Presentatie tijdens studiedag Blended Learning van Vereniging Hogescholen, Utrecht.
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This study focuses on students’ approaches to learning, particularly in innovative learning environments. A person-oriented research perspective was chosen to search for nuances and details that add to existing knowledge on secondary students’ learning. The relation between students’ goal orientations, learning strategies, and different learning environments was investigated via questionnaires and interviews. The questionnaire study revealed four profiles of 673 students’ (meta-)cognitive learning strategies. Differences in student learning were found between students of an innovative school and students of regular schools, indicating that learning strategies are elicited by the learning environments students are confronted with. The interview study with 20 students from the innovative school illustrated their learning in learning environments typical for this school. Results revealed how students from different profiles differed in their goal orientations and learning strategies and that these differences were related to students’ need for teacher support when learning. The results of this study provide qualitative and quantitative insight in (enhancing) secondary students’ learning, doing justice to the learners as persons and individual differences.
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Recently, more students have entered Dutch higher education. This is a consequence of the possibility to offer students to enter higher education, with a certificate from senior secondary education (SSVE). In earlier days most students in higher education had passed senior general secondary education (SGSE), or even pre-university education. It is to be expected that these 'new' students approach learning in a different way compared to the 'traditional' students in higher education. The goal of this study was to examine the possible differences between the two groups of students mentioned, and to gain insights in the role possible differences play in the way the two groups of students approach learning. Students' personality characteristics, regulation strategies, learning conceptions and motivational orientations were studied in relation to study approaches. It was assumed that patterns of relations between the variables mentioned would be different for the two groups of students. More specifically, it was expected to find stronger and more crystallised relations between variables within the group of SSVE-students. Indeed, when entering Higer Education, SSVE students scored higher than SGSE students on the personality variables autonomy and conscientiousness; as to their personal orientations on learning and instruction they were more self-test oriented and they scored higher on concrete processing and construction of knowledge. However, the strength and direction of the relations between the variables are the same for both groups. Our findings increase insights into relations between students' personalities and their approaches to learning when entering higher education; this concerns two groups of students from different educational backgrounds. Practically this implies that intake assessments considering personality and self-knowledge might help teachers, coaches and policy makers in advising students how to appraoch learning, when entering higher education. Copyright Elsevier Inc.
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Aim of this study is to gain more insights into conditions and approaches used by sport club consultants, affecting the vitalization process of voluntary sport clubs. This study is part of a larger research the competencies, approaches and interventions which sport club consultants need to provide support on vitalization processes in voluntary sport clubs.
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Technologie in het onderwijs wordt mondjesmaat toegepast (zie bijvoorbeeld Schildkamp, Wopereis, KatDe Jong, Peet & Hoetjes, 2020). Alle onderwijsinstellingen hebben tegenwoordig weliswaar een digitale leeromgeving, doch een optimaal gebruik ervan is nog niet gerealiseerd. In veel situaties wordt de digitale leeromgeving voornamelijk gebruikt voor administratieve functies en voor de beschikbaarstelling van leermiddelen. De Coronapandemie heeft voor een ongekende exponentiële groei in het gebruik van technologie gezorgd. Eenvoudigweg omdat de gebruikelijke manieren van lesgeven onmogelijk werden. In een mum van tijd schakelden docenten over naar Teams, Zoom of andere vergelijkbare technologie, werden colleges opgenomen of gestreamd, webinars ontwikkeld, kennisclips gemaakt en online gezet en werd de leeromgeving verder doorontwikkeld om communicatie synchroon en asynchroon te verbeteren. Dat is een prestatie van formaat waardoor het onderwijs in tijden van de pandemie online door kon blijven gaan. Zo ontstonden er door een mix van fysiek en online onderwijs allerlei vormen van blended learning. Blended Learning is een populair concept waar echter zeer uiteenlopende betekenissen achter schuil gaan (Oliver & Trigwell, 2005). Een allesomvattende definitie die op ieders instemming kan rekenen, is een utopie maar de omschrijving van SURF (2020) wordt frequent gehanteerd: Blended learning is een mengvorm van face-to-face en online (ICT-gebaseerde) onderwijsactiviteiten, leermaterialen en tools. Beide soorten leeractiviteiten maken een substantieel onderdeel uit van het onderwijs; idealiter versterken ze elkaar. Het doel is onderwijs te ontwikkelen dat gebruik maakt van ICT om effectief, efficiënt en flexibel leren mogelijk te maken, met een stijging van het leerrendement en de student- en docenttevredenheid tot gevolg. Vanwege het Coronavirus zien we dat onderwijsactiviteiten die voorheen op locatie in een onderwijssetting plaatsvonden, nu voornamelijk online plaatsvinden waarbij studenten en docenten inloggen in Teams, Zoom, Bluejeans of een vergelijkbare omgeving. De inhoud van het onderwijs of manier van lesgeven verandert echter niet of nauwelijks. Dit is illustratief voor wat we verstaan onder blended learning in de vorm van substitutie. Er is dan sprake van een vervanging: Het klaslokaal wordt ingeruild voor Teams. Ook al is straks de coronapandemie voorbij, dan gaan we er van uit dat het onderwijs meer blended zal blijven dan voorheen, omdat we nu op grote schaal de mogelijkheden ervaren van technologische toepassingen en die willen we behouden en verder uitbouwen. Er is momentum om na te denken over hoe te komen tot een meer optimale blend, en dus niet in de fase van substitutie te blijven verkeren, hetgeen vraagt om een herontwerp van het onderwijs. Met dit essay willen we hier de aandacht op vestigen.
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Hoofdstuk 2 uit Position paper Learning Communities van Netwerk learning Communities Grote maatschappelijke uitdagingen op het gebied van vergrijzing, duurzaamheid, digitalisering, segregatie en onderwijskwaliteit vragen om nieuwe manieren van werken, leren en innoveren. In toenemende mate wordt daarom ingezet op het bundelen van kennis en expertise van zowel publieke als private organisaties, die elkaar nodig hebben om te innoveren en complexe vraagstukken aan te pakken. Het concept ‘learning communities’ wordt gezien als dé oplossing om leren, werken en innoveren anders met elkaar te verbinden: collaboratief, co-creërend en contextrijk. Vanuit het Netwerk Learning Communities is een groep onafhankelijk onderzoekers van een groot aantal Nederlandse kennisinstellingen aan de slag gegaan met een kennissynthese rondom het concept ‘Learning Community’. Het Position paper is een eerste aanzet tot kennisbundeling. Een ‘levend document’ dat in de komende tijd verder aangevuld en verrijkt kan worden door onderzoekers, praktijkprofessionals en beleidsmakers.
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Learning theories broadly characterised as constructivist, agree on the importance to learning of the environment, but differ on what exactly it is that constitutes this importance. Accordingly, they also differ on the educational consequences to be drawn from the theoretical perspective. Cognitive constructivism focuses on the active role of the learner, and on real-life learning. Social-learning theories, comprising the socio-historical, socio-cultural theories as well as the situated-learning and community-of-practice approaches, emphasise learning as being a process within and a product of the social context. Critical-learning theory stresses that this social context is a man-made construction, which should be approached critically and transformed in order to create a better world. We propose to view these different approaches as contributions to our understanding of the learning-environment relationship, and their educational impact as questions to be addressed to educational contexts.
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The use of machine learning in embedded systems is an interesting topic, especially with the growth in popularity of the Internet of Things (IoT). The capacity of a system, such as a robot, to self-localize, is a fundamental skill for its navigation and decision-making processes. This work focuses on the feasibility of using machine learning in a Raspberry Pi 4 Model B, solving the localization problem using images and fiducial markers (ArUco markers) in the context of the RobotAtFactory 4.0 competition. The approaches were validated using a realistically simulated scenario. Three algorithms were tested, and all were shown to be a good solution for a limited amount of data. Results also show that when the amount of data grows, only Multi-Layer Perception (MLP) is feasible for the embedded application due to the required training time and the resulting size of the model.
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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."
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To adequately deal with the challenges faced within residential care for older people, such as the increasing complexity of care and a call for more person-centred practices, it is important that health care providers learn from their work. This study investigates both the nature of learning, among staff and students working within care for older people, and how workplace learning can be promoted and researched. During a longitudinal study within a nursing home, participatory and democratic research methods were used to collaborate with stakeholders to improve the quality of care and to promote learning in the workplace. The rich descriptions of these processes show that workplace learning is a complex phenomenon. It arises continuously in reciprocal relationship with all those present through which both individuals and environment change and co-evolve enabling enlargement of the space for possible action. This complexity perspective on learning refines and expands conventional beliefs about workplace learning and has implications for advancing and researching learning. It explains that research on workplace learning is itself a form of learning that is aimed at promoting and accelerating learning. Such research requires dialogic and creative methods. This study illustrates that workplace learning has the potential to develop new shared values and ways of working, but that such processes and outcomes are difficult to control. It offers inspiration for educators, supervisors, managers and researchers as to promoting conditions that embrace complexity and provides insight into the role and position of self in such processes.
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