Abstract
In the field of immersive learning, instructors often find it challenging to match their pedagogical approaches and content knowledge with specific technologies. Unfortunately, this usually results in either a lack of technology use or inappropriate use of some technologies. Teachers and trainers wishing to use immersive learning environments face a diversity of technological and pedagogical alternatives. To scaffold educators in their planning of immersive learning educational activities, we devised a recommendation tool, which maps educational context variables to the dimensions of immersion and uses educators' contexts to identify the closest educational uses. Sample educational activities for those uses are then presented, for various types of educational methodologies. Educators can use these samples to plan their educational activities in line with their current resources or to innovate by pursuing entirely different approaches.

Abstract
Crowdsourcing has received considerable attention over the last fifteen years and has been the subject of several experiments that demonstrate its large potential for use in real-world situations. With the rapid growth of and access to crowd work environments, there is a need for new ways to ensure more equitable access for all people. Task design is one of the core aspects of the crowdsourcing process and its optimization is a priority for many requesters that want to have their tasks solved in short times and with high levels of accuracy. Aligned with this goal, a cognitive personalization framework can make it feasible to assess the information processing preferences of crowd workers in order to provide a useful user interface (UI) adaptation. In an effort to address this issue, this study recruited a total of 64 crowd workers to take cognitive style tests and perform prototypical tasks. The results indicate that it is possible to apply short tests and then obtain some useful indicators for better matching tasks to workers with implications for improving the general outcomes and acceptance rates in crowdsourcing.

Abstract
Virtual reality (VR) is used in different application fields like health, tourism, or training. Most VR applications for these fields have been built from the ground up without any authoring tool to help the process. This systematic review surveys the existing literature on authoring tools for immersive content and critically analyzes its features and how they are evaluated. It proposes a research agenda with key contribution opportunities for the field. An analysis of the 29 studies that met the eligibility criteria revealed that four records did not present any evaluation regarding the authoring tools' evaluation, and only five records used specialized users to evaluate their authoring tools; all the others used non-specialized users. The most evaluated metrics were usability, effectiveness, efficiency, and satisfaction. The data collected to evaluate the metrics consisted mainly of Likert scales and reported mean opinion score (MOS). However, few records used well-established questionnaires to evaluate those metrics like System Usability Scale, Post-Study System Usability Questionnaire, After-Scenario Questionnaire and Igroup Presence Questionnaire. Additionally, five of the analyzed records included stimuli other than audiovisual. More research is recommended about the usage of ontologies in authoring tools to comprehend the full potential of its usage since none of them had ontologies.

Abstract
Today digital labor increasingly advocates for the inclusion of people who are excluded from society in someway. The proliferation of crowdsourcing as a new form of digital labor consisting mainly of microtasks that are characterized by a low level of complexity and short time periods in terms of accomplishment has allowed a wide spectrum of people to access the digital job market. However, there is a long-recognized mismatch between the expectations of employers and the capabilities of workers in microwork crowdsourcing marketplaces. Cognitive personalization has the potential to tailor microtasks to crowd workers, thus ensuring increased accessibility by providing the necessary coverage for individuals with disabilities and special needs. In this paper an architecture for a crowdsourcing system intended to support cognitive personalization in the design of microtasks is introduced. The architecture includes an ontology built for the representation of knowledge on the basis of the concepts of microtasks, cognitive abilities, and types of adaptation in order to personalize the interface to the crowd worker. The envisioned system contains a backend and a frontend that serve as an intermediary layer between the crowdsourcing platform and the workers. Finally, some results obtained to evaluate the proposed system are presented.

Abstract
Despite documentation being considered the primary challenge to agile methods in safety-critical software systems development [1], agile would be of particular interest to improve changeability while providing efficiency and effectiveness to all the phases of software development. In this work, we created mechanisms for automating document processing and management to improve the efficiency and effectiveness of documentation activities of safety-critical software systems development, most concretely in the aerospace domain. The implemented tools were co-designed and validated iteratively in the concrete industrial context of Critical Software (CSW) projects, within a wider research work towards continuous certification [3]. We interviewed Critical Software professionals to validate our solution, collected feedback on the implemented tools and got insights for future work. The tools were also the target of synthetic tests that allowed us to conclude that document automation is possible in the critical-safety software development industry and carries several benefits. The developed tools are not yet qualified in compliance with the DO-330 standard (Tools Qualification).

Abstract
Currently, business organizations are struggling with the increasing demand for learning needs to address their knowledge gaps. They must have a structure that can reach all employees in terms of training and extract all the important data which is collected by Learning Management Systems during the instruction or learning process. This data will be of extreme importance for better business decisions. In this paper, it is presented a Systematic Literature Review with their respective phases duly explained and framed in the topic. It allowed us to understand the benefits, challenges, enablers, and inhibitors of the deployment and usage of a specified Teaching-Learning Analytics Framework. Finally, it is concluded, that the development of a reference model, could fulfill this gap in knowledge and help business organizations to allocate resources better and improve the decision-making process as well as an instructional and learning process. To achieve the final goal of this research, future work about the development of a Survey Research methodology will be started to fulfill this gap of knowledge.