An Integration of Two Competing Models to Explain Practical Intelligence

Persistent Link:
http://hdl.handle.net/10150/194137
Title:
An Integration of Two Competing Models to Explain Practical Intelligence
Author:
Muammar, Omar Mohammed
Issue Date:
2006
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Practical intelligence that accounts for people's performance on real-life problem solving is not related to intelligence in the traditional theories. The primary purpose of this research was to investigate the role of two competing cognitive models in explaining practical intelligence. The author extracted from the literature four cognitive processes and two types of knowledge that significantly accounted for performance on real-life problem solving. The cognitive processes model included (a) metacognition, (b) defining a problem, (c) flexibility of thinking, and (d) selecting a solution strategy. The types of knowledge model included (a) structural knowledge, and (b) tacit knowledge. The secondary purpose of this research was to determine the contribution of some non-cognitive factors to practical intelligence. These factors included (a) self-efficacy, and (b) motivation. These processes and constructs were derived from contemporary theories of intelligence including the Triarchic Theory of Sternberg (1985a), the Bioecological Treatise of Ceci (1996), and theories of expertise.The author developed a Practical Intelligence Instrument (PII) battery based on components of the cognitive processes model, the types of knowledge model, and non-cognitive factors. The PII battery consisted of several subscales to measure components mentioned above. The PII also included items to measure familiarity with problems. The PII was administered to 116 volunteer participants. The validity of the PII subscales was derived from three sources: content, face, and construct validity, including convergent and discriminant. The reliability of the subscales in the PII battery ranged from .63 to .93. The PII also included four scenarios that are real-life problems. Participants were asked to provide solutions for these problems. Three experts from the social science field evaluated participants' strategies based on four criteria. Several statistical procedures were used to analyze the data including a hierarchal multiple regression model, ANOVA, and the Pearson Product-Moment correlation.The results showed that around 54% of the variance in practical intelligence was explained by the cognitive processes model, the types of knowledge model, and self-efficacy and motivation. The cognitive model explained around 42%. The types of knowledge model explained around 15%. The non-cognitive factors explained around 20 % of the variance in practical intelligence.
Type:
text; Electronic Dissertation
Keywords:
Practical; intelligence; problem solving; real-life; everyday
Degree Name:
PhD
Degree Level:
doctoral
Degree Program:
Special Education & Rehabilitation; Graduate College
Degree Grantor:
University of Arizona
Advisor:
Maker, C. June
Committee Chair:
Maker, C. June

Full metadata record

DC FieldValue Language
dc.language.isoENen_US
dc.titleAn Integration of Two Competing Models to Explain Practical Intelligenceen_US
dc.creatorMuammar, Omar Mohammeden_US
dc.contributor.authorMuammar, Omar Mohammeden_US
dc.date.issued2006en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractPractical intelligence that accounts for people's performance on real-life problem solving is not related to intelligence in the traditional theories. The primary purpose of this research was to investigate the role of two competing cognitive models in explaining practical intelligence. The author extracted from the literature four cognitive processes and two types of knowledge that significantly accounted for performance on real-life problem solving. The cognitive processes model included (a) metacognition, (b) defining a problem, (c) flexibility of thinking, and (d) selecting a solution strategy. The types of knowledge model included (a) structural knowledge, and (b) tacit knowledge. The secondary purpose of this research was to determine the contribution of some non-cognitive factors to practical intelligence. These factors included (a) self-efficacy, and (b) motivation. These processes and constructs were derived from contemporary theories of intelligence including the Triarchic Theory of Sternberg (1985a), the Bioecological Treatise of Ceci (1996), and theories of expertise.The author developed a Practical Intelligence Instrument (PII) battery based on components of the cognitive processes model, the types of knowledge model, and non-cognitive factors. The PII battery consisted of several subscales to measure components mentioned above. The PII also included items to measure familiarity with problems. The PII was administered to 116 volunteer participants. The validity of the PII subscales was derived from three sources: content, face, and construct validity, including convergent and discriminant. The reliability of the subscales in the PII battery ranged from .63 to .93. The PII also included four scenarios that are real-life problems. Participants were asked to provide solutions for these problems. Three experts from the social science field evaluated participants' strategies based on four criteria. Several statistical procedures were used to analyze the data including a hierarchal multiple regression model, ANOVA, and the Pearson Product-Moment correlation.The results showed that around 54% of the variance in practical intelligence was explained by the cognitive processes model, the types of knowledge model, and self-efficacy and motivation. The cognitive model explained around 42%. The types of knowledge model explained around 15%. The non-cognitive factors explained around 20 % of the variance in practical intelligence.en_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
dc.subjectPracticalen_US
dc.subjectintelligenceen_US
dc.subjectproblem solvingen_US
dc.subjectreal-lifeen_US
dc.subjecteverydayen_US
thesis.degree.namePhDen_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineSpecial Education & Rehabilitationen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorMaker, C. Juneen_US
dc.contributor.chairMaker, C. Juneen_US
dc.contributor.committeememberChalfant, Jamesen_US
dc.contributor.committeememberSchiever, Shirleyen_US
dc.contributor.committeememberTaylor, Johnen_US
dc.identifier.proquest1828en_US
dc.identifier.oclc659746354en_US
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