• Title/Summary/Keyword: Learning Conation

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The Study on the Effect of Learning Motivation and Conation on the Consultant' Entrepreneurship and Competencies - Focused on the Mediating Effect of Entrepreneurship - (학습동기 및 학습의지가 컨설턴트의 기업가 정신과 역량에 미치는 영향에 관한 연구 -기업가정신의 매개효과를 중심으로-)

  • Lee, In-Su;You, Yen-Yoo
    • Journal of Digital Convergence
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    • v.10 no.5
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    • pp.89-103
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    • 2012
  • This paper analyzed the effect of learning motivation and conation(endurance, effort) on the consultant' entrepreneurship(innovativeness, proactiveness, risk- taking) and competencies(ability, knowledge, attitude), and the mediating effect of the entrepreneurship on the consultant's competencies. The result shows that the learning motivation and conation have a positive impact on the partial factors of the consultant's entrepreneurship(innovativeness, proactiveness) and competencies(ability, knowledge), but not impact on the risk- taking and the attitude. Innovativeness and proactiveness have an positive impact on the consultant's competencies, but not the risk-taking. Innovation and proactiveness fully mediated the effect of learning motivation on the ability, and partially mediated on the knowledge. The effect of learning conation on the ability and knowledge was partially mediated by the innovation, not by the proactiveness. This study shows that the management of the learning motivation and conation, the education of entrepreneurship(innovativeness, proactiveness) are very important for the cultivating the consultant' competencies.

Values in Mathematics Education: Its Conative Nature, and How It Can Be Developed

  • Seah, Wee Tiong
    • Research in Mathematical Education
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    • v.22 no.2
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    • pp.99-121
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    • 2019
  • This article looks back and also looks forward at the values aspect of school mathematics teaching and learning. Looking back, it draws on existing academic knowledge to explain why the values construct has been regarded in recent writings as a conative variable, that is, associated with willingness and motivation. The discussion highlights the tripartite model of the human mind which was first conceptualised in the eighteenth century, emphasising the intertwined and mutually enabling processes of cognition, affect, and conation. The article also discusses what we already know about the nature of values, which suggests that values are both consistent and malleable. The trend in mathematics educational research into values over the last three decades or so is outlined. These allow for an updated definition of values in mathematics education to be offered in this article. Considering the categories of values that might be found in mathematics classrooms, an argument is also made for more attention to be paid to general educational values. After all, the potential of the values construct in mathematics education research extends beyond student understanding of and performance in mathematics, to realising an ethical mathematics education which is important for thriveability in the Fourth Industrial Revolution. Looking ahead, then, this article outlines a 4-step values development approach for implementation in the classroom, involving Justifying, Essaying, Declaring, and Identifying. With an acronym of JEDI, this novel approach has been informed by the theories of 'saying is believing', self-persuasion, insufficient justification, and abstract construals.

A Causal Model Analysis of Non-Cognitive Characteristics of Mathematics Learning (수학학습 정의적 영역에 대한 인과 모형 분석)

  • Lee, Hwan Chul;Kim, Hyung Won;Baeck, SeungGeun;Ko, Ho Kyoung;Yi, Hyun Sook
    • Communications of Mathematical Education
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    • v.31 no.2
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    • pp.187-201
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    • 2017
  • The study in this paper, which is part of a bigger study investigating non-cognitive characteristics of Korean students at the 4-12 grade levels, aims to identify the influential characteristics that explain students' decision to give up on mathematics learning. We consider seven non-cognitive student characteristics: value, interest, attitudes, external motivation, internal motivation, learning conation and efficacy. Data were collected from 21,485 Korean students, and were analyzed with a logistic regression method using SPSS. The findings show that efficacy was the most significant indicator of students' decision to give up on mathematics learning in all three grade level bands: elementary (4th-6th), middle (7th-9th) and high (10th-12th). In particular, the causal model analysis shows that students who highly value mathematics tend to have stronger internal and external motivation, which bring about stronger interest and learning conation, which in turn lead to positive attitudes and strong efficacy regarding the learning of mathematics. It was further found that while external motivation was a significant indicator of upper grade level students' decision to give up on mathematics learning, it was only a moderate indicator for lower grade level students. The findings of this study provide useful information about which non-cognitive areas need to be focused on, in what grade levels, to help students stay on track and not fall behind in learning mathematics.

The Development and Validation of the Survey of Students' Affective Characteristics in the Non-Cognitive Domain of Mathematics Learning (수학학습 정의적 영역 검사 도구 개발 연구)

  • Lee, Hwan Chul;Kim, Hyung Won;Ee, Ji-hye;Yi, Hyun Sook;Ko, Ho Kyoung
    • School Mathematics
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    • v.19 no.2
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    • pp.267-287
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    • 2017
  • Fostering students' positive affect related to mathematics such as attitudes toward mathematics and dispositions toward learning mathematical concepts is one of the major goals of school mathematics programs. In this study, we collected data from students at the 4-1 grade levels to develop an instrument that measures students' affect regarding mathematics learning. To develop the instrument, we first conducted focus group interviews, which we recorded, transcribed, and analyzed. We sorted the results according to seven components of the non-cognitive domain of mathematics learning, which drew from taxonomical constructs of previous research. We then conducted a pilot study in which we administered the instrument as a pretest and a posttest. We chose the final items based on confirmatory factor analysis and a reliability test of the pre and posttest scores. The final instrument contains 24 items, which are classified according to the seven components: interest, attitudes, value, external motivation, internal motivation, learning conation, and efficacy. We anticipate this instrument will be useful for studies that need to measure students' non-cognitive characteristics in relation to learning mathematics.