Documents disponibles écrits par cet auteur

Introductory circuit analysis learning from abstract and contextualized circuit representations / Amy M. Johnson in IEEE transactions on education, Vol. 57 N° 3 (Août 2014) 

Public ISBD [article]  in IEEE transactions on education > Vol. 57 N° 3 (Août 2014) . - pp. 160 - 168 Titre : Introductory circuit analysis learning from abstract and contextualized circuit representations : effects of diagram labels Type de document : texte imprimé Auteurs : Amy M. Johnson, Auteur ; Kirsten R. Butcher, Auteur ; Gamze Ozogul, Auteur Année de publication : 2015 Article en page(s) : pp. 160 - 168 Note générale : Education Langues : Anglais (eng) Mots-clés : Circuit  analysis  instruction  Circuit  diagram  Diagram  label  Electrical  circuit  analysis  Multiple  external  representations  Novice  learner Résumé : Novice learners are typically unfamiliar with abstract engineering symbols. They are also often unaccustomed to instructional materials consisting of a combination of text, diagrams, and equations. This raises the question of whether instruction on elementary electrical circuit analysis for novice learners should employ contextualized representations of the circuits with familiar components, such as batteries, or employ abstract representations with the abstract engineering terms and symbols. A further question is if text labels in the circuit diagrams would aid these learners. This study examined these research questions with a “2 × 3” experimental design, in which the two forms of representation (abstract or contextualized) were considered under three types of diagram labeling (no labels, static labels, or interactive labels). The design was implemented in an instructional module on elementary circuit analysis for novice learners. Results indicated that abstract representations led to higher near- and far-transfer post-test scores, and that interactive (student-generated) labeling resulted in higher near-transfer scores than either the no-labels or static-labels conditions. These findings suggest that abstract representations promote the development of deep, transferrable knowledge and that generative methods of integration, such as interactive diagram labeling, can facilitate learning with multiple external representations. ISSN : 0018-9359 En ligne : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6637101&sortType%3Das [...] [article] Introductory circuit analysis learning from abstract and contextualized circuit representations : effects of diagram labels [texte imprimé] / Amy M. Johnson, Auteur ; Kirsten R. Butcher, Auteur ; Gamze Ozogul, Auteur . - 2015 . - pp. 160 - 168. Education Langues : Anglais (eng) in IEEE transactions on education > Vol. 57 N° 3 (Août 2014) . - pp. 160 - 168 Mots-clés : Circuit  analysis  instruction  Circuit  diagram  Diagram  label  Electrical  circuit  analysis  Multiple  external  representations  Novice  learner Résumé : Novice learners are typically unfamiliar with abstract engineering symbols. They are also often unaccustomed to instructional materials consisting of a combination of text, diagrams, and equations. This raises the question of whether instruction on elementary electrical circuit analysis for novice learners should employ contextualized representations of the circuits with familiar components, such as batteries, or employ abstract representations with the abstract engineering terms and symbols. A further question is if text labels in the circuit diagrams would aid these learners. This study examined these research questions with a “2 × 3” experimental design, in which the two forms of representation (abstract or contextualized) were considered under three types of diagram labeling (no labels, static labels, or interactive labels). The design was implemented in an instructional module on elementary circuit analysis for novice learners. Results indicated that abstract representations led to higher near- and far-transfer post-test scores, and that interactive (student-generated) labeling resulted in higher near-transfer scores than either the no-labels or static-labels conditions. These findings suggest that abstract representations promote the development of deep, transferrable knowledge and that generative methods of integration, such as interactive diagram labeling, can facilitate learning with multiple external representations. ISSN : 0018-9359 En ligne : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6637101&sortType%3Das [...]