Learning activities in a makerspace are hands-on and characterized by design and inquiry. Evaluation is needed both for learners and their coaches in order to effectively guide the learning process of the children and for feedback on the effectiveness of the after-school maker activities. Due to its constructionist nature, learning in a makerspace requires specific forms of evaluation. In this paper we describe the development of an instrument that facilitates and captures reflection on the activities that children undertook in a library makerspace. Our aim is to capture learning in this context with multiple instruments: analysis of the artifacts that are made, observation of hands-on activities and interviews - which all are time consuming methods. Hence, we developed an easy to use tool for self-evaluation of maker learner activities for children. We build on the design of a visual instrument used for learning by design and inquiry in primary education. The findings and results are transferable to (formative) assessment and evaluation of learning activities by learners in other types of education and specific in maker education.
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The present study aimed to develop a football-specific self-report instrument measuring self-regulated learning in the context of daily practice, which can be used to monitor the extent to which players take responsibility for their own learning. Development of the instrument involved six steps: 1. Literature review based on Zimmerman's (2006) theory of self-regulated learning, 2. Item generation, 3. Item validation, 4. Pilot studies, 5. Exploratory factor analysis (EFA), and 6. Confirmatory factor analysis (CFA). The instrument was tested for reliability and validity among 204 elite youth football players aged 13-16 years (Mage = 14.6; s = 0.60; 123 boys, 81 girls). The EFA indicated that a five-factor model fitted the observed data best (reflection, evaluation, planning, speaking up, and coaching). However, the CFA showed that a three-factor structure including 22 items produced a satisfactory model fit (reflection, evaluation, and planning; non-normed fit index [NNFI] = 0.96, comparative fit index [CFI] = 0.95, root mean square error of approximation [RMSEA] = 0.067). While the self-regulation processes of reflection, evaluation, and planning are strongly related and fit well into one model, other self-regulated learning processes seem to be more individually determined. In conclusion, the questionnaire developed in this study is considered a reliable and valid instrument to measure self-regulated learning among elite football players.
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