{"id":4235,"date":"2018-09-18T17:55:01","date_gmt":"2018-09-18T21:55:01","guid":{"rendered":"https:\/\/www.amyork.ca\/academic\/zz\/?p=4235"},"modified":"2018-09-18T18:12:03","modified_gmt":"2018-09-18T22:12:03","slug":"problem-solving-and-expertise-learning-objectives","status":"publish","type":"post","link":"https:\/\/www.amyork.ca\/academic\/zz\/learning-objectives\/problem-solving-and-expertise-learning-objectives\/","title":{"rendered":"Problem Solving and Expertise Learning Objectives"},"content":{"rendered":"<p>Discuss, with examples, the nature of well-defined knowledge-lean problems and ill-defined, knowledge-rich problems in terms of their relevance to real-world problem-solving<\/p>\n<ul>\n<li>Well-defined problems \u2013 all aspects of the problem clearly stated, including initial conditions<\/li>\n<li>Ill-defined problems \u2013 problems underspecified and not enough information or available resources<\/li>\n<li>Knowledge-rich problems \u2013 need specialist knowledge<\/li>\n<li>Knowledge-lean problems \u2013 information required to solve problem is contained in the problem statement<\/li>\n<li>g. researchers \u2013 well-defined, knowledge-lean problems<\/li>\n<li>Real life problems are usually ill-defined and knowledge-rich problems for which the \u2018correct\u2019 or \u2018best\u2019 solution is unknown<\/li>\n<\/ul>\n<p>Compare and contrast the naturalistic and rational decision-making paradigms and discuss their relationship to notions of expertise. Consider how the dual system model of decision-making might align with the two paradigms<\/p>\n<ul>\n<li>Our notions of expertise are tied to our notions of good decisions and problem solving \uf0b7 Two decision-making paradigms:<\/li>\n<li>Unconscious processing (intuitive, automatic, immediate) \u2013 proposes intuitive answers to judge problems as they arise ~ operates under time pressure and uncertainty<\/li>\n<li>Conscious processing (analytical, controlled, rational) \u2013 monitors the quality of these judgements \u2013 it may endorse, correct, or override ~ requires sufficient information and sufficient time<\/li>\n<\/ul>\n<p>\uf0b7 Naturalistic (descriptive) paradigm (Simon)<\/p>\n<ul>\n<li>Decision making in complex and cognitively challenging environments<\/li>\n<li>Sense making in uncertain situations<\/li>\n<li>Situational awareness (assessment)<\/li>\n<\/ul>\n<p>\uf0b7 Rational (normative) paradigm (Klein)<\/p>\n<ul>\n<li>Not all relevant information is known to us, and cannot compare all possible outcomes to make best choice (optimization)<\/li>\n<li>Boundaries to rationality (constraints) due to:<\/li>\n<\/ul>\n<p>o Environmental constraints o Mental constraints o Temporal constraints<\/p>\n<p>\uf0b7 Rational vs Naturalistic<\/p>\n<ul>\n<li>Rational models of thinking dominant as they are most accessible to non-experts, and have agreed on methods and metrics<\/li>\n<li>Naturalistic models do not lend themselves to laboratory studies<\/li>\n<li>Naturalistic decision making studies use a mixture of methodologies, many of which are qualitative and opportunistic in nature<\/li>\n<li>New opportunities for studying expertise using complex game scenarios with inbuilt metrics<\/li>\n<\/ul>\n<p>Discuss the nature of expert skilled performance in a specific domain. Explain the role of \u201cchunking\u201d, pattern abstraction templates and schemas in domain specific expertise<\/p>\n<h2>Expertise<\/h2>\n<ul>\n<li>Expertise is domain-specific knowledge acquired over many years<\/li>\n<li>Routine expertise \u2013 using acquired knowledge to solve familiar problems efficiently<\/li>\n<li>Adaptive expertise \u2013 using acquired knowledge to solve novel problem or to make decisions under uncertainty or time-pressure<\/li>\n<\/ul>\n<h2>Domain Specific Expertise \u2013 Ericsson\u2019s Expert Performance Model<\/h2>\n<ul>\n<li>Complex decisions are made in risky, uncertain situations under time pressure<\/li>\n<li>Task execution involves cognitive processing and perceptuomotor coordination (vision for perception vs vision for action)<\/li>\n<li>Expertise is domain-specific and often does not transfer to new domains (can have negative transfer) \u2013 experts can have extremely deep, but narroe knowledge<\/li>\n<li>g. Experts in Chess<\/li>\n<li>Chess \u2013 a complex game of strategy that has documented levels of skill culminating in Grand Master (a universally recognized hallmark of expertise)<\/li>\n<li>Chess can then be played by novices who are then able to recognize the skill of Grand Masters<\/li>\n<li>Ericsson \u2013 long term working memory using retrieval cues (pattern fragments) based in short term memory<\/li>\n<\/ul>\n<h2>Chunking<\/h2>\n<ul>\n<li>Remembering a chunk or package of information (a unit of meaning) by a pattern fragment \u2018key\u2019<\/li>\n<li>STM holds 7+\/- 2 chunks of information (Miller, 1956)<\/li>\n<li>Experts appear to be able to expand their working memory by having fast information retrieval and manipulation via chunking<\/li>\n<\/ul>\n<p>Describe the role of deliberate, effortful practice in the acquisition of competence and expertise. Discuss the role that expertise plays in decision-making under uncertainty or time pressure<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Discuss, with examples, the nature of well-defined knowledge-lean problems and ill-defined, knowledge-rich problems in terms of their relevance to real-world problem-solving Well-defined problems \u2013 all aspects of the problem&hellip; <a class=\"continue\" href=\"https:\/\/www.amyork.ca\/academic\/zz\/learning-objectives\/problem-solving-and-expertise-learning-objectives\/\">Continue Reading<span> Problem Solving and Expertise Learning Objectives<\/span><\/a><\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[106],"tags":[],"_links":{"self":[{"href":"https:\/\/www.amyork.ca\/academic\/zz\/wp-json\/wp\/v2\/posts\/4235"}],"collection":[{"href":"https:\/\/www.amyork.ca\/academic\/zz\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.amyork.ca\/academic\/zz\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.amyork.ca\/academic\/zz\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/www.amyork.ca\/academic\/zz\/wp-json\/wp\/v2\/comments?post=4235"}],"version-history":[{"count":0,"href":"https:\/\/www.amyork.ca\/academic\/zz\/wp-json\/wp\/v2\/posts\/4235\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.amyork.ca\/academic\/zz\/wp-json\/wp\/v2\/media?parent=4235"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.amyork.ca\/academic\/zz\/wp-json\/wp\/v2\/categories?post=4235"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.amyork.ca\/academic\/zz\/wp-json\/wp\/v2\/tags?post=4235"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}