Hogeschool de Kempel

Teacher Learning Groups (TLGs) are social configurations in which student teachers (henceforth: students) learn together with peers, teacher trainers and teachers through social interactions (Doppenberg et al., 2012). Due to the restrictions caused by the COVID-19 pandemic, blended education has developed quickly. Blended education combines contact learning with distance learning ((Müller & Mildenberger, 2021). This workshop aims to shed light on how blended meetings interfere with the fulfilment of students’ basic psychological needs in TLGs. We also want to find out how to facilitate TLGs to support students’ basic psychological needs in times when social distancing is necessary or when blended education is convenient (e.g., to enhance the accessibility of education).

ABSTRACT Increasingly, teacher learning groups (TLGs) are being deployed as a way to realise high-quality educational designs. There is a need for monitoring and for insights into the development of TLGs. Therefore, in the present study, the ‘Dimensions of Social Learning Questionnaire’ (DSL-Q) is developed that can be used to map the social configuration of TLGs. This article describes the validation of the questionnaire for student teachers, teacher educators and in-service teachers (n = 488) by means of successive exploratory and confirmatory factor analysis, resulting in an instrument with good psychometric properties. The final version of the questionnaire contains 13 items, divided into three factors: practice integration, long-term orientation and goals, and shared identity and equal relationships. The instrument is suitable for quantitative research to gain more insights into the conditional and the outcome variables of social learning. Future research can incorporate theoretical dimensions regarding the value of the social learning process and its outcomes as well as insights concerning socially shared regulation of learning.

ABSTRACT The importance of social learning for student teachers’ professional development has gained acknowledgement. One way in which teacher training institutes incorporate social learning in their curricula is by involving students in teacher learning groups (TLGs). Participation in TLGs not only enables students to develop social skills, but also prevents them from feeling isolated and losing motivation for their studies. The present study uses convergent parallel mixed-methods design to search for relationships between TLGs’ social configuration and motivation among participating students (n = 55) of four Dutch primary teacher training institutes. The analyses reveal seven key variables for student motivation in TLGs: autonomous choices regarding content; new knowledge; sharing, support, and social skills; personal goals; autonomous choices regarding collaborating partners; scaffolding; equality in an informal atmosphere. Based on the findings, we advise teacher training institutes to consider integrating homogeneous and heterogeneous TLGs in their curricula, because both are valuable for student motivation.

ABSTRACT This study presents design principles for student facilitation in teacher learning groups (TLGs), based on a systematic literature review searching for characteristics, conditions, and outcomes of students working in TLGs. Notions of team learning, network learning, community learning, and collective learning within teacher education were taken as the main components of the search. The review turned out to be very lean in terms of input; only 17 articles did justice to this theme. The exercise resulted in five main characteristics of TLGs (i.e. shared vision and goals; a project-based approach; shared responsibility and ownership; diversity and equality; supportive structures, resources and roles) and associated conditional factors. We combined these characteristics and conditional factors to formulate design principles, which can serve as a starting point for the supervision of students in TLGs. The limited number of search results shows that more research into student learning in TLGs is needed. Furthermore, the design principles yielded by the review are formulated in very general terms. In follow-up research, we will monitor four institutes for primary teacher education that enable student learning in TLGs with various social configurations. This study is expected to further concretise the design principles for student learning in TLGs.

Listening to young children’s voices is an issue with increasing relevance for many researchers in the field of early childhood research. At the same time, teachers and researchers are faced with challenges to provide children with possibilities to express their notions, and to find ways of comprehending children’s voices. In our research we aim to provide a method for listening to, and analyzing young children’s voices on educational issues. In this article we describe a new step in our research in which we are dealing with the issues of validity and reliability for the evaluation of our coding system: is our coding system for analyzing young children’s voices valid and reliable?

The development of an in-home fall risk assessment tool is under investigation. Several fall risk screening tests such as the Timed-Get-Up-and-Go-test (TGUG) only provide a snapshot taken at a given time and place, where automated in-home fall risk assessment tools can assess the fall risk of a person on a continuous basis. During this study we monitored four older people in their own home for a period of three months and automatically assessed fall risk parameters. We selected a subset of fixed walking sequences from the resulting real-life video for analysis of the time needed to perform these sequences. The results show a significant diurnal and health-related variance in the time needed to cross the same distance. These results also suggest that trends in the transfer time can be detected with the presented system.

BackgroundThe aim of electroencephalogram (EEG) source localization is to find the brain areas responsible for EEG waves of interest. It consists of solving forward and inverse problems. The forward problem is solved by starting from a given electrical source and calculating the potentials at the electrodes. These evaluations are necessary to solve the inverse problem which is defined as finding brain sources which are responsible for the measured potentials at the EEG electrodes.MethodsWhile other reviews give an extensive summary of the both forward and inverse problem, this review article focuses on different aspects of solving the forward problem and it is intended for newcomers in this research field.ResultsIt starts with focusing on the generators of the EEG: the post-synaptic potentials in the apical dendrites of pyramidal neurons. These cells generate an extracellular current which can be modeled by Poisson's differential equation, and Neumann and Dirichlet boundary conditions. The compartments in which these currents flow can be anisotropic (e.g. skull and white matter). In a three-shell spherical head model an analytical expression exists to solve the forward problem. During the last two decades researchers have tried to solve Poisson's equation in a realistically shaped head model obtained from 3D medical images, which requires numerical methods. The following methods are compared with each other: the boundary element method (BEM), the finite element method (FEM) and the finite difference method (FDM). In the last two methods anisotropic conducting compartments can conveniently be introduced. Then the focus will be set on the use of reciprocity in EEG source localization. It is introduced to speed up the forward calculations which are here performed for each electrode position rather than for each dipole position. Solving Poisson's equation utilizing FEM and FDM corresponds to solving a large sparse linear system. Iterative methods are required to solve these sparse linear systems. The following iterative methods are discussed: successive over-relaxation, conjugate gradients method and algebraic multigrid method.ConclusionSolving the forward problem has been well documented in the past decades. In the past simplified spherical head models are used, whereas nowadays a combination of imaging modalities are used to accurately describe the geometry of the head model. Efforts have been done on realistically describing the shape of the head model, as well as the heterogenity of the tissue types and realistically determining the conductivity. However, the determination and validation of the in vivo conductivity values is still an important topic in this field. In addition, more studies have to be done on the influence of all the parameters of the head model and of the numerical techniques on the solution of the forward problem.

this paper we study plane curves of degree d with e total inflection points, for nonzero natural numbers d and e.