<?xml version="1.0" encoding="UTF-8" standalone="yes"?><oembed><version><![CDATA[1.0]]></version><provider_name><![CDATA[vyasastrategy]]></provider_name><provider_url><![CDATA[https://vyasastrategy.wordpress.com]]></provider_url><author_name><![CDATA[vvyasa]]></author_name><author_url><![CDATA[https://vyasastrategy.wordpress.com/author/vvyasa/]]></author_url><title><![CDATA[Course #3 :Schema and Child Concept&nbsp;Acquisition:]]></title><type><![CDATA[link]]></type><html><![CDATA[<p>Intuition initially sparse nodes of concepts and as the knowledge gets added nodes gets close and acts as a semi-symbolic concepts.</p>
<p>Course: Schemas in Problem solving</p>
<p>Instructor: Sandra P Marshall</p>
<p><a href="https://vyasastrategy.wordpress.com/2015/12/05/lec1-fundamentals">Lec1: Fundamentals</a></p>
<ul>
<li>Schema roots</li>
<li>The nature of schema</li>
<li>The Schemas of arithmetic story problem</li>
</ul>
<p><a href="https://vyasastrategy.wordpress.com/2015/12/05/lec2-schemas-and-instruction">Lec2: Schemas and Instruction</a></p>
<ul>
<li>Theoretical issues for instruction</li>
<li>The story problem solver</li>
<li>The problem-solving environment</li>
</ul>
<p><a href="https://vyasastrategy.wordpress.com/2015/12/05/lec3-learning-from-instruction">Lec3: Learning from Instruction</a></p>
<ul>
<li>Learning and schema theory</li>
<li>Learning from schema-based instruction</li>
<li>The acquisition of planning knowledge</li>
</ul>
<p><a href="https://vyasastrategy.wordpress.com/2015/12/05/lec4-schemas-and-assessment">Lec4: Schemas and Assessment</a></p>
<ul>
<li>Schema-based assessment</li>
<li>Assessment in SPE and PSE</li>
</ul>
<p><a href="https://vyasastrategy.wordpress.com/2015/12/05/lec5-schemas-and-models">Lec5: Schemas and Models</a></p>
<ul>
<li>Rule-based production systems.</li>
<li>Neural networks</li>
<li>Hybrid models</li>
<li>The performance model</li>
<li>The Learning model</li>
<li>The full schema model</li>
</ul>
<p>Coda</p>
<p>very interesting and very insightful. a good start to know how humans acquire knowledge. Moreover this theory also gives insight to how logic and probability bring two school of thoughts (Classical and Modern AI) together.</p>
<p>&nbsp;</p>
<p>&nbsp;</p>
<p>&nbsp;</p>
]]></html></oembed>