Deze uitgave is een eerste verkenning van de mogelijkheden om learning analytics in te zetten bij open en online onderwijs en de Grand Challenges die daarbij spelen. Vijf experts uit de special interest groups Open Education en Learning Analytics identificeerden daartoe de uitdagingen in één van beide gebieden. Per uitdaging is een literatuurstudie uitgevoerd en is onderzocht welke concrete vragen er bestaan, welke nationale en internationale voorbeelden er zijn en welke punten nader onderzoek verdienen.
This paper identifies some common and specific pitfalls in the development of sign language technologies targeted at deaf communities, with a specific focus on signing avatars. It makes the call to urgently interrogate some of the ideologies behind those technologies, including issues of ethical and responsible development. The paper addresses four separate and interlinked issues: ideologies about deaf people and mediated communication, bias in data sets and learning, user feedback, and applications of the technologies. The paper ends with several take away points for both technology developers and deaf NGOs. Technology developers should give more consideration to diversifying their team and working interdisciplinary, and be mindful of the biases that inevitably creep into data sets. There should also be a consideration of the technologies’ end users. Sign language interpreters are not the end users nor should they be seen as the benchmark for language use. Technology developers and deaf NGOs can engage in a dialogue about how to prioritize application domains and prioritize within application domains. Finally, deaf NGOs policy statements will need to take a longer view, and use avatars to think of a significantly better system compared to what sign language interpreting services can provide.
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Over the last two decades, institutions for higher education such as universities and colleges have rapidly expanded and as a result have experienced profound changes in processes of research and organization. However, the rapid expansion and change has fuelled concerns about issues such as educators' technology professional development. Despite the educational value of emerging technologies in schools, the introduction has not yet enjoyed much success. Effective use of information and communication technologies requires a substantial change in pedagogical practice. Traditional training and learning approaches cannot cope with the rising demand on educators to make use of innovative technologies in their teaching. As a result, educational institutions as well as the public are more and more aware of the need for adequate technology professional development. The focus of this paper is to look at action research as a qualitative research methodology for studying technology professional development in HE in order to improve teaching and learning with ICTs at the tertiary level. The data discussed in this paper have been drawn from a cross institutional setting at Fontys University of Applied Sciences, The Netherlands. The data were collected and analysed according to a qualitative approach.
Horse riding falls under the “Sport for Life” disciplines, where a long-term equestrian development can provide a clear pathway of developmental stages to help individuals, inclusive of those with a disability, to pursue their goals in sport and physical activity, providing long-term health benefits. However, the biomechanical interaction between horse and (disabled) rider is not wholly understood, leaving challenges and opportunities for the horse riding sport. Therefore, the purpose of this KIEM project is to start an interdisciplinary collaboration between parties interested in integrating existing knowledge on horse and (disabled) rider interaction with any novel insights to be gained from analysing recently collected sensor data using the EquiMoves™ system. EquiMoves is based on the state-of-the-art inertial- and orientational-sensor system ProMove-mini from Inertia Technology B.V., a partner in this proposal. On the basis of analysing previously collected data, machine learning algorithms will be selected for implementation in existing or modified EquiMoves sensor hardware and software solutions. Target applications and follow-ups include: - Improving horse and (disabled) rider interaction for riders of all skill levels; - Objective evidence-based classification system for competitive grading of disabled riders in Para Dressage events; - Identifying biomechanical irregularities for detecting and/or preventing injuries of horses. Topic-wise, the project is connected to “Smart Technologies and Materials”, “High Tech Systems & Materials” and “Digital key technologies”. The core consortium of Saxion University of Applied Sciences, Rosmark Consultancy and Inertia Technology will receive feedback to project progress and outcomes from a panel of international experts (Utrecht University, Sport Horse Health Plan, University of Central Lancashire, Swedish University of Agricultural Sciences), combining a strong mix of expertise on horse and rider biomechanics, veterinary medicine, sensor hardware, data analysis and AI/machine learning algorithm development and implementation, all together presenting a solid collaborative base for derived RAAK-mkb, -publiek and/or -PRO follow-up projects.
The utilization of drones in various industries, such as agriculture, infrastructure inspection, and surveillance, has significantly increased in recent years. However, navigating low-altitude environments poses a challenge due to potential collisions with “unseen” obstacles like power lines and poles, leading to safety concerns and equipment damage. Traditional obstacle avoidance systems often struggle with detecting thin and transparent obstacles, making them ill-suited for scenarios involving power lines, which are essential yet difficult to perceive visually. Together with partners that are active in logistics and safety and security domains, this project proposal aims at conducting feasibility study on advanced obstacle detection and avoidance system for low-flying drones. To that end, the main research question is, “How can AI-enabled, robust and module invisible obstacle avoidance technology can be developed for low-flying drones? During this feasibility study, cutting-edge sensor technologies, such as LiDAR, radar, camera and advanced machine learning algorithms will be investigated to what extent they can be used be to accurately detect “Not easily seen” obstacles in real-time. The successful conclusion of this project will lead to a bigger project that aims to contribute to the advancement of drone safety and operational capabilities in low-altitude environments, opening new possibilities for applications in industries where low-flying drones and obstacle avoidance are critical.
In the context of global efforts to increase sustainability and reduce CO2 emissions in the chemical industry, bio-based materials are receiving increasing attention as renewable alternatives to petroleum-based polymers. In this regard, Visolis has developed a bio-based platform centered around the efficient conversion of plant-derived sugars to mevalonolactone (MVL) via microbial fermentation. Subsequently, MVL is thermochemically converted to bio-monomers such as isoprene and 3-methyl-1,5-pentane diol, which are ultimately used in the production of polymer materials. Currently, the Visolis process has been optimized to use high-purity, industrial dextrose (glucose) as feedstock for their fermentation process. Dutch Sustainable Development (DSD) has developed a direct processing technology in which sugar beets are used for fermentation without first having to go through sugar extraction and refinery. The main exponent of this technology is their patented Betaprocess, in which the sugar beet is essentially exposed to heat and a mild vacuum explosion, opening the cell walls and releasing the sugar content. This Betaprocess has the potential to speed up current fermentation processes and lower feedstock-related costs. The aim of this project is to combine aforementioned technologies to enable the production of mevalonolactone using sucrose, present in crude sugar beet bray after Betaprocessing. To this end, Zuyd University of Applied Sciences (Zuyd) intends to collaborate with Visolis and DSD. Zuyd will utilize its experience in both (bio)chemical engineering and fermentation to optimize the process from sugar beet (pre)treatment to product recovery. Visolis and DSD will contribute their expertise in microbial engineering and low-cost sugar production. During this collaboration, students and professionals will work together at the Chemelot Innovation and Learning Labs (CHILL) on the Brightlands campus in Geleen. This collaboration will not only stimulate innovation and sustainable chemistry, but also provides starting professionals with valuable experience in this expanding field.
