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301.
Differential Learning as a Key Training Approach to Improve Creative and Tactical Behavior in Soccer
Sara Santos Diogo Coutinho Bruno Gonçalves Wolfgang Schöllhorn Jaime Sampaio Nuno Leite 《Research quarterly for exercise and sport》2018,89(1):11-24
Purpose: The aim of this study was to identify the effects of a differential-learning program, embedded in small-sided games, on the creative and tactical behavior of youth soccer players. Forty players from under-13 (U13) and under-15 (U15) were allocated into control and experimental groups and were tested using a randomized pretest to posttest design using small-sided games situations. Method: The experimental group participated in a 5-month differential-learning program embodied in small-sided games situations, while the control group participated in a typical small-sided games training program. In-game creativity was assessed through notational analyses of the creative components, and the players’ positional data were used to compute tactical-derived variables. Results: The findings suggested that differential learning facilitated the development of creative components, mainly concerning attempts (U13, small; U15, small), versatility (U13, moderate; U15, small), and originality (U13, unclear; U15, small) of players’ actions. Likewise, the differential-learning approach provided a decrease in fails during the game in both experimental groups (moderate). Moreover, differential learning seemed to favor regularity in pitch-positioning behavior for the distance between players’ dyads (U13, small; U15, small), the distance to the team target (U13, moderate; U15, small), and the distance to the opponent target (U13, moderate; U15, small). Conclusions: The differential-learning program stressed creative and positional behavior in both age groups with a distinct magnitude of effects, with the U13 players demonstrating higher improvements over the U15 players. Overall, these findings confirmed that the technical variability promoted by differential learning nurtures regularity of positioning behavior. 相似文献
302.
Judith Stanja Wolfgang Gritz Johannes Krugel Anett Hoppe Sarah Dannemann 《British journal of educational technology : journal of the Council for Educational Technology》2023,54(1):58-75
Formative assessment is considered to be helpful in students' learning support and teaching design. Following Aufschnaiter's and Alonzo's framework, formative assessment practices of teachers can be subdivided into three practices: eliciting evidence, interpreting evidence and responding. Since students' conceptions are judged to be important for meaningful learning across disciplines, teachers are required to assess their students' conceptions. The focus of this article lies on the discussion of learning analytics for supporting the assessment of students' conceptions in class. The existing and potential contributions of learning analytics are discussed related to the named formative assessment framework in order to enhance the teachers' options to consider individual students' conceptions. We refer to findings from biology and computer science education on existing assessment tools and identify limitations and potentials with respect to the assessment of students' conceptions.
Practitioner notes
What is already known about this topic- Students' conceptions are considered to be important for learning processes, but interpreting evidence for learning with respect to students' conceptions is challenging for teachers.
- Assessment tools have been developed in different educational domains for teaching practice.
- Techniques from artificial intelligence and machine learning have been applied for automated assessment of specific aspects of learning.
- Findings on existing assessment tools from two educational domains are summarised and limitations with respect to assessment of students' conceptions are identified.
- Relevent data that needs to be analysed for insights into students' conceptions is identified from an educational perspective.
- Potential contributions of learning analytics to support the challenging task to elicit students' conceptions are discussed.
- Learning analytics can enhance the eliciting of students' conceptions.
- Based on the analysis of existing works, further exploration and developments of analysis techniques for unstructured text and multimodal data are desirable to support the eliciting of students' conceptions.