Exploring creative thinking in graphically mediated synchronous dialogues

publication-status: Publishedtypes: ArticleThis paper reports on an aspect of the EC funded Argunaut project which researched and developed awareness tools for moderators of online dialogues. In this study we report on an investigation into the nature of creative thinking in online dialogues and whether or not this creative thinking can be coded for and recognized automatically such that moderators can be alerted when creative thinking is occurring or when it has not occurred after a period of time. We outline a dialogic theory of creativity, as the emergence of new perspectives from the interplay of voices, and the testing of this theory using a range of methods including a coding scheme which combined coding for creative thinking with more established codes for critical thinking, artificial intelligence pattern-matching techniques to see if our codes could be read automatically from maps and ‘key event recall’ interviews to explore the experience of participants. Our findings are that: (1) the emergence of new perspectives in a graphical dialogue map can be recognized by our coding scheme supported by a machine pattern-matching algorithm in a way that can be used to provide awareness indicators for moderators; (2) that the trigger events leading to the emergence of new perspectives in the online dialogues studied were most commonly disagreements and (3) the spatial representation of messages in a graphically mediated synchronous dialogue environment such as Digalo may offer more affordance for creativity than the much more common scrolling text chat environments. All these findings support the usefulness of our new account of creativity in online dialogues based on dialogic theory and demonstrate that this account can be operationalised through machine coding in a way that can be turned into alerts for moderators

Towards adaptive argumentation learning systems : theoretical and practical considerations in the design of argumentation learning systems

This dissertation addresses four issues of pivotal importance in realizing the promises of adaptive argumentation learning systems: (1) User interface: How can argumentation user interfaces be designed to effectively structure and support problem solving, peer interaction, and learning? (2) Software architecture: How can software architectures of adaptive argumentation learning systems be designed to be employable across different argumentation domains and application scenarios in a flexible and cost-effective manner? (3) Diagnostics: How can user behavior be analyzed, automatically and accurately, to drive automated adaptations and help generation? (4) Adaptation: How can strategies for automated adaptation and support be designed to promote problem solving, peer interaction, and learning in an optimal fashion? Regarding issue (1), this dissertation investigates argument diagrams and structured discussion interfaces, two areas of focal interest in argumentation learning research during the past decades. The foundation for such structuring approaches is given by theories of learning and teaching with knowledge representations (theory of representational guidance) and collaboration scripts (script theory of guidance in computer-supported collaborative learning). This dissertation brings these two strands of research together and presents a computer-based learning environment that combines both approaches to support students in conducting high-quality discussions of controversial texts. An empirical study confirms that this combined approach has positive impact on the quality of discussions, thus, underpins the theoretical basis of the approach. Regarding issue (2), this dissertation presents a software framework for enhancing argumentation systems with adaptive support mechanisms. Adaptive support functionality of past argumentation systems has been tailored to particular domains and application scenarios. A novel software framework is presented that abstracts from the specific demands of different domains and application scenarios to provide a more general approach. The approach comprises an extensive configuration subsystem that allows the flexible definition of intelligent software agents, that is, software components able to reason and act autonomously to help students engage in fruitful learning activities. A graphical authoring tool has been conceptualized and implemented to simplify the process of defining and administering software agents beyond what has been achieved with the provided framework system. Among other things, the authoring tool allows, for the first time, specifying relevant patterns in argument diagrams using a graphical language. Empirical results indicate the high potential of the authoring approach but also challenges for future research. Regarding issue (3), the dissertation investigates two alternative approaches to automatically analyzing argumentation learning activities: the knowledge-driven and the data-driven analysis method. The knowledge-driven approach utilizes a pattern search component to identify relevant structures in argument diagrams based on declarative pattern specifications. The capabilities and appropriateness of this approach are demonstrated through three exemplary applications, for which pedagogically relevant patterns have been defined and implemented within the component. The approach proves particularly useful for patterns of limited complexity in scenarios with sufficient expert knowledge available. The data-driven approach is based on machine learning techniques, which have been employed to induce computational classifiers for important aspects of graphical online discussions, such as off-topic contributions, reasoned claims, and question-answer interactions. Validation results indicate that this approach can be realistically used even for complex classification tasks involving natural language. This research constitutes the first investigation on the use of machine learning techniques to analyze diagram-based educational discussions. The dissertation concludes with discussing the four addressed research challenges in the broader context of existing theories and empirical results. The pros and cons of different options in the design of argumentation learning systems are juxtaposed; areas for future research are identified. This final part of the dissertation gives researchers and practitioners a synopsis of the current state of the art in the design of argumentation learning systems and its theoretical and empirical underpinning. Special attention is paid to issue (4), with an in-depth discussion of existing adaptation approaches and corresponding empirical results.Diese Dissertationsschrift behandelt die folgenden vier Fragestellungen, welche bei der Realisierung adaptiver Argumentationssysteme von zentraler Bedeutung sind: (1) Benutzerschnittstelle: Wie müssen Benutzerschnittstellen beschaffen sein, um Problemlöse-, Kooperations- und Lernprozesse effektiv zu strukturieren und zu unterstützen? (2) Softwarearchitektur: Wie können die Funktionalitäten eines adaptiven Argumentationslernsystems in eine Softwarearchitektur abgebildet werden, welche flexibel und mit angemessenem Aufwand in verschiedenen Bereichen und Szenarien einsetzbar ist? (3) Diagnostik: Wie kann Benutzerverhalten automatisch und mit hoher Genauigkeit analysiert werden, um automatisierte Anpassungen und Hilfestellungen effektiv zu steuern? (4) Adaption: Wie sollten automatisierte Anpassungen und Hilfestellungen ausgestaltet werden, um Problemlöse-, Kooperations- und Lernprozesse optimal zu unterstützen? Hinsichtlich Fragestellung (1) untersucht diese Arbeit Argumentationsdiagramme und strukturierte Onlinediskussionen, zwei Schwerpunkte der Forschung zu Lernsystemen für Argumentation der vergangenen Jahre. Die Grundlage solcher Strukturierungsansätze bilden Theorien zum Lehren und Lernen mit Wissensrepräsentationen (theory of representational guidance) und Kooperationsskripten (script theory of guidance in computer-supported collaborative learning). Diese Arbeit führt beide Forschungsstränge in einer neuartigen Lernumgebung zusammen, die beide Ansätze vereint, um Lernende beim Diskutieren kontroverser Texte zu unterstützen. Eine empirische Untersuchung zeigt, dass sich dieser kombinierte Ansatz positiv auf die Diskussionsqualität auswirkt und bekräftigt damit die zu Grunde liegenden theoretischen Annahmen. Hinsichtlich Fragestellung (2) stellt diese Arbeit ein Software-Rahmensystem zur Bereitstellung adaptiver Unterstützungsmechanismen in Argumentationssystemen vor. Das Rahmensystem abstrahiert von domänen- und anwendungsspezifischen Besonderheiten und stellt damit einen generelleren Ansatz im Vergleich zu früheren Systemen dar. Der Ansatz umfasst ein umfangreiches Konfigurationssystem zur Definition intelligenter Softwareagenten, d. h. Softwarekomponenten, die eigeständig schlussfolgern und handeln, um Lernprozesse zu unterstützen. Um das Definieren und Administrieren von Softwareagenten über das bereitgestellte Rahmensystem hinaus zu vereinfachen, wurde ein grafisches Autorenwerkzeug konzipiert und entwickelt. Unter anderem erlaubt dieses erstmals, relevante Muster in Argumentationsdiagrammen ohne Programmierung mittels einer grafischen Sprache zu spezifizieren. Empirische Befunde zeigen neben dem hohen Potential des Ansatzes auch die Notwendigkeit weiterführender Forschung. Hinsichtlich Fragestellung (3) untersucht diese Arbeit zwei alternative Ansätze zur automatisierten Analyse von Lernaktivitäten im Bereich Argumentation: die wissensbasierte und die datenbasierte Analysemethodik. Der wissensbasierte Ansatz wurde mittels einer Softwarekomponente zur Mustersuche in Argumentationsdiagrammen umgesetzt, welche auf Grundlage deklarativer Musterbeschreibungen arbeitet. Die Möglichkeiten und Eignung des Ansatzes werden anhand von drei Beispielszenarien demonstriert, für die verschiedenartige, pädagogisch relevante Muster innerhalb der entwickelten Softwarekomponente definiert wurden. Der Ansatz erweist sich insbesondere als nützlich für Muster eingeschränkter Komplexität in Szenarien, für die Expertenwissen in ausreichendem Umfang verfügbar ist. Der datenbasierte Ansatz wurde mittels maschineller Lernverfahren umgesetzt. Mit deren Hilfe wurden Klassifikationsroutinen zur Analyse zentraler Aspekte von Onlinediskussionen, wie beispielsweise themenfremde Beiträge, begründete Aussagen und Frage-Antwort-Interaktionen, algorithmisch hergeleitet. Validierungsergebnisse zeigen, dass sich dieser Ansatz selbst für komplexe Klassifikationsprobleme eignet, welche die Berücksichtigung natürlicher Sprache erfordern. Dies ist die erste Arbeit zum Einsatz maschineller Lernverfahren zur Analyse von diagrammbasierten Lerndiskussionen. Die Arbeit schließt mit einer Diskussion des aktuellen Forschungsstands hinsichtlich der vier Fragestellungen im breiteren Kontext existierender Theorien und empirischer Befunde. Die Vor- und Nachteile verschiedener Optionen für die Gestaltung von Lernsystemen für Argumentation werden gegenübergestellt und zukünftige Forschungsfelder vorgeschlagen. Dieser letzte Teil der Arbeit bietet Forschern und Anwendern einen umfassenden Überblick des aktuellen Forschungsstands bezüglich des Designs computerbasierter Argumentationslernsysteme und den zugrunde liegenden lehr- und lerntheoretischen Erkenntnissen. Insbesondere wird auf Fragestellung (4) vertiefend eingegangen und bisherige Adaptionsansätze einschließlich entsprechender empirischer Befunde erörtert

Evaluating smart city learning

Measurement and analysis of individually interpreted learning experiences can build a knowledge picture of how learners perceive immersive technology-mediated learning in smart cities. Comparison of these learning experiences, with theoretical factors derived from relevant literature, may then shed light on the usefulness of theory in practical learning design and approaches to the evaluation of immersive learning environments analysed from a theoretical basis. In turn, this may contribute to current approaches of urban smart city environment planning for citizen engaged ‘human smart cities’ [14]. Mobile learning location-based prototypes will be developed with subject experts and implemented in open (urban) spaces located at Upper Barrakka Gardens, Valletta for history and Argotti Gardens, Floriana for botany. This paper discusses potential methodologies for designing a measurement of the effectiveness of these learning experiences and associated learning design for immersive urban learning environments mediated by mobile and networked technologies. Acknowledging the hybrid nature [9] of smart city learning, interactions between digital tools, content and community, measuring both intra- and inter-learner experiences is anticipated. Identifying and quantifying these dimensions of interactions will help us understand more about how urban smart learning activities create immersive experiences for each learner, engaging them in a variety of internal cognitive and social processes. To clarify mutual interaction between theoretical and empirical factors, a system of theoretical factors of significance is proposed to be developed, and then correlated, with learning experience analysis factors. A brief review of hybrid learning environment research, including ubiquitous learning [4] manifested in hybrid [9], mobile [8] and smart city [2] environments, provides context for how analytical methodology might be applied to an interactive learning system in smart cities. Phenomenographic techniques of variation and outcome space are investigated, together with the Dialogic Space concept [30] of conversation interaction for analysing dialogues.Funded by the Horizon 2020 Framework Programme of the European Union.peer-reviewe

Design and implementation of cooperative multi-player game to foster social interaction

Nowadays, a high percentage of the population owns a personal device to connect with anyone at any time. Yet, these smartphones affect the face-to-face interaction, prompting individuals' attention to their devices instead. Besides, games have also shifted from tools to communicate through the use of competition and/or collaboration to complex systems with global interconnection, complicated artificial intelligence agents and high definition graphics. Nonetheless, smartphones give the opportunity to play games at any time and location, being the capabilities of personal devices merely explored in situations where people are collocated. The main objective of this thesis is to create an application for smartphones to encourage communication and socialization. Imaginary has been developed as a playful experience where players must overcome the lack of shared information to achieve a better outcome than other players or groups. The game shows a picture to one player that is unknown by the rest. Players can compete against each other or collaborate as a team to reproduce the picture as similar as possible. Asymmetry and lack of awareness hinder the player's task, making communication an essential tool to success. A user study was conducted to evaluate the impact of the application in the communication and to detect possible usability problems. It consisted of 6 sessions with 4-5 participants from different nationalities and levels of familiarity with others. The results have defined Imaginary as a relaxing, engaging and playful game that facilitates interaction and communication. Participants described the game as a new experience that can be used for team up, learning purposes or just for leisure

Promoting Andean children's learning of science through cultural and digital tools

Conference Theme: To see the world and a grain of sand: Learning across levels of space, time, and scaleIn Peru, there is a large achievement gap in rural schools. In order to overcome this problem, the study aims to design environments that enhance science learning through the integration of ICT with cultural artifacts, respecting the Andean culture and empower rural children to pursue lifelong learning. This investigation employs the Cultural-Historical Activity Theory (CHAT) framework, and the Design-Based Research (DBR) methodology using an iterative process of design, implementation and evaluation of the innovative practice.published_or_final_versio

Arkose: A Prototype Mechanism and Tool for Collaborative Information Generation and Distillation.

The goals of this thesis have been to gain a better understanding of collaborative knowledge sharing and distilling and to build a prototype collaborative system that supports flexible knowledge generation and distillation. To reach these goals, I have conducted two user studies and built two systems. The first system, Arkose 1.0, is a prototype collaborative distillation system for a discussion space, which provides a set of augmentative tools to facilitate the filtering, structuring, and organizing of discussion information. Arkose 1.0 supports editors to distill a discussion space incrementally and collaboratively, and allows a gradual increase in the order and reusability of the information space. The study of an online question-answering community, Naver Knowledge-iN, investigates users’ knowledge sharing behaviors in a large online question-answering community. Through the analyses of a large quantity of question/answer pairs and 26 user interviews, the study analyzes the characteristics of knowledge generation and user participation behavior and gains insights into their motivations, roles, usage and expertise. It reveals that the limiting nature of the reply interfaces of Knowledge-iN leads to the accumulation of simple and easy questions and answers. This tendency is encouraged by the point system that rewards users who answer many questions quickly. Arkose2 is designed and implemented based on the lessons and insights gained in building Arkose 1.0 and examining Naver Knowledge-iN. Arkose2 provides a host of additional interaction mechanisms and supportive tools over Arkose 1.0 that assists users to flexibly generate knowledge and distill and organize it better. Finally, the evaluation of Arkose2 reveals a number of insights, issues, and lessons about users’ distillation activities of discussion spaces and features of Arkose2. These together provide valuable lessons and insights for the architecture and features of the next generation collective intelligent system.Ph.D.InformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/78880/1/ksnam_1.pd

A multi-fold assessment framework for virtualized collaborative and social learning scenarios

Proposem un procés de virtualització de sessions col·laboratives en directe a partir de fòrums de discussió i xats web amb l'objectiu de produir recursos d'aprenentatge en línia interactius per a ser utilitzats pels alumnes i generar un efecte positiu en la participació de l'alumne. Per tal de millorar encara més la implicació de l'aprenentatge, vam dotar al nostre procés de virtualització d'un marc d'avaluació múltiple que proporciona la consciència efectiva i la retroalimentació constructiva als alumnes de la col·laboració original amb interaccions entre els membres del grup. La investigació presentada es centra en l'avaluació electrònica d'aprenentatge col·laboratiu i social i s'estén amb analítiques d'aprenentatge i tècniques d'anàlisi de xarxa social que són capaces d'analitzar i representar les interaccions cognitives i socials amb sessions de col·laboració en viu subjacents.Proponemos un proceso de virtualización de sesiones colaborativas en directo a partir de foros de discusión y chats web con el objetivo de producir recursos de aprendizaje en línea interactivos para ser utilizados por los alumnos y generar un efecto positivo en la participación del alumno. Con el fin de mejorar aún más la implicación del aprendizaje, dotamos a nuestro proceso de virtualización de un marco de evaluación múltiple que proporciona la conciencia efectiva y la retroalimentación constructiva a los alumnos de la colaboración original con interacciones entre los miembros del grupo. La investigación presentada se centra en la evaluación electrónica de aprendizaje colaborativo y social y se extiende con analíticas de aprendizaje y técnicas de análisis de red social que son capaces de analizar y representar las interacciones cognitivas y sociales con sesiones de colaboración en vivo subyacentes.We propose a virtualization process of live collaborative sessions from Web discussion forums and chats with the aim to produce interactive and attractive online learning resources to be used by learners, thus having a positive effect in learner engagement. In order to enhance further learning engagement, we endow our virtualization process with a multifold assessment framework that provides effective awareness and constructive feedback to learners from the original collaborative interactions among group members. The research presented focuses on e-assessment of collaborative and social learning and extends it with Learning Analytics and Social Network Analysis techniques that are able to analyse and represent cognitive and social interactions underlying live collaborative sessions

Dialogue for Intercultural Understanding

This open access book is a result of an extensive, ambitious and wide-ranging pan-European project focusing on the development of children and young people’s cultural literacy and what it means to be European in the 21st century prioritising intercultural dialogue and mutual understanding. The Horizon 2020 funded, 3-year DIalogue and Argumentation for cultural Literacy Learning (DIALLS) project included ten partners from countries in and around Europe with the aim to centralise co-constructive dialogue as a main cultural literacy value and to promote tolerance, empathy and inclusion. This is achieved through teaching children in schools from a young age to engage together in discussions where they may have differing viewpoints or perspectives, to enable a growing awareness of their own cultural identities, and those of others. Central to the project is children’s engagement with wordless picture books and films, which are used as stimuli for discussions around core cultural themes such as social responsibility, living together and sustainable development. In order to enable intercultural dialogue in action, the project developed an online platform as a tool for engagement across classes, and which this book elaborates on. The book explores themes underpinning this unique interdisciplinary project, drawing together scholars from cultural studies, civics education and linguistics, psychologists, socio-cultural literacy researchers, teacher educators and digital learning experts. Each chapter of the book explores a theme that is common to the project, and celebrates its interdisciplinarity by exploring these themes through different lenses

MENON : automating a Socratic teaching model for mathematical proofs

This thesis presents an approach to adaptive pedagogical feedback for arbitrary domains as an alternative to resource-intensive pre-compiled feedback, which represents the state-of-the-art in intelligent tutoring systems today. A consequence of automatic adaptive feedback is that the number of tasks with pedagogical feedback that can be offered to the student increases, and with it the opportunity for practice. We focus on automating different aspects of teaching that together are primarily responsible for learning and can be integrated in a unified natural-language output. The automatic production and natural-language generation of feedback enables its personalisation both at the pedagogical and the natural-language dialogue level. We propose a method for automating the production of domain-independent adaptive feedback. The proof- of-concept implementation of the tutorial manager Menon is carried out for the domain of set-theory proofs. More specifically, we define a pedagogical model that abides by schema and cognitive load theory, and by the synergistic approach to learning. We implement this model in a Socratic teaching strategy whose basic units of feedback are dialogue moves. We use empirical data from two domains to derive a taxonomy of tutorial-dialogue moves, and define the most central and sophisticated move hint. The formalisation of the cognitive content of hints is inspired by schema theory and is facilitated by a domain ontology.Die vorliegende Arbeit präsentiert eine Annäherung an adaptives pädagogisches Feedback für beliebige Domäne. Diese Herangehensweise bietet eine Alternative zu ressource-intensivem, vorübersetztem Feedback, dass das heutige "state-of-the-art'; in intelligenten tutoriellen Systemen ist. Als Folge können zahlreiche Aufgaben mit pädagogischem Feedback für die Praxis angeboten werden. Der Schwerpunkt der Arbeit liegt auf der Automatisierung verschiedener Aspekte des Lehrprozesses, die in ihrer Gesamtheit wesentlich den Lernprozess beeinflussen, und in einer einheitlichen Systemausgabe Natürlicher Sprache integriert werden können. Die automatische Produktion und die Systemgenerierung von Feedback in Natürlicher Sprache ermöglichen eine Individualisierung des Feedback auf zwei Ebenen: einer pädagogischen und einer dialogischen Ebene. Dazu schlagen wir eine Methode vor, durch die adaptives Feedback automatisiert werden kann, und implementieren den tutoriellen Manager Menon als "proof-of-concept'; beispielhaft für die Domäne von Beweisen in der Mengentheorie. Konkret definieren wir ein pädagogisches Modell, das sich auf Schema- und Kognitionstheorie sowie auf die synergetische Herangehensweise an Lernen stützt. Dieses Modell wird in einer Sokratischen Lehrmethode implementiert, deren basale Feedback-Elemente aus Dialogakten bestehen. Zur Bestimmung einer Taxonomie Tutorielle-Dialogakte sowie des zentralen und komplexen Dialogakts hint (Hinweis) wenden wir empirische Daten aus zwei Domänen an. Die Formalisierung des kognitiven Inhaltes von Hinweisen folgt der Schematheorie und basiert auf einer Domänenontologie