Computing has evolved from isolated machines, providing calculative support of applications, toward communication networks that provide functional support to groups of people and embedded systems. Perhaps, one of the most compelling feature and benefit of computers is their overwhelming computing efficiency. Today, we conceive distributed computational systems of an ever-increasing sophistication, which we then apply in various settings – critical support functions of our society just to name one important application area. The spread and impact of computing, in terms of so-called information society technologies, has obviously gained a very high momentum over the years and today it delivers a technology that our societies have come to depend on. To this end, concerns related to our acceptance of qualities of computing, e.g., dependability, are increasingly emphasized by users as well as vendors. An indication of this increased focus on dependability is found in contemporary efforts of mitigating the effects from systemic failures in critical infrastructures, e.g., energy distribution, resource logistics, and financial transactions. As such, the dependable function of these infrastructures is governed by means of more or less autonomic computing systems that interact with cognitive human agents. However, due to intricate system dependencies as well as being situated in our physical environment, even the slightest – unanticipated – perturbation in one of these embedded systems can result in degradations or catastrophic failures of our society. We argue that this contemporary problem of computing mainly is due to our own difficulties in modeling and engineering the involved system complexities in an understandable manner. Consequently, we have to provide support for dependable computing systems by means of new methodologies of systems engineering. From a historical perspective, computing has evolved, from being supportive of quite well defined and understood tasks of algorithmic computations, into a disruptive technology that enables and forces change upon organizations as well as our society at large. In effect, a major challenge of contemporary computing is to understand, predict, and harness the involved systems’ increasing complexity in terms of constituents, dependencies, and interactions – turning them into dependable systems. In this thesis, we therefore introduce a model of open computational systems, as the means to convey these systems’ factual behavior in realistic situations, but also in order to facilitate our own understanding of how to monitor and control their complex interdependencies. Moreover, since the critical variables that govern these complex systems’ qualitative behavior can be of a very elusive nature, we also introduce a method of online engineering, whereby cognitive agents – human and software – can instrument these open computational systems according to their own subjective and temporal understanding of some complex situation at hand.

The ubiquitous use of computers and greater accessibility of the Internet have triggered widespread use of educational innovations such as online discussion forums, Wikis, Open Educational Resources, MOOCs, to name a few. These advances have led to the creation of a wide range of instructional videos, written documents and discussion archives by engineering learners seeking to expand their learning and advance their knowledge beyond the engineering classroom. However, it remains a challenging task to assess the quality of knowledge advancement on these learning platforms particularly due to the informal nature of engagement as a whole and the massive amount of learner-generated data. This research addresses this broad challenge through a research approach based on the examination of the state of knowledge advancement, analysis of relationships between variables indicative of knowledge creation and participation in knowledge creation, and identification of groups of learners. The study site is an online engineering community, All About Circuits, that serves 31,219 electrical and electronics engineering learners who contributed 503,908 messages in 65,209 topics. The knowledge creation metaphor provides the guiding theoretical framework for this research. This metaphor is based on a set of related theories that conceptualizes learning as a collaborative process of developing shared knowledge artifacts for the collective benefit of a community of learners. In a knowledge-creating community, the quality of learning and participation can be evaluated by examining the degree of collaboration and the advancement of knowledge artifacts over an extended period of time. Software routines were written in Python programming language to collect and process more than half a million messages, and to extract user-produced data from 87,263 web pages to examine the use of engineering terms, social networks and engineering artifacts. Descriptive analysis found that state of knowledge advancement varies across discussion topics and the level of engagement in knowledge creating activities varies across individuals. Non-parametric correlation analysis uncovered strong associations between topic length and knowledge creating activities, and between the total interactions experienced by individuals and individual engagement in knowledge creating activities. On the other hand, the variable of individual total membership period has week associations with individual engagement in knowledge creating activities. K-means clustering analysis identified the presence of eight clusters of individuals with varying lengths of participation and membership, and Kruskal-Wallis tests confirmed that significant differences between the clusters. Based on a comparative analysis of Kruskal-Wallis Score Means and the examination of descriptive statistics for each cluster, three groups of learners were identified: Disengaged (88% of all individuals), Transient (10%) and Engaged (2%). A comparison of Spearman Correlations between pairs of variables suggests that variable of individual active membership period exhibits stronger association with knowledge creation activities for the group of Disengaged, whereas the variable of individual total interactions exhibits stronger association with knowledge creation activities for the group of Engaged. Limitations of the study are discussed and recommendations for future work are made. / Ph. D.

There is an emerging field in the design and development of complex systems, where systems are built upon components which in themselves are large scale systems – system of systems. Among other things, the system of systems viewpoint emphasises on open complex systems. In this thesis, the model of open computational systems is used to convey the constituents, dependencies, and interactions of such complex distributed systems. These open complex systems are exposed to critical events, occurring in the systems execution environment. Moreover, these events may have negative effects on the system at hand, resulting in system behaviour diverging from intended. Also, to take all possible affecting events in consideration when designing the system is impossible. By being able to instrument the system at hand in real time, i.e. online, one may be able to compensate the effects caused by critical events. However, to enable online instrumentation, one needs a supporting methodology which handles issues of an online nature and supporting technologies. In this thesis, this support is enabled by the methodology of online engineering and the technology of visualization. Furthermore, these instrumentations can be performed by cognitive agents – both human and software – which may explore and refine a specific system in conformance with their own, or cooperative, agendas and qualitative goals. To be able to perform the instrumentation, the cognitive agents need to be able to observe the phenomenon at hand to gain situation awareness, which in itself lies as a foundation for the decision process, carried out during the instrumentation phase. With this in mind, one quickly realizes the importance of enabling observation of open computational systems for both human and software cognitive agents. If human cognitive agents are involved in applying the methodology; the requirements on how the system is represented for the observing human agent – how the system is visualized – grows even more important. In this thesis, we emphasise visualization technology as a supporting technology for human cognitive agents in their observation process. By providing human cognitive agents with visualization technology, we may enhance the result of their observation process and thereby also increase the possibility to reach their qualitative goals. Hence, visualization of open computational systems affects a human cognitive agent’s situation awareness, which in itself lies as the foundation for the decision making process on instrumentation of the specific system at hand in conformance with the agent’s qualitative goals. This thesis will present an evaluation of a supporting tool for visualization of systemic qualities in open computational systems. Such tool must supply functions which convey the set of requirements put forward by the selected model, method, and technology. Moreover, the evaluation will be accompanied by appropriate recommendations for improvement of such a tool.

Student interactions in learning environments are vital for learning development. The growth of online learning in higher education has led stakeholders to question how to identify student interactions with course material and increase the quality and value of the learning experience. This research focused on leveraging existing learning analytics from the Canvas Learning Management System (LMS) to identify course interactions and make data-informed course design decisions. Learning analytics were collected from 113 students in three course sections of an online construction management course. Three surveys were also distributed to each course section to gather the students' perceptions of the learning methods and their interactions for assistance. An exploratory graphical analysis visually depicted student interactions in the online course through the students' hourly and weekly interaction levels, page visits, and discussion board activity. A paired t-test was used to statistically compare the survey responses on the students' perceptions of the learning methods. The learning analytics results showed the students' interaction levels peaked in the afternoon and evening hours, and their weekly interactions and page visits lessened after the midterm exam. Additionally, based on Pearson's correlation test, the discussion board interactions significantly correlated with student performance. Lastly, the surveys showed that students found watching the lecture videos and reading the lecture slides to be the most helpful methods when learning the course material. These results have important implications for online stakeholders as learning analytics and student perceptions can inform online course design to facilitate student, instructor, and content interactions. / Master of Science / In an online course, students click on lecture pages to watch lecture videos, they use discussion boards to post and reply to their peers, and they visit their courses at whatever time suits them. These interactions are difficult for an instructor to identify. Therefore, making it harder for them to engage with the students, determine which students are at-risk for failing, or develop their courses based on the students' interactions. This research study leverages learning analytics to identify student interactions in an online construction management course to improve academic decision-making and course design. Learning analytics are interaction data collected from a course that includes every student's interaction with the course material (e.g., page clicks, discussion posts and replies). Additionally, surveys were distributed to each of the three online construction management course sections used in this study to gather the students' thoughts about the available learning methods (e.g., video lectures, lecture slides). The learning analytics results showed that student interaction fluctuates by the hour and lessens after the midterm exam. The survey results found watching the lecture videos and reading the lecture slides were the most helpful learning methods. The capabilities of learning analytics must be addressed by online stakeholders when developing future online courses. The growth of online learning is inevitable, and the results of this paper suggest that learning analytics can identify unnoticed student interaction patterns and influence future online course design.

The main objective of this thesis is to propose the control of 2D object in a remote scene, using a contextualized, collaborative and interactive multimedia. The 2D objects are mainly electronic devices. For the use case in this work, an IP camera is placed in front of the device to control. The generated stream is decoded. The front of the device is identified using image-processing techniques based on natural feature points. Then, an interactive multimedia based on the MPEG-4 binary format for scenes standard is built and broadcasted to the remote users. In order to handle collaboration, we propose a notification mechanism and communication tools to reproduce the "group awareness", which allows users to apprehend interactions between them. This approach leads us to enrich the MPEG-4 BIFS with the websocket protocol. The use of the semantic web allows us to encode expected sequences of use of the interactive multimedia. Eventually the system provides on the fly interaction adaptations to the end-user. The implementation of a proof of concept is illustrated in contributions to two open source projects : Ocelot (http://ocelot.ow2.org) and GPAC (http://gpac.wp.institut-telecom.fr)

Le principal objectif de cette thèse est de contrôler des objets à deux dimensions dans des scènes distantes, en utilisant des flux multimédia interactifs et contextualisés. Pour le cas d’usage de ces travaux, ces objets sont des instruments de mesures de physique. Une caméra IP est placée devant l’instrument à contrôler. Le flux généré est décodé. L’instrument est reconnu par des méthodes de traitement d’images basées sur les points caractéristiques locaux. Un flux multimédia interactif basé sur le standard « MPEG-4 binary format » construit et envoyé aux utilisateurs distants. Pour supporter la collaboration, nous proposons un mécanisme de notifications ainsi que des outils de communication pour reproduire la « sensation de groupe ». Cela permet aux utilisateurs d’appréhender les interactions entre eux. Cette approche nous a conduit à enrichir le standard MPEG-BIFS avec le protocole websocket. L’utilisation du web sémantique nous permet d’encoder des séquences d’interaction prévues avec l’instrument. Le système permet également de proposer l’adaptation à la volée du flux multimédia. L’implémentation d’un prototype est illustré dans la contribution à deux projets open source : Ocelot (http://ocelot.ow2.org) et GPAC (http://gpac.wp.institut-telecom.fr) / The main objective of this thesis is to propose the control of 2D object in a remote scene, using a contextualized, collaborative and interactive multimedia. The 2D objects are mainly electronic devices. For the use case in this work, an IP camera is placed in front of the device to control. The generated stream is decoded. The front of the device is identified using image-processing techniques based on natural feature points. Then, an interactive multimedia based on the MPEG-4 binary format for scenes standard is built and broadcasted to the remote users. In order to handle collaboration, we propose a notification mechanism and communication tools to reproduce the “group awareness”, which allows users to apprehend interactions between them. This approach leads us to enrich the MPEG-4 BIFS with the websocket protocol. The use of the semantic web allows us to encode expected sequences of use of the interactive multimedia. Eventually the system provides on the fly interaction adaptations to the end-user. The implementation of a proof of concept is illustrated in contributions to two open source projects : Ocelot (http://ocelot.ow2.org) and GPAC (http://gpac.wp.institut-telecom.fr)