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Activity Number:
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283
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Type:
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Contributed
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Date/Time:
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Tuesday, August 4, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistical Education
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| Abstract - #304139 |
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Title:
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Analogical Encoding of Statistics Problems: Role of Self-Explanation and Feedback
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Author(s):
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Simin Hall*+ and Eric Vance
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Companies:
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Virginia Polytechnic Institute and State University and Virginia Polytechnic Institute and State University
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Address:
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623 McBryde Hall (0218), Blacksburg, VA, 24061,
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Keywords:
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Statistics problem solving ; Analogical Encoding ; Feedback ; On-line technology ; Self-explanation ; Pattern recognition
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Abstract:
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Novice problem solvers often fail to recognize structural similarities between a problem they know and a new problem because they are more concerned with the surface features (story line) of the problem than with the structural features of the problem which involve the shared relations between the objects in the problem. We used an online technology to investigate whether students' self-explanations and reception of feedback influenced recognition of similarities between surface features and structural features of statistical problems. Of the students in the Feedback group, 59% scored at least D or better compared to 37% in the no-feedback group (chi-squared =6.53, df=1, p < .05). On average students in our study gave feedback 442 times more often than students usually do in classrooms. A content analysis of the students' feedback and self-explanation revealed students' misconceptions.
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