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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 7 of 7 1 The contribution of visual articulatory gestures and orthography to speech processing: Evidence from novel word learning Pattamadilok, Chotiga; Welby, Pauline; Tyler, Michael In: ISSN: 0278-7393 ; EISSN: 1939-1285 ; Journal of Experimental Psychology: Learning, Memory, and Cognition ; https://hal.archives-ouvertes.fr/hal-03189083 ; Journal of Experimental Psychology: Learning, Memory, and Cognition, American Psychological Association, In press, ⟨10.1037/xlm0001036⟩ (2021) BASE Show details 2 From graphemes to language and to knowledge ; Des graphèmes à la langue et à la connaissance Haralambous, Yannis. - : HAL CCSD, 2020 In: https://hal.archives-ouvertes.fr/tel-02986651 ; Intelligence artificielle [cs.AI]. Université de Bretagne Occidentale, 2020 (2020) BASE Show details 3 Теория и методика вербальной и иконической репрезентации социокультурной реальности в печатных СМИ БАБИКОВА МАРИНА РАШИТОВНА; ЧУДИНОВ АНАТОЛИЙ ПРОКОПЬЕВИЧ. - : Федеральное государственное бюджетное образовательное учреждение высшего профессионального образования «Уральский государственный педагогический университет», 2016 BASE Show details 4 Visualization of Decision Processes Using a Cognitive Architecture Livingston, Mark A; Murugesan, Arthi; Brock, Derek... In: DTIC (2013) BASE Show details 5 Exploring the Complexity of Tree Thinking Expertise in an Undergraduate Systematics Course Halverson, Kristy L.; Pires, J. Chris; Abell, Sandra K. In: Faculty Publications (2011) Abstract: Student understanding of biological representations has not been well studied. Yet, we know that to be efficient problem solvers in evolutionary biology and systematics, college students must develop expertise in thinking with a particular type of representation, phylogenetic trees. The purpose of this study was to understand how undergraduates make sense of phylogenetic representations presented in a plant systematics course designed to promote student tree thinking expertise. The primary data sources were two-tiered pre/posttests and interviews with key informants. Using observations and document analysis as supporting data, we identified multiple misconceptions within students' knowledge of systematics not previously identified in the literature. Relying upon these misconceptions, students developed alternative types of reasoning that interfered with interpreting and using trees. We constructed a classification of student reasoning and identified a suite of varying levels of approaches that went beyond misreading the topology of phylogenetic trees to include the persistent use of nonevolutionary reasoning to address phylogenetic problems. We categorized student reasoning as extraneous, ecological, morphological, branch influenced, tree shape influenced, node influenced, limited phylogenetic, and phylogenetic. By better understanding our students reasoning by qualitative assessments, these findings have implications for curriculum, instruction, and assessment strategies. (C) 2011 Wiley Periodicals, Inc. Sci Ed 95: 794-823, 2011 Keyword: biodiversity; classification; Education; evolution; expertise; knowledge representation; misconceptions; problem solving; Science and Mathematics Education; thinking skills; topology; visual aids URL: http://lynx.lib.usm.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=eue&AN=508462321&site=ehost-live https://aquila.usm.edu/fac_pubs/417 BASE Hide details 6 Computational processes in human vision : an interdisciplinary perspective Pylyshyn, Zenon W.. - Norwood, NJ : Ablex, 1988 MPI für Psycholinguistik Show details 7 Computational Imagery In: http://papers.cnl.salk.edu/PDFs/Computational Neuroscience 2001-3563.pdf BASE Show details

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