Key words for learning science: the structure of students' sign networks in mechanics
<p>Learning science requires conceptual change. Hence, understanding this process is important to develop successful methods of science teaching. Susan Carey’s Theory of the Origin of Concepts (TOOC) is one of the most complete theories of conceptual change. TOOC identifies Quinian bootstra...
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
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2023
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| _version_ | 1811139966031364096 |
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| author | Taylor, RD |
| author2 | Hillier, J |
| author_facet | Hillier, J Taylor, RD |
| author_sort | Taylor, RD |
| collection | OXFORD |
| description | <p>Learning science requires conceptual change. Hence, understanding this process is important to develop successful methods of science teaching. Susan Carey’s Theory of the Origin of Concepts (TOOC) is one of the most complete theories of conceptual change. TOOC identifies Quinian bootstrapping as a mechanism that drives conceptual development, with a network of connections between signs (words) forming a placeholder sign structure, which then guides the development of concepts. The nature of placeholder sign structure within scientific domains of knowledge is not known.</p>
<p>This research has examined sign networks in mechanics formed by 6 A-level Physics students learning mechanics and has contrasted these networks with the networks of 5 A-level Psychology students (all aged 16 to 18). Considered word associations and snowball sampling were used to measure individual directed sign networks. The structure of these networks was characterised using basic network parameters and by fitting the degree distributions with different models (e.g., Poisson distribution or power-law) to determine whether the networks contained highly connected hub-words. The Force Conceptual Inventory (FCI) and interviews were used to assess participants’ conceptual understanding of mechanics. The interview transcripts were analysed using content and lexicogrammatical analysis.</p>
<p>The FCI scores and the interview analysis showed the physicists and psychologists have a different conceptual understanding of mechanics, but that the macrostructure of all the placeholder sign networks is similar. The networks are sparse, have short average path lengths and low average degree, and high clustering. However, the connections (microstructure) between signs are different in the physics and psychology networks. These structural features suggest conceptual development is guided by a small number of connections (sparseness and low average degree) between neighbouring signs (clusters), which are closely connected to other parts of the network (short average path length).</p>
<p>All the sign networks contain hub-words, with, <em>force, energy, time,</em> and <em>particle</em> occurring frequently in all networks, but <em>mass</em> is only found in the physics networks. The presence of hub-words suggests the clusters of signs are connected via these hub-words and that the sign structure ‘grows’, or is organised, around hub-words. Furthermore, the interview analysis of the use of <em>force</em> in explanations and the FCI scores suggest this structural feature is present in the psychology networks before these participants have a full conceptual understanding of mechanics (i.e., force is recognised as a cause of motion, rather than acceleration). This is consistent with TOOC account of Quinian bootstrapping driving conceptual development and has implications for the pedagogical practice in physics and beyond.</p> |
| first_indexed | 2024-09-25T04:14:29Z |
| format | Thesis |
| id | oxford-uuid:d3484a5b-96a9-48b3-9ece-1412ba38eb95 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-09-25T04:14:29Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | oxford-uuid:d3484a5b-96a9-48b3-9ece-1412ba38eb952024-07-12T13:02:25ZKey words for learning science: the structure of students' sign networks in mechanicsThesishttp://purl.org/coar/resource_type/c_db06uuid:d3484a5b-96a9-48b3-9ece-1412ba38eb95LearningConcept mappingConcept learningEnglishHyrax Deposit2023Taylor, RDHillier, JChilds, AErduran, SKoponen, I<p>Learning science requires conceptual change. Hence, understanding this process is important to develop successful methods of science teaching. Susan Carey’s Theory of the Origin of Concepts (TOOC) is one of the most complete theories of conceptual change. TOOC identifies Quinian bootstrapping as a mechanism that drives conceptual development, with a network of connections between signs (words) forming a placeholder sign structure, which then guides the development of concepts. The nature of placeholder sign structure within scientific domains of knowledge is not known.</p> <p>This research has examined sign networks in mechanics formed by 6 A-level Physics students learning mechanics and has contrasted these networks with the networks of 5 A-level Psychology students (all aged 16 to 18). Considered word associations and snowball sampling were used to measure individual directed sign networks. The structure of these networks was characterised using basic network parameters and by fitting the degree distributions with different models (e.g., Poisson distribution or power-law) to determine whether the networks contained highly connected hub-words. The Force Conceptual Inventory (FCI) and interviews were used to assess participants’ conceptual understanding of mechanics. The interview transcripts were analysed using content and lexicogrammatical analysis.</p> <p>The FCI scores and the interview analysis showed the physicists and psychologists have a different conceptual understanding of mechanics, but that the macrostructure of all the placeholder sign networks is similar. The networks are sparse, have short average path lengths and low average degree, and high clustering. However, the connections (microstructure) between signs are different in the physics and psychology networks. These structural features suggest conceptual development is guided by a small number of connections (sparseness and low average degree) between neighbouring signs (clusters), which are closely connected to other parts of the network (short average path length).</p> <p>All the sign networks contain hub-words, with, <em>force, energy, time,</em> and <em>particle</em> occurring frequently in all networks, but <em>mass</em> is only found in the physics networks. The presence of hub-words suggests the clusters of signs are connected via these hub-words and that the sign structure ‘grows’, or is organised, around hub-words. Furthermore, the interview analysis of the use of <em>force</em> in explanations and the FCI scores suggest this structural feature is present in the psychology networks before these participants have a full conceptual understanding of mechanics (i.e., force is recognised as a cause of motion, rather than acceleration). This is consistent with TOOC account of Quinian bootstrapping driving conceptual development and has implications for the pedagogical practice in physics and beyond.</p> |
| spellingShingle | Learning Concept mapping Concept learning Taylor, RD Key words for learning science: the structure of students' sign networks in mechanics |
| title | Key words for learning science: the structure of students' sign networks in mechanics |
| title_full | Key words for learning science: the structure of students' sign networks in mechanics |
| title_fullStr | Key words for learning science: the structure of students' sign networks in mechanics |
| title_full_unstemmed | Key words for learning science: the structure of students' sign networks in mechanics |
| title_short | Key words for learning science: the structure of students' sign networks in mechanics |
| title_sort | key words for learning science the structure of students sign networks in mechanics |
| topic | Learning Concept mapping Concept learning |
| work_keys_str_mv | AT taylorrd keywordsforlearningsciencethestructureofstudentssignnetworksinmechanics |