Abstract
The Inven!RA architecture is an approach for online tracking of progression towards learning objectives, from analytics of distributed learning activities, provided by multiple third parties. However, there are few examples on how to implement such third-party learning activities, known as Activity Provider modules. We followed the Inven!RA architecture interfacing specification to create and implement two sample learning activities: a technical documentation analysis activity and an Arduino microelectronics programming activity. Integration tests with an Inven!RA architecture prototype confirmed the adequacy of this implementation. Thus, these samples provide clarification on how to design and develop Inven!RA Activity Provider modules.;A arquitetura Inven!RA é uma abordagem para o acompanhamento online da evolução face a objetivos de aprendizagem, através de dados analíticos de atividades de aprendizagem distribuídas, proporcionadas por um leque variado de entidades externas. Como são escassos os exemplos de implementação destas atividades de aprendizagem externas, designadas por módulos de Prestadores de Atividades,seguimos a especificação de interfaces da arquitetura para criar e implementar dois exemplos de atividades de aprendizagem: uma atividade de análise de documentação técnica e uma de programação de microeletrónica com Arduino. Testes de integração com um protótipo da Inven!RA confirmaram a adequação destas implementações. Consequentemente, proporcionam clarificação quanto à forma de conceber e desenvolver módulos de Prestadores de Atividades para a arquitetura Inven!RA.

Abstract
Chairing online Master Programmes requires constant monitoring and decision-making, amidst diversified data and ongoing processes. If misunderstood or misinterpreted, poor decisions may result, as well as lost opportunities to support enrolled students. Decision-making can be supported by dashboards, but there are few prototypes which underwent limited evaluation. We focus on identifying and prototyping efficient visualisation and interaction methods for such a dashboard, to offer online Master Program chairs opportunities for better analysis and decision-making. Design science research was conducted: evaluate and revise an existing prototype; evaluate the revised prototype with master program chairs; design, implementation, and evaluation of a final prototype, again involving master program chairs. The final prototype dashboard provides a way for Master Program chairs to visualize and interact with Master Program data, to support improved analysis of information and quick identification of problems, towards better decision-making.;A coordenação de cursos de mestrado online requer constante acompanhamento e tomada de decisões, com dados diversificados e processos em curso. Se mal interpretados, podem advir decisões inadequadas ou perderem-se oportunidades de apoiar os alunos do curso. Existem painéis de instrumentos de apoio, mas poucos protótipos, carentes de avaliação aprofundada. Focámo-nos na identificação e prototipagem de métodos de visualização e interação para um destes painéis, visando proporcionar aos coordenadores de cursos de mestrado online oportunidades para melhor tomada de decisão. Conduzimos iterações de investigação por ciência da conceção: avaliação e reformulação de protótipo existente; avaliação do protótipo revisto por coordenadores de cursos de mestrado; conceção, implementação e avaliação de protótipo final, novamente envolvendo coordenadores de cursos. O protótipo final constitui uma forma de coordenadores de curso visualizarem e interagirem com os dados do curso, apoiando melhor análise e rápida identificação de problemas, visando melhor tomada de decisões.

Abstract
Assessment and tracking of activities in non-traditional contexts, such as immersive environments, is a complex and timeconsuming process for instructors. This limits the widespread adoption of immersive environments, since the consequences of those constraints are lack of awareness for orchestration of learning, and lack of elements for assessment. The Inven!RA architecture proposes tackling this problem by collecting status and outcome analytics from multiple immersive activities into a single learning plan, where they are mapped to learning objectives. This enables the creation of learning dashboards for instructors and students, to support their awareness and assessment, enabling learning orchestration and self-regulation of learning. We present an implementation of the Inven!RA architecture in a platform linked to a remote computer networking laboratory, exemplifying how the architecture can achieve its purported goals.

Abstract
The Open Laboratory of Interdisciplinary Experimentation (LAEI) had its 1st edition as UC "lnovPed" in the academic year 2018/2019, resulting from a proposal presented by professors from the Faculty of Arts, Faculty of Engineering and collaborators of the U. Porto. Imp1ementing the U.OpenLah concept and involving students from different degrees and scientific areas, LAEI has sought to develop basic skills and added value in creating digital experiences. Through theoretical exposition and an experimentation exercise in the field of digital content production or technologies for innovative digital content, creativity and project management, students share and implement the concepts and competences learned, including those of the scientific area of origin.

Abstract
Natural user interfaces are becoming widespread as a focus of research in human-computer interaction. Gestural interaction is an important part of this field, but generally done by mimicry. This raises concerns such as the necessity of creating abstractions for non-imitable commands and the difficulty of finding gestures that are meaningful for a worldwide audience. Cultural backgrounds impart different meanings to gestures. In this research , we explore the concept of allowing individuals to interact with computer systems using gesture from the individual’s own culture, focusing on a software engineering approach to support this idea. The aim is to leverage the rich semantics of non-mimicry cultural gestures to expand gestural interaction to support abstract commands for instructions that do not have a matching gestural imitation. This approach also holds the potential to support the learning of gestural commands, by linking them to the cultural background of each user. The proposed software engineering approach demonstrates the feasibility of planning applications with commands in mind, not specific gestures, separating concerns between gestural identification (which can include cultural background elements) and actual commands.

Abstract
A Shamanic Interface is a recent concept that posits that the acknowledgment of culture in gestural commands may contribute to richer and more powerful user interaction with abstract concepts and complexity, but has a lack of empirical validation. Hence, this paper presents a game developed as an empirical research tool for data collection and testing on shamanic interfaces. The game is a small maze where users use gestures to control a character to reach the end of each level. The control gestures performed by each user are captured with a Leap Motion controller and recognized through Hidden Markov Models. Three command sets were implemented: Portuguese cultural gestures, Dutch cultural gestures, and a generic set. This paper evaluates the game with different users to check its playability. We conclude that the game can be used as a research data-collection tool as is, but also acknowledge several playability-related improvement recommendations.