TY - JOUR
T1 - Analyzing problem's difficulty based on neural networks and knowledge map
AU - Kuo, Rita
AU - Lien, Wei Peng
AU - Chang, Maiga
AU - Heh, Jia Sheng
N1 - Funding Information:
Supported in part by grants-in-aid 12670472 (to M.O.), 11670490 and 10557055 (to H.M.), and 13670579 and Special Coordination Funds for Promoting Science and Technology (to S.K.) from the Ministry of Education, Culture, Sports, Science and Technology, a grant from the Total Health Promotion Foundation (to M.O.), grants-in-aid from The Tokyo Biochemical Research Foundation (to H.M.), and grants for Multibioprobe Research Program and President's Special Research Grant from RIKEN (to S.K).
PY - 2004/4
Y1 - 2004/4
N2 - This paper proposes a methodology to calculate both the difficulty of the basic problems and the difficulty of solving a problem. The method to calculate the difficulty of problem is according to the process of constructing a problem, including Concept Selection, Unknown Designation, and Proposition Construction. Some necessary measures observed in the problem construction process are also defined in this paper in order to formulate and calculate the difficulties. Beside the difficulty of the basic problem, four difficulty dimensions for problem solvers to realize what kinds of abilities they are lack of to deal with the problem, including Identification, Elaboration, Planning, and Execution, corresponding to the each step of problem solving process are also analyzed and designed by the artificial neural networks in this paper. By these difficulty measures learners can understand what kind of problems they meet and what sort of problem solving strategies they use in solving the problem. To verify our goals, an Item Generating System is constructed for demonstrating and supporting the difficulty calculation in the end of this paper.
AB - This paper proposes a methodology to calculate both the difficulty of the basic problems and the difficulty of solving a problem. The method to calculate the difficulty of problem is according to the process of constructing a problem, including Concept Selection, Unknown Designation, and Proposition Construction. Some necessary measures observed in the problem construction process are also defined in this paper in order to formulate and calculate the difficulties. Beside the difficulty of the basic problem, four difficulty dimensions for problem solvers to realize what kinds of abilities they are lack of to deal with the problem, including Identification, Elaboration, Planning, and Execution, corresponding to the each step of problem solving process are also analyzed and designed by the artificial neural networks in this paper. By these difficulty measures learners can understand what kind of problems they meet and what sort of problem solving strategies they use in solving the problem. To verify our goals, an Item Generating System is constructed for demonstrating and supporting the difficulty calculation in the end of this paper.
KW - Difficulty of problems
KW - Knowledge map
KW - Least-mean square
KW - Neural networks
KW - Problem solving process
UR - http://www.scopus.com/inward/record.url?scp=3042695345&partnerID=8YFLogxK
M3 - Journal Article
AN - SCOPUS:3042695345
SN - 1436-4522
VL - 7
SP - 42
EP - 50
JO - Educational Technology and Society
JF - Educational Technology and Society
IS - 2
ER -