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Using Tutors to Improve Educational Games: A Cognitive Game for Policy Argument

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Title: Using Tutors to Improve Educational Games: A Cognitive Game for Policy Argument
Language: English
Authors: Easterday, Matthew W., Aleven, Vincent, Scheines, Richard, Carver, Sharon M.
Source: Journal of the Learning Sciences. 2017 26(2):226-276.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 51
Publication Date: 2017
Sponsoring Agency: Institute of Education Sciences (ED)
Contract Number: R305B040063
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Educational Games, Intelligent Tutoring Systems, Policy, Persuasive Discourse, College Students, Randomized Controlled Trials, Problem Solving, Student Interests, Self Efficacy, Pretests Posttests, Performance, Policy Analysis, Path Analysis, Feedback (Response), Error Correction, Likert Scales
DOI: 10.1080/10508406.2016.1269287
ISSN: 1050-8406
Abstract: How might we balance assistance and penalties to intelligent tutors and educational games that increase learning and interest? We created two versions of an educational game for learning policy argumentation called Policy World. The game (only) version provided minimal feedback and penalized students for errors whereas the game+tutor version provided additional step-level teaching feedback and immediate error correction. A total of 105 university students played either the game or game+tutor version of Policy World in a randomized, controlled, two-group, between-subjects experiment, during which we measured students' problem-solving abilities, interest in the game, self-reported competence, and pre- and posttest performance. The game+tutor version increased learning of policy analysis skills and self-reported competence. A path analysis supported the claim that greater assistance helped students to learn analysis better, which increased their feelings of competence, which increased their interest in the game. Log data of student behavior showed that debate performance improved only for students who had sufficiently mastered analysis. This study shows that we can design interesting and effective games to teach policy argumentation and how increasing tutoring and reducing penalties in educational games can increase learning without sacrificing interest.
Abstractor: As Provided
IES Funded: Yes
Entry Date: 2017
Accession Number: EJ1136206
Database: ERIC
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  Data: Using Tutors to Improve Educational Games: A Cognitive Game for Policy Argument
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  Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
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  Data: 10.1080/10508406.2016.1269287
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  Data: 1050-8406
– Name: Abstract
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  Data: How might we balance assistance and penalties to intelligent tutors and educational games that increase learning and interest? We created two versions of an educational game for learning policy argumentation called Policy World. The game (only) version provided minimal feedback and penalized students for errors whereas the game+tutor version provided additional step-level teaching feedback and immediate error correction. A total of 105 university students played either the game or game+tutor version of Policy World in a randomized, controlled, two-group, between-subjects experiment, during which we measured students' problem-solving abilities, interest in the game, self-reported competence, and pre- and posttest performance. The game+tutor version increased learning of policy analysis skills and self-reported competence. A path analysis supported the claim that greater assistance helped students to learn analysis better, which increased their feelings of competence, which increased their interest in the game. Log data of student behavior showed that debate performance improved only for students who had sufficiently mastered analysis. This study shows that we can design interesting and effective games to teach policy argumentation and how increasing tutoring and reducing penalties in educational games can increase learning without sacrificing interest.
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  Data: 2017
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      – Type: doi
        Value: 10.1080/10508406.2016.1269287
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 51
        StartPage: 226
    Subjects:
      – SubjectFull: Educational Games
        Type: general
      – SubjectFull: Intelligent Tutoring Systems
        Type: general
      – SubjectFull: Policy
        Type: general
      – SubjectFull: Persuasive Discourse
        Type: general
      – SubjectFull: College Students
        Type: general
      – SubjectFull: Randomized Controlled Trials
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      – SubjectFull: Problem Solving
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      – SubjectFull: Student Interests
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      – SubjectFull: Self Efficacy
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      – SubjectFull: Pretests Posttests
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      – SubjectFull: Performance
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      – SubjectFull: Policy Analysis
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      – SubjectFull: Path Analysis
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      – SubjectFull: Feedback (Response)
        Type: general
      – SubjectFull: Error Correction
        Type: general
      – SubjectFull: Likert Scales
        Type: general
    Titles:
      – TitleFull: Using Tutors to Improve Educational Games: A Cognitive Game for Policy Argument
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