| Project/Area Number |
18500716
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Educational technology
|
|---|
| Research Institution | Fukui Prefectural University |
|---|
Principal Investigator |
TANAKA Takeyuki Fukui Prefectural University, Center for Arts and Sciences, Associate Professor (10244526)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
YAMAKAWA Osamu Fukui Prefectural University, Professor (90230325)
KIKUSAWA Masahiro Fukui Prefectural University, Professor (50144340)
|
|---|
| Project Period (FY) |
2006 – 2007
|
| Project Status |
Completed (Fiscal Year 2007)
|
| Budget Amount *help |
¥3,950,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2007: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2006: ¥2,000,000 (Direct Cost: ¥2,000,000)
|
|---|
| Keywords | item response theory / IRT / instructional design / computer literacy / remedial study / placement test / achivement test |
|---|
| Research Abstract |
Computer literacy is one of the most important coursework in the current basic education in Japanese university. However, the prior knowledge of first-year students is very different among the students. In order to teach effectively, it is necessary for the course to provide the best option for each student. The ability of first-year students in computer usage have been measured for four years using the item response theory, so far. Our aim of this study is developing the selection method for learning modules corresponding to IRT score. The instructional design theory was applied to the development of the learning modules. If the subdivided learning modules by the instructional design are connected with the IRT scores of the students, it is possible for the students to choose the best learning module according to their prior knowledge. This idea is an example of so-called adaptive learning model.
For this purpose, firstly, a prior knowledge survey for first-year students about the learning module was executed. Secondary, the IRT score of students and the probability of prior knowledge of the learning modules are brought into connection by the 2-parameters logistic model. This connection method introduces an indicator to select the learning modules corresponding to the IRT score. We call the indicator "knowledge degree". The indicator can work as a criterion to provide the learning modules to the students who has a specific IRT score.
For adaptive learning, we can check the students' duty by a paper test or a technical test in every learning module. According to the instructional design theory, the students should take every test in spite of too difficult or too easy module. Meanwhile, the merit of our method is less effort for teachers and students. We can judge the learning modules to be skipped or not by the light test and survey only.
|
