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Analyzing and Exploring Affective and Cognitive Learning Outcomes in Computer Games through Data Science

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Title: Analyzing and Exploring Affective and Cognitive Learning Outcomes in Computer Games through Data Science
Language: English
Authors: Ayman Alzaid
Source: ProQuest LLC. 2023Ph.D. Dissertation, New Mexico State University.
Availability: ProQuest LLC. 789 East Eisenhower Parkway, P.O. Box 1346, Ann Arbor, MI 48106. Tel: 800-521-0600; Web site: http://www.proquest.com/en-US/products/dissertations/individuals.shtml
Peer Reviewed: N
Page Count: 268
Publication Date: 2023
Document Type: Dissertations/Theses - Doctoral Dissertations
Tests/Questionnaires
Education Level: Elementary Education
Grade 4
Intermediate Grades
Grade 5
Middle Schools
Descriptors: Computer Games, Outcomes of Education, Game Based Learning, Mathematics Instruction, Elementary School Students, Student Attitudes, Grade 4, Grade 5, Time on Task, Interaction, Learner Engagement, Student Motivation, Design, Educational Games, Mathematics Education
ISBN: 979-83-8168-737-8
Abstract: As computer games become integral to students' learning experiences, this dissertation investigates the impact of educational game-based learning on mathematical outcomes and attitudes among elementary school students. Employing data science techniques, including statistical approaches and quantitative analysis through data mining of gameplay data alongside student surveys and assessments, the research delves into diverse gameplay patterns among fourth and fifth-grade students. Utilizing cluster analysis, three distinct student clusters--Agrinautica Masters, Math Pioneers, and Learning Explorers--are revealed, each exhibiting varying levels of mathematical complexity and game feature usage. The study unveils relationships between gameplay duration, student interactions, and the impact of autonomous learning and engagement. Survey results highlight positive student perceptions of Agrinautica, with varying attitudes observed among the clusters. The discussion further explores how the game's design, incorporating elements to enhance motivation and engagement, influences these perceptions. Drawing on constructivist learning theory and educational game research, the findings offer insights into improving educational practices, game design, and measurement. Implications include the development of comprehensive data collection frameworks and teacher training for effective game integration, with recommendations for future research to advance educational gameplay data analysis. Ultimately, this dissertation contributes valuable insights, laying a foundation for enhancing learning outcomes and reducing math-related anxiety through educational games in mathematics education. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]
Abstractor: As Provided
Entry Date: 2024
Access URL: https://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:30695458
Accession Number: ED645639
Database: ERIC
FullText Text:
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PubType: Dissertation/ Thesis
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  Data: Analyzing and Exploring Affective and Cognitive Learning Outcomes in Computer Games through Data Science
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  Data: As computer games become integral to students' learning experiences, this dissertation investigates the impact of educational game-based learning on mathematical outcomes and attitudes among elementary school students. Employing data science techniques, including statistical approaches and quantitative analysis through data mining of gameplay data alongside student surveys and assessments, the research delves into diverse gameplay patterns among fourth and fifth-grade students. Utilizing cluster analysis, three distinct student clusters--Agrinautica Masters, Math Pioneers, and Learning Explorers--are revealed, each exhibiting varying levels of mathematical complexity and game feature usage. The study unveils relationships between gameplay duration, student interactions, and the impact of autonomous learning and engagement. Survey results highlight positive student perceptions of Agrinautica, with varying attitudes observed among the clusters. The discussion further explores how the game's design, incorporating elements to enhance motivation and engagement, influences these perceptions. Drawing on constructivist learning theory and educational game research, the findings offer insights into improving educational practices, game design, and measurement. Implications include the development of comprehensive data collection frameworks and teacher training for effective game integration, with recommendations for future research to advance educational gameplay data analysis. Ultimately, this dissertation contributes valuable insights, laying a foundation for enhancing learning outcomes and reducing math-related anxiety through educational games in mathematics education. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]
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    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 268
    Subjects:
      – SubjectFull: Computer Games
        Type: general
      – SubjectFull: Outcomes of Education
        Type: general
      – SubjectFull: Game Based Learning
        Type: general
      – SubjectFull: Mathematics Instruction
        Type: general
      – SubjectFull: Elementary School Students
        Type: general
      – SubjectFull: Student Attitudes
        Type: general
      – SubjectFull: Grade 4
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      – SubjectFull: Grade 5
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      – SubjectFull: Time on Task
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      – SubjectFull: Interaction
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      – SubjectFull: Learner Engagement
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      – SubjectFull: Student Motivation
        Type: general
      – SubjectFull: Design
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      – SubjectFull: Educational Games
        Type: general
      – SubjectFull: Mathematics Education
        Type: general
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      – TitleFull: Analyzing and Exploring Affective and Cognitive Learning Outcomes in Computer Games through Data Science
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