Knowledge-rich teaching: A model of curriculum design coherence

被引:23
|
作者
Rata, Elizabeth [1 ]
机构
[1] Univ Auckland, Auckland, New Zealand
关键词
curriculum; teachers; academic knowledge; concepts; curriculum design; academic identity; EDUCATION;
D O I
10.1002/berj.3520
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
A theoretical model called 'Curriculum Design Coherence' (CDC) is described and justified. The model's purpose is to assist teachers in the compulsory and higher education sectors to design courses that can accommodate the complex and interdependent relationship between concepts and content and between knowledge and skills. Its intended usefulness as a curriculum design tool may also contribute to teachers' pedagogical decision-making. The model was initially developed in a New Zealand university Engineering study and is now being trialled in a study in the compulsory schooling sector with the 'Knowledge-Rich School Project'. The CDC model integrates concepts, content and competencies in a coherent way, thereby avoiding several tendencies which have affected curriculum studies in recent decades. These are: a 'skills' versus 'concepts' bifurcation; an over-emphasis on fragmented content without conceptual integration; and a similar over-emphasis on pedagogy (the 'how') at the expense of what is taught. The first sections of the article discuss the theories used to justify the model's connections between the elements of concepts, content and competencies. The theories concern (1) knowledge types (disciplinary and socio-cultural) and (2) knowledge forms (propositional/conceptual and procedural/competencies). The justification is followed by a description of the CDC model itself.
引用
收藏
页码:681 / 697
页数:17
相关论文
共 50 条
  • [1] Context and Implications Document for: The curriculum design coherence model in the knowledge-rich school project
    Rata, Elizabeth
    [J]. REVIEW OF EDUCATION, 2021, 9 (02): : 496 - 499
  • [2] Knowledge-rich catalog services for engineering design
    Kim, Jihie
    Will, Peter
    Ling, S. Ringo
    Neches, Bob
    [J]. Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM, 2003, 17 (4-5): : 349 - 366
  • [3] Powerful knowledge, educational potential and knowledge-rich curriculum: pushing the boundaries
    Deng, Zongyi
    [J]. JOURNAL OF CURRICULUM STUDIES, 2022, 54 (05) : 599 - 617
  • [4] Knowledge-rich catalog services for engineering design
    Kim, J
    Will, P
    Ling, SR
    Neches, B
    [J]. AI EDAM-ARTIFICIAL INTELLIGENCE FOR ENGINEERING DESIGN ANALYSIS AND MANUFACTURING, 2003, 17 (4-5): : 349 - 366
  • [5] Knowledge-rich contexts discovery
    Barrière, C
    [J]. ADVANCES IN ARTIFICIAL INTELLIGENCE, 2004, 3060 : 187 - 201
  • [6] Supporting educational software design with knowledge-rich tools
    Bell, B
    [J]. INTERNATIONAL CONFERENCE ON THE LEARNING SCIENCES, 1996, 1996, : 339 - 344
  • [7] Designing knowledge-rich curricula
    Hezemans, Marijke
    Ritzen, Magda
    [J]. LEARNING TO LIVE IN THE KNOWLEDGE SOCIETY, 2008, : 295 - +
  • [8] Knowledge-rich optimisation of prefabricated facades to support conceptual design
    Montali, Jacopo
    Sauchelli, Michele
    Jin, Qian
    Overend, Mauro
    [J]. AUTOMATION IN CONSTRUCTION, 2019, 97 : 192 - 204
  • [9] Active catalog: A knowledge-rich design library facilitating information consumption
    Luo, P
    Will, P
    [J]. KNOWLEDGE INTENSIVE CAD, VOL 2, 1997, : 157 - 172
  • [10] DESIGN OF KNOWLEDGE-RICH HIERARCHICAL CONTROLLERS FOR LARGE FUNCTIONAL-SYSTEMS
    ACAR, L
    OZGUNER, U
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1990, 20 (04): : 791 - 803