Background: Differential learning (DL) is a motor learning method characterized by high amounts of variability during practice and is claimed to provide the learner with a higher learning rate than other methods. However, some controversy surrounds DL theory, and to date, no overview exists that compares the effects of DL to other motor learning methods.Objective: To evaluate the effectiveness of DL in comparison to other motor learning methods in the acquisition and retention phase.Design: Systematic review and exploratory meta-analysis.Methods: PubMed (MEDLINE), Web of Science, and Google Scholar were searched until February 3, 2020. To be included, (1) studies had to be experiments where the DL group was compared to a control group engaged in a different motor learning method (lack of practice was not eligible), (2) studies had to describe the effects on one or more measures of performance in a skill or movement task, and (3) the study report had to be published as a full paper in a journal or as a book chapter.Results: Twenty-seven studies encompassing 31 experiments were included. Overall heterogeneity for the acquisition phase (post-pre; I2 = 77%) as well as for the retention phase (retention-pre; I2 = 79%) was large, and risk of bias was high. The meta-analysis showed an overall small effect size of 0.26 [0.10, 0.42] in the acquisition phase for participants in the DL group compared to other motor learning methods. In the retention phase, an overall medium effect size of 0.61 [0.30, 0.91] was observed for participants in the DL group compared to other motor learning methods.Discussion/Conclusion: Given the large amount of heterogeneity, limited number of studies, low sample sizes, low statistical power, possible publication bias, and high risk of bias in general, inferences about the effectiveness of DL would be premature. Even though DL shows potential to result in greater average improvements between pre- and post/retention test compared to non-variability-based motor learning methods, more high-quality research is needed before issuing such a statement. For robust comparisons on the relative effectiveness of DL to different variability-based motor learning methods, scarce and inconclusive evidence was found.
https://www.researchgate.net/publication/323361454_Design_Implementation_of_Technology-Enhanced_Workplace_Learning/references DOI: 10.13140/RG.2.2.26079.56489
From the article: "The educational domain is momentarily witnessing the emergence of learning analytics – a form of data analytics within educational institutes. Implementation of learning analytics tools, however, is not a trivial process. This research-in-progress focuses on the experimental implementation of a learning analytics tool in the virtual learning environment and educational processes of a case organization – a major Dutch university of applied sciences. The experiment is performed in two phases: the first phase led to insights in the dynamics associated with implementing such tool in a practical setting. The second – yet to be conducted – phase will provide insights in the use of pedagogical interventions based on learning analytics. In the first phase, several technical issues emerged, as well as the need to include more data (sources) in order to get a more complete picture of actual learning behavior. Moreover, self-selection bias is identified as a potential threat to future learning analytics endeavors when data collection and analysis requires learners to opt in."
Aiming for a more sustainable future, biobased materials with improved performance are required. For biobased vinyl polymers, enhancing performance can be achieved by nanostructuring the material, i.e. through the use of well-defined (multi-)block, gradient, graft, comb, etc., copolymer made by controlled radical polymerization (CRP). Dispoltec has developed a new generation of alkoxyamines, which suppress termination and display enhanced end group stability compared to state-of-art CRP. Hence, these alkoxyamines are particularly suited to provide access to such biobased nanostructured materials. In order to produce alkoxyamines in a more environmentally benign and efficient manner, a photo-chemical step is beneficial for the final stage in their synthesis. Photo-flow chemistry as a process intensification technology is proposed, as flow chemistry inherently leads to more efficient reactions. In particular, photo-flow offers the benefit of significantly enhancing reactant concentrations and reducing batch times due to highly improved illumination. The aim of this project is to demonstrate at lab scale the feasibility of producing the new generation of alkoxy-amines via a photo-flow process under industrially relevant conditions regarding concentration, duration and efficiency. To this end, Zuyd University of Applied Sciences (Zuyd), CHemelot Innovation and Learning Labs (CHILL) and Dispoltec BV want to enter into a collaboration by combining the expertise of Dispoltec on alkoxyamines for CRP with those of Zuyd and CHILL on microreactor technology and flow chemistry. Improved access to these alkoxyamines is industrially relevant for initiator manufacturers, as well as producers of biobased vinyl polymers and end-users aiming to enhance performance through nanostructuring biobased materials. In addition, access in this manner is a clear demonstration for the high industrial potential of photo-flow chemistry as sustainable manufacturing tool. Further to that, students and professionals working together at CHILL will be trained in this emerging, industrially relevant and sustainable processing tool.
Hbo-studenten doen tijdens hun opleiding werkervaring op, bijvoorbeeld door stage te lopen. Wij onderzoeken op welke manier technologie het leerproces van studenten op de werkplek kan ondersteunen. We ontwikkelen ontwerpprincipes en de daarop gebaseerde Stage-App.Doel Studenten leren op de werkplek heel anders dan op de hogeschool. Het leren gebeurt vaak onbewust en impliciet. De Stage-App helpt studenten bewuster te worden van dit leerproces en hier actiever mee bezig te zijn, om uiteindelijk meer uit hun stage te halen. Resultaten Dit onderzoek loopt. We hebben de resultaten tot nu toe gedeeld via posters, presentaties en artikelen. Gepubliceerde artikelen Exploring Design Principles for Technology-Enhanced Workplace Learning Design Propositions for Technology-Enhanced Workplace Learning Design & Implementation of Technology-Enhanced Workplace Learning Learning Analytics voor Stages en Werkplekleren Workplace Learning Analytics in Higher Engineering Education Automated Feedback for Workplace Learning in Higher Education De open-source Stage-App is beschikbaar via Github.com. Looptijd 01 november 2015 - 31 december 2020 Aanpak In het eerste deel van onderzoek hebben we uitgezocht wat er nodig is om een app voor het leerproces te ontwerpen. Vervolgens hebben we de Stage-App ontwikkeld. Daarin kunnen studenten registreren wat ze hebben geleerd en dit koppelen aan de leerdoelen die ze vanuit hun opleiding meekrijgen. We ontwikkelen de app zoveel mogelijk vanuit het perspectief van de student. Om de app aan te laten sluiten op de wensen en eisen van studenten houden we interviews, enquêtes, gebruikerstesten en co-design-sessies. Tegelijkertijd baseren we de functionaliteiten op literatuuronderzoek over werkplekleren en 'technology enhanced learning', om te zorgen dat de app het leerproces zo goed mogelijk ondersteunt.
