A study of the improvement of the quality of student teachers’ lessons in interactive (story)book reading through the use of data-feedback on observed lessons. Variables regarding the optimal time use, the quality of instruction and the student teachers’ pedagogical relation with pupils were included in a one group pre-test post-test design.
In dit rapport wordt verslag uitgebracht van het onderzoek naar de resultaten van de toepassing van een cyclisch model voor observatie en data-gestuurde feedback.
De meest gebruikte opbouw in business intelligence, predictive analitics en analytics modellen is de moeilijkheidsgraad: 1) descriptive, 2) diagnostic, 3) predictive en 4) prescriptive. Deze schaal vertelt iets over de volwassenheid van het gebruik van data door de organisatie. Een model dat niet op zichzelf staat en een achterliggende methode kent is de data driehoek van EDM (Figuur 1), welke in dit artikel zal worden toegelicht.
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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.
Physical rehabilitation programs revolve around the repetitive execution of exercises since it has been proven to lead to better rehabilitation results. Although beginning the motor (re)learning process early is paramount to obtain good recovery outcomes, patients do not normally see/experience any short-term improvement, which has a toll on their motivation. Therefore, patients find it difficult to stay engaged in seemingly mundane exercises, not only in terms of adhering to the rehabilitation program, but also in terms of proper execution of the movements. One way in which this motivation problem has been tackled is to employ games in the rehabilitation process. These games are designed to reward patients for performing the exercises correctly or regularly. The rewards can take many forms, for instance providing an experience that is engaging (fun), one that is aesthetically pleasing (appealing visual and aural feedback), or one that employs gamification elements such as points, badges, or achievements. However, even though some of these serious game systems are designed together with physiotherapists and with the patients’ needs in mind, many of them end up not being used consistently during physical rehabilitation past the first few sessions (i.e. novelty effect). Thus, in this project, we aim to 1) Identify, by means of literature reviews, focus groups, and interviews with the involved stakeholders, why this is happening, 2) Develop a set of guidelines for the successful deployment of serious games for rehabilitation, and 3) Develop an initial implementation process and ideas for potential serious games. In a follow-up application, we intend to build on this knowledge and apply it in the design of a (set of) serious game for rehabilitation to be deployed at one of the partners centers and conduct a longitudinal evaluation to measure the success of the application of the deployment guidelines.
In het RAAK-project, genaamd Groningen MAPS, is er veel data en kennis vergaard van waaruit antwoorden zijn geformuleerd op verschillende vragen rondom belasting en belastbaarheid van (top)sporters. Het onderzoek naar de factoren die invloed hebben op de prestaties en het blessurerisico van sporters heeft opgeleverd dat we nu meer inzicht hebben in de informatie die nodig is om gericht te zoeken naar verbanden tussen belasting en belastbaarheid. We hebben echter nog niet gekeken naar de data vanuit een datamining perspectief. Datamining is het gericht zoeken naar verbanden in een database met als doel het opstellen van profielen. Deze profielen kunnen nieuwe inzichten geven waardoor sporters van nog betere feedback voorzien kunnen worden. Het doel van het Top-up project is om kennis te ontwikkelen over het automatiseren van de verwerking en analyse van datastromen. Dit zal leiden tot een datasysteem wat automatisch analyses uitvoert achter de schermen. Met dit datasysteem kan de Groningen MAPS-data verder geanalyseerd worden (door middel van datamining) om nieuw inzicht te verkrijgen op het gebied van patronen in belasting en belastbaarheid van (top)sporters.
