa en el concepte de model d'estil d'aprenentatge. A partir de l'estudi de set d'ells, s'ha construït una Ontologia de Model d'Estil d'Aprenentatge Global per a ajudar als instructors amb informacio' sobre les característiques de l'aprenent i recomanar els apropiats per a personalitzacio'. Els resultats del nostre treball s'han plasmat en el disseny d'una eina d'autor de materials d'aprenentatge anomenada LOAT. S'han descrit els seus requi-sits, els elements de la seua arquitectura, i alguns detalls de la seua interfície d'usuari. Com a exemple del seu ús, s'inclou un cas d'estudi que mostra com és el desenvolupament d'alguns components d'aprenentatge.Ezzat Labib Awad, A. (2017). Enforcing Customization in e-Learning Systems: an ontology and product line-based approach [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/90515TESI

    The role of well-being in consumer's responses to personalized advertising on social media

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    In two studies, this paper examines how perceived personalization in advertisements on social media affects brand engagement and ad avoidance. Using a preregistered between-subjects cross-sectional survey (n = 794), we tested four different moderated mediation models with perceived creepiness and perceived relevance as competing mediating variables, and hedonic and eudaimonic well-being as moderating variables. Perceived relevance explains the positive effect of perceived personalization on brand engagement and the negative effect on ad avoidance. Moreover, perceived creepiness explains the negative effect of perceived personalization on ad avoidance. Contrary to our hypotheses, we find positive effects of perceived personalization via perceived creepiness on brand engagement and ad avoidance. Then, a qualitative think-aloud survey (n = 36) shows that participants are accustomed to personalized advertisements and scroll to avoid them unless there is relevant or useful content. Independent of their well-being, participants are not creeped out because of personalized advertising; however, it does raise their privacy concerns. Finally, the findings of our two studies indicate that advertisers and social media need to particularly consider consumers' negative affective well-being to effectively deliver personalized advertisements due to the increase in creepiness and/or privacy concerns.</p

    Dyadic Speech-based Affect Recognition using DAMI-P2C Parent-child Multimodal Interaction Dataset

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    Automatic speech-based affect recognition of individuals in dyadic conversation is a challenging task, in part because of its heavy reliance on manual pre-processing. Traditional approaches frequently require hand-crafted speech features and segmentation of speaker turns. In this work, we design end-to-end deep learning methods to recognize each person's affective expression in an audio stream with two speakers, automatically discovering features and time regions relevant to the target speaker's affect. We integrate a local attention mechanism into the end-to-end architecture and compare the performance of three attention implementations -- one mean pooling and two weighted pooling methods. Our results show that the proposed weighted-pooling attention solutions are able to learn to focus on the regions containing target speaker's affective information and successfully extract the individual's valence and arousal intensity. Here we introduce and use a "dyadic affect in multimodal interaction - parent to child" (DAMI-P2C) dataset collected in a study of 34 families, where a parent and a child (3-7 years old) engage in reading storybooks together. In contrast to existing public datasets for affect recognition, each instance for both speakers in the DAMI-P2C dataset is annotated for the perceived affect by three labelers. To encourage more research on the challenging task of multi-speaker affect sensing, we make the annotated DAMI-P2C dataset publicly available, including acoustic features of the dyads' raw audios, affect annotations, and a diverse set of developmental, social, and demographic profiles of each dyad.Comment: Accepted by the 2020 International Conference on Multimodal Interaction (ICMI'20

    Behavlets: a Method for Practical Player Modelling using Psychology-Based Player Traits and Domain Specific Features

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    As player demographics broaden it has become important to understand variation in player types. Improved player models can help game designers create games that accommodate a range of play styles/preferences, and may also facilitate the design of systems that detect player type and adapt dynamically in real-time. Existing approaches can model players, but most focus on tracking and classifying behaviour based on simple functional metrics such as deaths, specific choices, player avatar attributes, and completion times. We describe a different approach which seeks to leverage expert domain knowledge using a theoretical framework linking behaviour and game design patterns. The aim is to derive features of play from sequences of actions which are intrinsically informative about behaviour – which, because they are directly interpretable with respect to psychological theory of behaviour, we name ‘Behavlets’. We present the theoretical underpinning of this approach from research areas including psychology, temperament theory, player modelling, and game composition. The Behavlet creation process is described in detail; illustrated using a clone of the well-known game Pac-Man, with data gathered from 100 participants. A workshop evaluation study is also presented, where nine game design expert participants were briefed on the Behavlet concepts and requisite models, and then attempted to apply the method to games of the well-known first/third-person shooter genres, exemplified by ‘Gears of War’, (Microsoft). The participants found 139 Behavlet concepts mapping from behavioural preferences of the temperament types, to design patterns of the shooter genre games. We conclude that the Behavlet approach has significant promise, is complementary to existing methods and can improve theoretical validity of player models.Peer reviewe

    Websites are capable of reflecting a particular human temperament : fact or fad?

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    This study suggests that it is possible to classify websites as either extrovert or introvert and logical or emotional in style, impact and appearance. Both the extraversion/ introversion and logical/emotional dichotomies are major descriptors in the character typology devised by C.G. Jung and extended by others. Apart from the dichotomies mentioned above, Jung’s typology also makes use of various emotional characteristics of human beings as descriptors of temperament or character. The study suggests that it is useful to identify websites in terms of the descriptors that Jung and others propose, and that different websites will display various “temperamental” differences that are as important for website design as is a clear understanding of the temperaments of its target users. By taking account of the most common temperamental differences in websites, it should be possible to maximise the efficiency and appearance of different kinds of websites such as those created for government agencies, banks, online shopping, social networking and search engines.Dissertation (MIT)--University of Pretoria, 2008.Informaticsunrestricte

    Guided generation of pedagogical concept maps from the Wikipedia

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    We propose a new method for guided generation of concept maps from open accessonline knowledge resources such as Wikies. Based on this method we have implemented aprototype extracting semantic relations from sentences surrounding hyperlinks in the Wikipedia’sarticles and letting a learner to create customized learning objects in real-time based oncollaborative recommendations considering her earlier knowledge. Open source modules enablepedagogically motivated exploration in Wiki spaces, corresponding to an intelligent tutoringsystem. The method extracted compact noun–verb–noun phrases, suggested for labeling arcsbetween nodes that were labeled with article titles. On average, 80 percent of these phrases wereuseful while their length was only 20 percent of the length of the original sentences. Experimentsindicate that even simple analysis algorithms can well support user-initiated information retrievaland building intuitive learning objects that follow the learner’s needs.Peer reviewe

    The relationship between computer interaction and individual user characteristics

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    Development of effective human computer interaction is being approached independently by two disciplines -- user interface design and computer aided instruction. The lack of communication between the two fields has left each separately pursuing different paths toward the same goals. This thesis attempts to bridge the gap between these two disciplines. An exploratory study was conducted to analyze whether user choices in a computer aided instruction environment and personality types as defined by the Myers-Briggs type indicator are related strongly enough to provide the basis for future user models. The results demonstrated that no single instructional strategy was preferred, implying the need for more than one user model. The amount of instruction chosen did not increase performance. These conclusions have impact on research efforts to understand how both user and system characteristics influence the use of computer technology. The current research efforts to incorporate artificial intelligence techniques by both user interface designers and computer aided instruction developers has heightened the need for knowledge-based systems incorporating interdisciplinary research efforts
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