Challenges of programming apprentice

The present article describes the challenges programming apprentices face and identifies the elements and processes that set them apart from experienced programmers. And also explains why a conventional programming languages teaching approach fails to map the programming mental model. The purpose of this discussion is to benefit from ideas and cognitive philosophies to be embedded in programming learning tools. Cognitive components are modeled as elements to be handled by the apprentices in tutoring systems while performing a programming task. In this process a mental level solution (the mental model of the program) and an implementation level solution (the program) are created. The mapping between these representations is a path followed by the student explicitly in this approach. © 2011 IEEE.

Practising Arithmetic Using Educational Video Games with an Interpersonal Computer

Studies show the positive effects that video games can have on student performance and attitude towards learning. In the past few years, strategies have been generated to optimize the use of technological resources with the aim of facilitating widespread adoption of technology in the classroom. Given its low acquisition and maintenance costs, the interpersonal computer allows individual interaction and simultaneous learning with large groups of students. The purpose of this work was to compare arithmetical knowledge acquired by third-grade students through the use of game-based activities and non-game-based activities using an interpersonal computer, with knowledge acquired through the use of traditional paper-and-pencil activities, and to analyze their impact in various socio-cultural contexts. To do this, a quasi-experimental study was conducted with 271 students in three different countries (Brazil, Chile, and Costa Rica), in both rural and urban schools. A set of educational games for practising arithmetic was developed and tested in six schools within these three countries. Results show that there were no significant differences (ANCOVA) in the learning acquired from game-based vs. non-game-based activities. However, both showed a significant difference when compared with the traditional method. Additionally, both groups using the interpersonal computer showed higher levels of student interest than the traditional method group, and these technological methods were seen to be especially effective in increasing learning among weaker students.

Adaptive Rückmeldungen im intelligenten Tutorensystem LARGO

Das intelligente Tutorensystem LARGO für die Rechtswissenschaften soll Jurastudenten helfen, Argumentationsstrategien zu lernen. Im verwendeten Ansatz werden Gerichtsprotokolle als Lernmaterialien verwendet: Studenten annotieren diese und erstellen graphische Repräsentationen des Argumentationsverlaufs. Das System kann dabei zur Reflexion über die von Anwälten vorgebrachten Argumente anregen und Lernende auf mögliche Schwächen in ihrer Analyse des Disputs hinweisen. Zur Erkennung von Schwächen verwendet das System Graphgrammatiken und kollaborative Filtermechanismen. Dieser Artikel stellt dar, wie in LARGO auf Basis der Bestimmung eines „Benutzungskontextes“ die Rückmeldungen im System benutzungsadaptiv gestaltet werden. Weiterhin diskutieren wir auf Basis der Ergebnisse einer kontrollierten Studie mit dem System, welche mit Jurastudierenden an der University of Pittsburgh stattfand, in wie weit der automatisch bestimmte Benutzungskontext zur Vorhersage von Lernerfolgen bei Studenten verwendbar ist.

(Lifelong) learning in your pocket?

Der Beitrag fokussiert die Entwicklung, den Einsatz und die Nutzung von innovativen Technologien zur Unterstützung von Bildungsszenarien in Schule, Hochschule und Weiterbildung. Ausgehend von den verschiedenen Phasen des Corporate Learning, Social Learning, Mobile Learning und Intelligent Learning wird in einem ersten Abschnitt das Nutzungsverhalten von Technologien durch Kinder, Jugendliche und (junge) Erwachsene in Schule, Studium und Lehre betrachtet. Es folgt die Darstellung technologischer Entwicklungen auf Basis des Technology Life Cycle und die Konsequenzen von unterschiedlichen Entwicklungszuständen und Reifegraden von Technologien wie Content Learning Management, sozialen Netzwerken, mobilen Endgeräten, multidimensionalen und -modalen Räumen bis hin zu Anwendungen augmentierter Realität und des Internets der Dinge, Dienste und Daten für den Einsatz und die Nutzung in Bildungsszenarien. Nach der Darstellung von Anforderungen an digitale Technologien hinsichtlich Inhalte, Didaktik und Methodik wie etwa hinsichtlich der Erstellung von Inhalten, deren Wiederverwendung, Digitalisierung und Auffindbarkeit sowie Standards werden methodische Hinweise zur Nutzung digitaler Technologien zur Interaktion von Lernenden, von Lehrenden, sozialer Interaktion, kollaborativem Autorieren, Kommentierung, Evaluation und Begutachtung gegeben. Abschließend werden - differenziert für Schule und Hochschule - Erkenntnisse zu Rahmenbedingungen, Einflussgrößen, hemmenden und fördernden Faktoren sowie Herausförderungen bei der Einführung und nachhaltigen Implementation digitaler Technologien im schulischen Unterricht, in Lehre, Studium und Weiterbildung im Überblick zusammengefasst.

Una propuesta de modelado del estudiante basada en ontologías y diagnóstico pedagógico-cognitivo no monótono

Los recientes avances tecnológicos han encontrado un potencial campo de explotación en la educación asistida por computador. A finales de los años 90 surgió un nuevo campo de investigación denominado Entornos Virtuales Inteligentes para el Entrenamiento y/o Enseñanza (EVIEs), que combinan dos áreas de gran complejidad: Los Entornos Virtuales (EVs) y los Sistemas de Tutoría Inteligente (STIs). De este modo, los beneficios de los entornos 3D (simulación de entornos de alto riesgo o entornos de difícil uso, etc.) pueden combinarse con aquéllos de un STIs (personalización de materias y presentaciones, adaptación de la estrategia de tutoría a las necesidades del estudiante, etc.) para proporcionar soluciones educativas/de entrenamiento con valores añadidos. El Modelo del Estudiante, núcleo de un SIT, representa el conocimiento y características del estudiante, y refleja el proceso de razonamiento del estudiante. Su complejidad es incluso superior cuando los STIs se aplican a EVs porque las nuevas posibilidades de interacción proporcionadas por estos entornos deben considerarse como nuevos elementos de información clave para el modelado del estudiante, incidiendo en todo el proceso educativo: el camino seguido por el estudiante durante su navegación a través de escenarios 3D; el comportamiento no verbal tal como la dirección de la mirada; nuevos tipos de pistas e instrucciones que el módulo de tutoría puede proporcionar al estudiante; nuevos tipos de preguntas que el estudiante puede formular, etc. Por consiguiente, es necesario que la estructura de los STIs, embebida en el EVIE, se enriquezca con estos aspectos, mientras mantiene una estructura clara, estructurada, y bien definida. La mayoría de las aproximaciones al Modelo del Estudiante en STIs y en IVETs no consideran una taxonomía de posibles conocimientos acerca del estudiante suficientemente completa. Además, la mayoría de ellas sólo tienen validez en ciertos dominios o es difícil su adaptación a diferentes STIs. Para vencer estas limitaciones, hemos propuesto, en el marco de esta tesis doctoral, un nuevo mecanismo de Modelado del Estudiante basado en la Ingeniería Ontológica e inspirado en principios pedagógicos, con un modelo de datos sobre el estudiante amplio y flexible que facilita su adaptación y extensión para diferentes STIs y aplicaciones de aprendizaje, además de un método de diagnóstico con capacidades de razonamiento no monótono. El método de diagnóstico es capaz de inferir el estado de los objetivos de aprendizaje contenidos en el SIT y, a partir de él, el estado de los conocimientos del estudiante durante su proceso de aprendizaje. La aproximación almodelado del estudiante propuesta ha sido implementada e integrada en un agente software (el agente de modelado del estudiante) dentro de una plataforma software existente para el desarrollo de EVIEs denominadaMAEVIF. Esta plataforma ha sido diseñada para ser fácilmente configurable para diferentes aplicaciones de aprendizaje. El modelado del estudiante presentado ha sido implementado e instanciado para dos tipos de entornos de aprendizaje: uno para aprendizaje del uso de interfaces gráficas de usuario en una aplicación software y para un Entorno Virtual para entrenamiento procedimental. Además, se ha desarrollado una metodología para guiar en la aplicación del esta aproximación de modelado del estudiante a cada sistema concreto.---ABSTRACT---Recent technological advances have found a potential field of exploitation in computeraided education. At the end of the 90’s a new research field emerged, the so-called Intelligent Virtual Environments for Training and/or Education (IVETs), which combines two areas of great complexity: Virtual Environments (VE) and Intelligent Tutoring Systems (ITS). In this way, the benefits of 3D environments (simulation of high risk or difficult-to-use environments, etc.) may be combined with those of an ITS (content and presentation customization, adaptation of the tutoring strategy to the student requirements, etc.) in order to provide added value educational/training solutions. The StudentModel, core of an ITS, represents the student’s knowledge and characteristics, and reflects the student’s reasoning process. Its complexity is even higher when the ITSs are applied on VEs because the new interaction possibilities offered by these environments must be considered as new key information pieces for student modelling, impacting all the educational process: the path followed by the student during their navigation through 3D scenarios; non-verbal behavior such as gaze direction; new types of hints or instructions that the tutoring module can provide to the student; new question types that the student can ask, etc. Thus, it is necessary for the ITS structure, which is embedded in the IVET, to be enriched by these aspects, while keeping a clear, structured and well defined architecture. Most approaches to SM on ITSs and IVETs don’t consider a complete enough taxonomy of possible knowledge about the student. In addition, most of them have validity only in certain domains or they are hard to be adapted for different ITSs. In order to overcome these limitations, we have proposed, in the framework of this doctoral research project, a newStudentModeling mechanism that is based onOntological Engineering and inspired on pedagogical principles, with a wide and flexible data model about the student that facilitates its adaptation and extension to different ITSs and learning applications, as well as a rich diagnosis method with non-monotonic reasoning capacities. The diagnosis method is able to infer the state of the learning objectives encompassed by the ITS and, fromit, the student’s knowledge state during the student’s process of learning. The proposed student modelling approach has been implemented and integrated in a software agent (the student modeling agent) within an existing software platform for the development of IVETs called MAEVIF. This platform was designed to be easily configurable for different learning applications. The proposed student modeling has been implemented and it has been instantiated for two types of learning environments: one for learning to use the graphical user interface of a software application and a Virtual Environment for procedural training. In addition, a methodology to guide on the application of this student modeling approach to each specific system has been developed.

Especificación del comportamiento de un avatar en un mundo virtual mediante una ontología

El presente trabajo describe la construcción de una aplicación que controla a un Non Player Character (NPC), en un mundo virtual. La aplicación desarrollada, que tiene como nombre BotManager, realiza dos tareas fundamentales: 1) conectarse al repositorio de conocimiento, que en esta implementación es una ontología expresada en OWL, para obtener las acciones que debe realizar el NPC dentro del mundo virtual; y 2) ordenar al NPC que realice estas acciones en un mundo virtual creado con la plataforma OpenSimulator. BotManager puede tener variadas aplicaciones, por lo tanto puede ser usada como complemento en mundos virtuales aplicados a la educación, simulación, ocio, etc. Ahora bien, la principal razón que motivó el desarrollo del BotManager fue la de crear un sistema de demostración automática de tareas en un mundo virtual destinado a la educación/ entrenamiento. De esta forma, un Sistema Inteligente de Tutoría integrado con un mundo virtual podría demostrar paso a paso a un estudiante cómo realizar una tarea en el mundo virtual. La ontología que lee el BotManager extiende la ontología propuesta en la tesis “Una propuesta de modelado del estudiante basada en ontologías y diagnóstico pedagógico-cognitivo no monótono” de Julia Parraga en el 2011 (Ontología de Julia). La construcción y las pruebas del BotManager se llevaron a cabo en tres etapas: 1) creación de la Ontología de Acciones del NPC que extiende la Ontología de Julia; 2) diseño e implementación de la aplicación en C# que lee la ontología que contiene el plan de acción del NPC, y ordena al NPC realizar las acciones en el mundo virtual; y 3) pruebas de la aplicación con la práctica “preparación de una taza de cafe”, que es parte de un Laboratorio Virtual de Biotecnología. El BotManager se ha diseñado como una aplicación cliente que se conecta a un servidor de Open- Simulator. Por lo tanto, puede ejecutarse en una máquina distinta a la del servidor. Asimismo, en la implementación del BotManager se ha utilizado una librería gratuita denominada LibOpenMetaverse que permite controlar un NPC de forma remota.---ABSTRACT---This paper describes the construction of an application that controls a Non Player Character (NPC), in a virtual world. The application developed, called BotManager, performs two main tasks: 1) the connection to the repository of knowledge, which in this implementation is an ontology expressed in OWL, and retrieving the actions to be performed by the NPC within the virtual world; and 2) commanding the NPC to perform these actions in a virtual world created with the OpenSimulator platform. BotManager can have diverse applications, therefore it can be used as a complement in virtual worlds applied to education, simulation, entertainment, etc. However, the main reason behind the development of BotManager was to create an automatic demonstration of tasks in a virtual world for education / training. Thus, a virtual world integrated with an Intelligent Tutoring Systems could demonstrate step by step to a student how to perform a task in the virtual world. The ontology used by the BotManager extends ontology proposed in the thesis “A proposal for modeling ontologies based student and not monotonous teaching-cognitive diagnosis” by Julia Parraga in 2011 (Julia’s Ontology). Construction and testing of BotManager were conducted in three stages: 1) creation of the NPC Actions Ontology by extending the Julia’s Ontology; 2) design and implementation of the application in C# that reads the ontology containing the plan of action of the NPC, and commands the NPC to perform the read plan in the virtual world; and 3) testing of the application with the practice “preparing a cup of coffee”, which is part of a Virtual Laboratory of Biotechnology. The BotManager has been designed as a client application that connects to an OpenSimulator server. Therefore, it can run on a different machine to the server. To implement the BotManager we have used a free library called libopenmetaverse that allows us to control a NPC remotely.

A conceptual model of personalized virtual learning environments

The Virtual Learning Environment (VLE) is one of the fastest growing areas in educational technology research and development. In order to achieve learning effectiveness, ideal VLEs should be able to identify learning needs and customize solutions, with or without an instructor to supplement instruction. They are called Personalized VLEs (PVLEs). In order to achieve PVLEs success, comprehensive conceptual models corresponding to PVLEs are essential. Such conceptual modeling development is important because it facilitates early detection and correction of system development errors. Therefore, in order to capture the PVLEs knowledge explicitly, this paper focuses on the development of conceptual models for PVLEs, including models of knowledge primitives in terms of learner, curriculum, and situational models, models of VLEs in general pedagogical bases, and particularly, the definition of the ontology of PVLEs on the constructivist pedagogical principle. Based on those comprehensive conceptual models, a prototyped multiagent-based PVLE has been implemented. A field experiment was conducted to investigate the learning achievements by comparing personalized and non-personalized systems. The result indicates that the PVLE we developed under our comprehensive ontology successfully provides significant learning achievements. These comprehensive models also provide a solid knowledge representation framework for PVLEs development practice, guiding the analysis, design, and development of PVLEs. (c) 2005 Elsevier Ltd. All rights reserved.

Intelligent agent supported personalization for virtual learning environments

Virtual learning environments (VLEs) are computer-based online learning environments, which provide opportunities for online learners to learn at the time and location of their choosing, whilst allowing interactions and encounters with other online learners, as well as affording access to a wide range of resources. They have the capability of reaching learners in remote areas around the country or across country boundaries at very low cost. Personalized VLEs are those VLEs that provide a set of personalization functionalities, such as personalizing learning plans, learning materials, tests, and are capable of initializing the interaction with learners by providing advice, necessary instant messages, etc., to online learners. One of the major challenges involved in developing personalized VLEs is to achieve effective personalization functionalities, such as personalized content management, learner model, learner plan and adaptive instant interaction. Autonomous intelligent agents provide an important technology for accomplishing personalization in VLEs. A number of agents work collaboratively to enable personalization by recognizing an individual's eLeaming pace and reacting correspondingly. In this research, a personalization model has been developed that demonstrates dynamic eLearning processes; secondly, this study proposes an architecture for PVLE by using intelligent decision-making agents' autonomous, pre-active and proactive behaviors. A prototype system has been developed to demonstrate the implementation of this architecture. Furthemore, a field experiment has been conducted to investigate the performance of the prototype by comparing PVLE eLearning effectiveness with a non-personalized VLE. Data regarding participants' final exam scores were collected and analyzed. The results indicate that intelligent agent technology can be employed to achieve personalization in VLEs, and as a consequence to improve eLeaming effectiveness dramatically.

Computational approaches to emotional decision making

Findings on the role that emotion plays in human behavior have transformed Artificial Intelligence computations. Modern research explores how to simulate more intelligent and flexible systems. Several studies focus on the role that emotion has in order to establish values for alternative decision and decision outcomes. For instance, Busemeyer et al. (2007) argued that emotional state affects the subjectivity value of alternative choice. However, emotional concepts in these theories are generally not defined formally and it is difficult to describe in systematic detail how processes work. In this sense, structures and processes cannot be explicitly implemented. Some attempts have been incorporated into larger computational systems that try to model how emotion affects human mental processes and behavior (Becker-Asano & Wachsmuth, 2008; Marinier, Laird & Lewis, 2009; Marsella & Gratch, 2009; Parkinson, 2009; Sander, Grandjean & Scherer, 2005). As we will see, some tutoring systems have explored this potential to inform user models. Likewise, dialogue systems, mixed-initiative planning systems, or systems that learn from observation could also benefit from such an approach (Dickinson, Brew & Meurers, 2013; Jurafsky & Martin, 2009). That is, considering emotion as interaction can be relevant in order to explain the dynamic role it plays in action and cognition (see Boehner et al., 2007).

Intelligent tutoring system for distance education

This study aims to develop and implement a tool called intelligent tutoring system in an online course to help a formative evaluation in order to improve student learning. According to Bloom et al. (1971,117) formative evaluation is a systematic evaluation to improve the process of teaching and learning. The intelligent tutoring system may provide a timely and high quality feedback that not only informs the correctness of the solution to the problem, but also informs students about the accuracy of the response relative to their current knowledge about the solution. Constructive and supportive feedback should be given to students to reveal the right and wrong answers immediately after taking the test. Feedback about the right answers is a form to reinforce positive behaviors. Identifying possible errors and relating them to the instructional material may help student to strengthen the content under consideration. The remedial suggestion should be given in each answer with detaileddescription with regards the materials and instructional procedures before taking next step. The main idea is to inform students about what they have learned and what they still have to learn. The open-source LMS called Moodle was extended to accomplish the formative evaluation, high-quality feedback, and the communal knowledge presented here with a short online financial math course that is being offered at a large University in Brazil. The preliminary results shows that the intelligent tutoring system using high quality feedback helped students to improve their knowledge about the solution to the problems based on the errors of their past cohorts. The results and suggestion for future work are presented and discussed.

A Microleakage Study Of Gutta-percha/ah Plus And Resilon/real Self-etch Systems After Different Irrigation Protocols.

The development and maintenance of the sealing of the root canal system is the key to the success of root canal treatment. The resin-based adhesive material has the potential to reduce the microleakage of the root canal because of its adhesive properties and penetration into dentinal walls. Moreover, the irrigation protocols may have an influence on the adhesiveness of resin-based sealers to root dentin. The objective of the present study was to evaluate the effect of different irrigant protocols on coronal bacterial microleakage of gutta-percha/AH Plus and Resilon/Real Seal Self-etch systems. One hundred ninety pre-molars were used. The teeth were divided into 18 experimental groups according to the irrigation protocols and filling materials used. The protocols used were: distilled water; sodium hypochlorite (NaOCl)+eDTA; NaOCl+H3PO4; NaOCl+eDTA+chlorhexidine (CHX); NaOCl+H3PO4+CHX; CHX+eDTA; CHX+ H3PO4; CHX+eDTA+CHX and CHX+H3PO4+CHX. Gutta-percha/AH Plus or Resilon/Real Seal Se were used as root-filling materials. The coronal microleakage was evaluated for 90 days against Enterococcus faecalis. Data were statistically analyzed using Kaplan-Meier survival test, Kruskal-Wallis and Mann-Whitney tests. No significant difference was verified in the groups using chlorhexidine or sodium hypochlorite during the chemo-mechanical preparation followed by eDTA or phosphoric acid for smear layer removal. The same results were found for filling materials. However, the statistical analyses revealed that a final flush with 2% chlorhexidine reduced significantly the coronal microleakage. A final flush with 2% chlorhexidine after smear layer removal reduces coronal microleakage of teeth filled with gutta-percha/AH Plus or Resilon/Real Seal SE.

Does The Reciproc File Remove Root Canal Bacteria And Endotoxins As Effectively As Multifile Rotary Systems?

To evaluate the effectiveness of Reciproc for the removal of cultivable bacteria and endotoxins from root canals in comparison with multifile rotary systems. The root canals of forty human single-rooted mandibular pre-molars were contaminated with an Escherichia coli suspension for 21 days and randomly assigned to four groups according to the instrumentation system: GI - Reciproc (VDW); GII - Mtwo (VDW); GIII - ProTaper Universal (Dentsply Maillefer); and GIV -FKG Race(™) (FKG Dentaire) (n = 10 per group). Bacterial and endotoxin samples were taken with a sterile/apyrogenic paper point before (s1) and after instrumentation (s2). Culture techniques determined the colony-forming units (CFU) and the Limulus Amebocyte Lysate assay was used for endotoxin quantification. Results were submitted to paired t-test and anova. At s1, bacteria and endotoxins were recovered in 100% of the root canals investigated (40/40). After instrumentation, all systems were associated with a highly significant reduction of the bacterial load and endotoxin levels, respectively: GI - Reciproc (99.34% and 91.69%); GII - Mtwo (99.86% and 83.11%); GIII - ProTaper (99.93% and 78.56%) and GIV - FKG Race(™) (99.99% and 82.52%) (P < 0.001). No statistical difference were found amongst the instrumentation systems regarding bacteria and endotoxin removal (P > 0.01). The reciprocating single file, Reciproc, was as effective as the multifile rotary systems for the removal of bacteria and endotoxins from root canals.

Photoelastic Analysis Of Fixed Partial Prosthesis Crown Height And Implant Length On Distribution Of Stress In Two Dental Implant Systems.

The aim of this study was to evaluate by photoelastic analysis stress distribution on short and long implants of two dental implant systems with 2-unit implant-supported fixed partial prostheses of 8 mm and 13 mm heights. Sixteen photoelastic models were divided into 4 groups: I: long implant (5 × 11 mm) (Neodent), II: long implant (5 × 11 mm) (Bicon), III: short implant (5 × 6 mm) (Neodent), and IV: short implants (5 × 6 mm) (Bicon). The models were positioned in a circular polariscope associated with a cell load and static axial (0.5 Kgf) and nonaxial load (15°, 0.5 Kgf) were applied to each group for both prosthetic crown heights. Three-way ANOVA was used to compare the factors implant length, crown height, and implant system (α = 0.05). The results showed that implant length was a statistically significant factor for both axial and nonaxial loading. The 13 mm prosthetic crown did not result in statistically significant differences in stress distribution between the implant systems and implant lengths studied, regardless of load type (P > 0.05). It can be concluded that short implants showed higher stress levels than long implants. Implant system and length was not relevant factors when prosthetic crown height were increased.

Dentine Bond Strength And Antimicrobial Activity Evaluation Of Adhesive Systems.

This study evaluated the dentine bond strength (BS) and the antibacterial activity (AA) of six adhesives against strict anaerobic and facultative bacteria. Three adhesives containing antibacterial components (Gluma 2Bond (glutaraldehyde)/G2B, Clearfil SE Protect (MDPB)/CSP and Peak Universal Bond (PUB)/chlorhexidine) and the same adhesive versions without antibacterial agents (Gluma Comfort Bond/GCB, Clearfil SE Bond/CSB and Peak LC Bond/PLB) were tested. The AA of adhesives and control groups was evaluated by direct contact method against four strict anaerobic and four facultative bacteria. After incubation, according to the appropriate periods of time for each microorganism, the time to kill microorganisms was measured. For BS, the adhesives were applied according to manufacturers' recommendations and teeth restored with composite. Teeth (n=10) were sectioned to obtain bonded beams specimens, which were tested after artificial saliva storage for one week and one year. BS data were analyzed using two-way ANOVA and Tukey test. Saliva storage for one year reduces the BS only for GCB. In general G2B and GCB required at least 24h for killing microorganisms. PUB and PLB killed only strict anaerobic microorganisms after 24h. For CSP the average time to eliminate the Streptococcus mutans and strict anaerobic oral pathogens was 30min. CSB showed no AA against facultative bacteria, but had AA against some strict anaerobic microorganisms. Storage time had no effect on the BS for most of the adhesives. The time required to kill bacteria depended on the type of adhesive and never was less than 10min. Most of the adhesives showed stable bond strength after one year and the Clearfil SE Protect may be a good alternative in restorative procedures performed on dentine, considering its adequate bond strength and better antibacterial activity.