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Hybrid Learning Environments

This paper deals with the problematic nature of the transition between education and the workplace. A smooth transition between education and the workplace requires learners to develop an integrated knowledge base, but this is problematic as most educational programmes offer knowledge and experiences in a fragmented manner, scattered over a variety of subjects, modules and (work) experiences. To overcome this problem, we propose a design approach and shifting the educational focus of attention from individual learners to learning environments. The broader notion of learning environments facilitates transitions by establishing horizontal connections between schools and the workplace. The main argument of this paper is that combining or connecting aspects of school-based settings only is not sufficient to ensure learners will develop an integrated knowledge base. The concept and examples of “hybrid learning environment” show how formal, school-based learning and workplace experiences can be closely connected. The paper offers a framework of four coherent perspectives that can help to understand the complex nature of such environments and to design hybrid learning environments: the “agency perspective”, the “spatial perspective”, the “temporal perspective”, and the “instrumental perspective”. The framework is applied to three cases taken from vocational education in the Netherlands to describe what hybrid learning environments look like in contemporary educational practice. RÉSUMÉ

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12/31/2011
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Similar but different

The purpose of this study was to provide more insight into how the physical education (PE) context can be better tailored to the diverse motivational demands of secondary school students. Therefore, we examined how different constructs of student motivation in the context of PE combine into distinct motivational profiles, aiming to unveil motivational similarities and differences between students’ PE experiences. Participants were 2,562 Dutch secondary school students, aged 12–18, from 24 different schools. Students responded to questionnaires assessing their perception of psychological need satisfaction and frustration, and perceived mastery and performance climate in PE. In order to interpret the emerging profiles additional variables were assessed (i.e. demographic, motivational and PE-related variables). Two-step cluster analysis identified three meaningful profiles labelled as negative perceivers, moderate perceivers and positive perceivers. These three profiles differed significantly with regard to perceived psychological need satisfaction and frustration and their perception of the motivational climate. This study demonstrates that students can be grouped in distinct profiles based on their perceptions of the motivational PE environment. Consequently, the insights obtained could assist PE teachers in designing instructional strategies that target students’ differential motivational needs.

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02/09/2020
Similar but different
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A First Step Towards Learning Analytics

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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06/17/2017
A First Step Towards Learning Analytics