The Experts below are selected from a list of 24009 Experts worldwide ranked by ideXlab platform
Saeema Ahmedkristensen - One of the best experts on this subject based on the ideXlab platform.
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empirically analysing Design reasoning patterns abductive deductive reasoning patterns dominate Design idea generation
Design Studies, 2019Co-Authors: Claus Lundgaard Cramerpetersen, Bo T Christensen, Saeema AhmedkristensenAbstract:Reasoning is a fundamental process in Design Activity, and it provides a way to understand Design behaviour. Theories and models of Design propose reasoning that follows abductive-deductive patterns. At the micro-level, these patterns are untested. This study analyses verbal reasoning patterns at the micro-level for group idea generation using protocol analyses of concurrent verbalisations from five Design teams with industry participants. The results show that reasoning in Design Activity across 218 ideas follows general patterns of abductive-deductive reasoning. At the individual idea level, the reasoning patterns are disorderly and enter into micro-patterns of inference. The study concludes that understanding reasoning at early-stage idea generation processes is indicative of the mental models and abductive-deductive reasoning that are prevalent in Design Activity.
Patricia Osseweijer - One of the best experts on this subject based on the ideXlab platform.
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An analysis of the impact of student–scientist interaction in a technology Design Activity, using the expectancy-value model of achievement related choice
International Journal of Technology and Design Education, 2016Co-Authors: Anne-lotte Masson, Tanja Klop, Patricia OsseweijerAbstract:Many education initiatives in science and technology education aim to create enthusiasm among young people to pursue a career in Science, Technology, Engineering, and Mathematics (STEM). Research suggests that personal interaction between secondary school students and scientists could be a success factor, but there is a need for more in-depth research on the actual effects of science education initiatives. This paper describes an in-depth, qualitative assessment of a technology Design Activity, using as a theoretical framework the expectancy-value model of academic choice Eccles and Wigfield (Annu Rev Psychol 53:109–132, 2002 ). A core element in the studied education initiative is the interaction between secondary school students and scientists. Semi-structured interviews were conducted with participating students and analysed qualitatively to disentangle the factors in their motivation to participate in this initiative and their experiences and memories gathered during participation. Last, this paper reflects on the use of the expectancy-value model for in-depth assessments of science education initiatives. Results show that interest-enjoyment values and attainment values are most important in the students’ motivation to participate in the studied Activity. These values are connected to educational principles of authentic practice, and of providing meaningful contexts for scientific concepts. Furthermore, results show that the interaction between students and scientists is not automatically a success factor. Disappointment in this interaction, can cast a shadow on students’ whole experience. This leads us to propose to include an additional factor in the expectancy-value model of achievement related choice: educational environment, including ‘personal interaction’ as an element. Adding this factor would—in our opinion—create an even better framework for in-depth assessment of science education initiatives.
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an analysis of the impact of student scientist interaction in a technology Design Activity using the expectancy value model of achievement related choice
International Journal of Technology and Design Education, 2016Co-Authors: Anne-lotte Masson, Tanja Klop, Patricia OsseweijerAbstract:Many education initiatives in science and technology education aim to create enthusiasm among young people to pursue a career in Science, Technology, Engineering, and Mathematics (STEM). Research suggests that personal interaction between secondary school students and scientists could be a success factor, but there is a need for more in-depth research on the actual effects of science education initiatives. This paper describes an in-depth, qualitative assessment of a technology Design Activity, using as a theoretical framework the expectancy-value model of academic choice Eccles and Wigfield (Annu Rev Psychol 53:109–132, 2002). A core element in the studied education initiative is the interaction between secondary school students and scientists. Semi-structured interviews were conducted with participating students and analysed qualitatively to disentangle the factors in their motivation to participate in this initiative and their experiences and memories gathered during participation. Last, this paper reflects on the use of the expectancy-value model for in-depth assessments of science education initiatives. Results show that interest-enjoyment values and attainment values are most important in the students’ motivation to participate in the studied Activity. These values are connected to educational principles of authentic practice, and of providing meaningful contexts for scientific concepts. Furthermore, results show that the interaction between students and scientists is not automatically a success factor. Disappointment in this interaction, can cast a shadow on students’ whole experience. This leads us to propose to include an additional factor in the expectancy-value model of achievement related choice: educational environment, including ‘personal interaction’ as an element. Adding this factor would—in our opinion—create an even better framework for in-depth assessment of science education initiatives.
Claus Lundgaard Cramerpetersen - One of the best experts on this subject based on the ideXlab platform.
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empirically analysing Design reasoning patterns abductive deductive reasoning patterns dominate Design idea generation
Design Studies, 2019Co-Authors: Claus Lundgaard Cramerpetersen, Bo T Christensen, Saeema AhmedkristensenAbstract:Reasoning is a fundamental process in Design Activity, and it provides a way to understand Design behaviour. Theories and models of Design propose reasoning that follows abductive-deductive patterns. At the micro-level, these patterns are untested. This study analyses verbal reasoning patterns at the micro-level for group idea generation using protocol analyses of concurrent verbalisations from five Design teams with industry participants. The results show that reasoning in Design Activity across 218 ideas follows general patterns of abductive-deductive reasoning. At the individual idea level, the reasoning patterns are disorderly and enter into micro-patterns of inference. The study concludes that understanding reasoning at early-stage idea generation processes is indicative of the mental models and abductive-deductive reasoning that are prevalent in Design Activity.
Anne-lotte Masson - One of the best experts on this subject based on the ideXlab platform.
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An analysis of the impact of student–scientist interaction in a technology Design Activity, using the expectancy-value model of achievement related choice
International Journal of Technology and Design Education, 2016Co-Authors: Anne-lotte Masson, Tanja Klop, Patricia OsseweijerAbstract:Many education initiatives in science and technology education aim to create enthusiasm among young people to pursue a career in Science, Technology, Engineering, and Mathematics (STEM). Research suggests that personal interaction between secondary school students and scientists could be a success factor, but there is a need for more in-depth research on the actual effects of science education initiatives. This paper describes an in-depth, qualitative assessment of a technology Design Activity, using as a theoretical framework the expectancy-value model of academic choice Eccles and Wigfield (Annu Rev Psychol 53:109–132, 2002 ). A core element in the studied education initiative is the interaction between secondary school students and scientists. Semi-structured interviews were conducted with participating students and analysed qualitatively to disentangle the factors in their motivation to participate in this initiative and their experiences and memories gathered during participation. Last, this paper reflects on the use of the expectancy-value model for in-depth assessments of science education initiatives. Results show that interest-enjoyment values and attainment values are most important in the students’ motivation to participate in the studied Activity. These values are connected to educational principles of authentic practice, and of providing meaningful contexts for scientific concepts. Furthermore, results show that the interaction between students and scientists is not automatically a success factor. Disappointment in this interaction, can cast a shadow on students’ whole experience. This leads us to propose to include an additional factor in the expectancy-value model of achievement related choice: educational environment, including ‘personal interaction’ as an element. Adding this factor would—in our opinion—create an even better framework for in-depth assessment of science education initiatives.
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an analysis of the impact of student scientist interaction in a technology Design Activity using the expectancy value model of achievement related choice
International Journal of Technology and Design Education, 2016Co-Authors: Anne-lotte Masson, Tanja Klop, Patricia OsseweijerAbstract:Many education initiatives in science and technology education aim to create enthusiasm among young people to pursue a career in Science, Technology, Engineering, and Mathematics (STEM). Research suggests that personal interaction between secondary school students and scientists could be a success factor, but there is a need for more in-depth research on the actual effects of science education initiatives. This paper describes an in-depth, qualitative assessment of a technology Design Activity, using as a theoretical framework the expectancy-value model of academic choice Eccles and Wigfield (Annu Rev Psychol 53:109–132, 2002). A core element in the studied education initiative is the interaction between secondary school students and scientists. Semi-structured interviews were conducted with participating students and analysed qualitatively to disentangle the factors in their motivation to participate in this initiative and their experiences and memories gathered during participation. Last, this paper reflects on the use of the expectancy-value model for in-depth assessments of science education initiatives. Results show that interest-enjoyment values and attainment values are most important in the students’ motivation to participate in the studied Activity. These values are connected to educational principles of authentic practice, and of providing meaningful contexts for scientific concepts. Furthermore, results show that the interaction between students and scientists is not automatically a success factor. Disappointment in this interaction, can cast a shadow on students’ whole experience. This leads us to propose to include an additional factor in the expectancy-value model of achievement related choice: educational environment, including ‘personal interaction’ as an element. Adding this factor would—in our opinion—create an even better framework for in-depth assessment of science education initiatives.
Bo T Christensen - One of the best experts on this subject based on the ideXlab platform.
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empirically analysing Design reasoning patterns abductive deductive reasoning patterns dominate Design idea generation
Design Studies, 2019Co-Authors: Claus Lundgaard Cramerpetersen, Bo T Christensen, Saeema AhmedkristensenAbstract:Reasoning is a fundamental process in Design Activity, and it provides a way to understand Design behaviour. Theories and models of Design propose reasoning that follows abductive-deductive patterns. At the micro-level, these patterns are untested. This study analyses verbal reasoning patterns at the micro-level for group idea generation using protocol analyses of concurrent verbalisations from five Design teams with industry participants. The results show that reasoning in Design Activity across 218 ideas follows general patterns of abductive-deductive reasoning. At the individual idea level, the reasoning patterns are disorderly and enter into micro-patterns of inference. The study concludes that understanding reasoning at early-stage idea generation processes is indicative of the mental models and abductive-deductive reasoning that are prevalent in Design Activity.
