IEICE TRANSACTIONS on Information
Learners' Self Checking and Its Effectiveness in Conceptual Data Modeling Exercises
Summary :
Conceptual data modeling is an important activity in database design. However, it is difficult for novice learners to master its skills. In the conceptual data modeling, learners are required to detect and correct errors of their artifacts by themselves because modeling tools do not assist these activities. We call such activities self checking, which is also an important process. However, the previous research did not focus on it and/or the data collection of self checks. The data collection of self checks is difficult because self checking is an internal activity and self checks are not usually expressed. Therefore, we developed a method to help learners express their self checks by reflecting on their artifact making processes. In addition, we developed a system, KIfU3, which implements this method. We conducted an evaluation experiment and showed the effectiveness of the method. From the experimental results, we found out that (1) the novice learners conduct self checks during their conceptual data modeling tasks; (2) it is difficult for them to detect errors in their artifacts; (3) they cannot necessarily correct the errors even if they could identify them; and (4) there is no relationship between the numbers of self checks by the learners and the quality of their artifacts.
- Publication
- IEICE TRANSACTIONS on Information Vol.E101-D No.7 pp.1801-1810
- Publication Date
- 2018/07/01
- Publicized
- 2018/04/20
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2017KBP0001
- Type of Manuscript
- Special Section PAPER (Special Section on Knowledge-Based Software Engineering)
- Category
Authors
Takafumi TANAKA
Tokyo University of Agriculture and Technology
Hiroaki HASHIURA
Nippon Institute of Technology
Atsuo HAZEYAMA
Tokyo Gakugei University
Seiichi KOMIYA
National Institute of Informatics
Yuki HIRAI
Shinshu University
Keiichi KANEKO
Tokyo University of Agriculture and Technology
Keyword
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Takafumi TANAKA, Hiroaki HASHIURA, Atsuo HAZEYAMA, Seiichi KOMIYA, Yuki HIRAI, Keiichi KANEKO, "Learners' Self Checking and Its Effectiveness in Conceptual Data Modeling Exercises" in IEICE TRANSACTIONS on Information,
vol. E101-D, no. 7, pp. 1801-1810, July 2018, doi: 10.1587/transinf.2017KBP0001.
Abstract: Conceptual data modeling is an important activity in database design. However, it is difficult for novice learners to master its skills. In the conceptual data modeling, learners are required to detect and correct errors of their artifacts by themselves because modeling tools do not assist these activities. We call such activities self checking, which is also an important process. However, the previous research did not focus on it and/or the data collection of self checks. The data collection of self checks is difficult because self checking is an internal activity and self checks are not usually expressed. Therefore, we developed a method to help learners express their self checks by reflecting on their artifact making processes. In addition, we developed a system, KIfU3, which implements this method. We conducted an evaluation experiment and showed the effectiveness of the method. From the experimental results, we found out that (1) the novice learners conduct self checks during their conceptual data modeling tasks; (2) it is difficult for them to detect errors in their artifacts; (3) they cannot necessarily correct the errors even if they could identify them; and (4) there is no relationship between the numbers of self checks by the learners and the quality of their artifacts.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2017KBP0001/_p
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@ARTICLE{e101-d_7_1801,
author={Takafumi TANAKA, Hiroaki HASHIURA, Atsuo HAZEYAMA, Seiichi KOMIYA, Yuki HIRAI, Keiichi KANEKO, },
journal={IEICE TRANSACTIONS on Information},
title={Learners' Self Checking and Its Effectiveness in Conceptual Data Modeling Exercises},
year={2018},
volume={E101-D},
number={7},
pages={1801-1810},
abstract={Conceptual data modeling is an important activity in database design. However, it is difficult for novice learners to master its skills. In the conceptual data modeling, learners are required to detect and correct errors of their artifacts by themselves because modeling tools do not assist these activities. We call such activities self checking, which is also an important process. However, the previous research did not focus on it and/or the data collection of self checks. The data collection of self checks is difficult because self checking is an internal activity and self checks are not usually expressed. Therefore, we developed a method to help learners express their self checks by reflecting on their artifact making processes. In addition, we developed a system, KIfU3, which implements this method. We conducted an evaluation experiment and showed the effectiveness of the method. From the experimental results, we found out that (1) the novice learners conduct self checks during their conceptual data modeling tasks; (2) it is difficult for them to detect errors in their artifacts; (3) they cannot necessarily correct the errors even if they could identify them; and (4) there is no relationship between the numbers of self checks by the learners and the quality of their artifacts.},
keywords={},
doi={10.1587/transinf.2017KBP0001},
ISSN={1745-1361},
month={July},}
Copy
TY - JOUR
TI - Learners' Self Checking and Its Effectiveness in Conceptual Data Modeling Exercises
T2 - IEICE TRANSACTIONS on Information
SP - 1801
EP - 1810
AU - Takafumi TANAKA
AU - Hiroaki HASHIURA
AU - Atsuo HAZEYAMA
AU - Seiichi KOMIYA
AU - Yuki HIRAI
AU - Keiichi KANEKO
PY - 2018
DO - 10.1587/transinf.2017KBP0001
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E101-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2018
AB - Conceptual data modeling is an important activity in database design. However, it is difficult for novice learners to master its skills. In the conceptual data modeling, learners are required to detect and correct errors of their artifacts by themselves because modeling tools do not assist these activities. We call such activities self checking, which is also an important process. However, the previous research did not focus on it and/or the data collection of self checks. The data collection of self checks is difficult because self checking is an internal activity and self checks are not usually expressed. Therefore, we developed a method to help learners express their self checks by reflecting on their artifact making processes. In addition, we developed a system, KIfU3, which implements this method. We conducted an evaluation experiment and showed the effectiveness of the method. From the experimental results, we found out that (1) the novice learners conduct self checks during their conceptual data modeling tasks; (2) it is difficult for them to detect errors in their artifacts; (3) they cannot necessarily correct the errors even if they could identify them; and (4) there is no relationship between the numbers of self checks by the learners and the quality of their artifacts.
ER -
English
