ASIA unversity:Item 310904400/3870
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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/3870


    Title: An Ontology-Based Programming Assessment by Misconception Mining
    Authors: fan yang chi
    Contributors: Department of Information Science and Applications
    Keywords: Programming Learning, Misconception, Programming Concept, Prerequisite Concept, Ontology, Frame, Data Mining
    Date: 2007
    Issue Date: 2009-11-17 11:54:22 (UTC+0)
    Publisher: Asia University
    Abstract: It is an important and challenging issue to overcome the problem within the
    student learning in programming. From the observations, there are many programming
    misconceptions occur when the student writing their programs. Several bugs such as
    missing token or misuse token frequently occur. We want to find out whether the
    student incautious or they have misconception about the programming concepts, or
    whether there are some prerequisite concepts they didn?t learn properly. We, then,
    propose the idea to find out what reason does behind this fact. We propose an
    Ontology-Based Programming Misconception Analyzing Scheme (OBPMAS) which
    has the following three phases to reach our goal: (1) Phase 1: Frame-Based Program
    Concept Hierarchy Construction, (2) Phase 2: Debugging Test Item Generation and (3)
    Phase 3: Misconception Analyzer. After Program Statement Ontology has been
    constructed, we model the concept with each frame above in Frame-Based Program
    Concept Hierarchy Construction phase. We construct the Buggy Pattern Ontology
    (BPO) containing about many error types, where is also use frame to describe in detail
    about BPO. We analyze the answer sheet by using association rule mining to construct
    the concept map. From that answer sheet, we can predict what misconceptions the
    student may have. Then we can obtain the feedback as the strategy for the teacher to
    improve student learning in programming course. Experiments we did involved about
    fifty persons (i.e., the student). The result show us the research we did that help
    improve learning effects and learning strategy.
    Appears in Collections:[Department of Applied Informatics and Multimedia] Theses & dissertations

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