Skip to main content

Table 5 R-squares and RMSEs between final exam scores and predictions across sets of selected feature variables

From: The possibility of predicting learning performance using features of note taking activities and instructions in a blended learning environment

 

R-squares

RMSE

Feature set

Without Inst.

With Inst.

Without Inst.

With Inst.

NT-f + 13 variablesa

0.06

0.07

6.6

4.4

NT-f + 2 variablesb

0.17

0.64

5.9

2.8

NT-f + 2 variablesc

0.18

0.72

5.9

2.5

NT-f (the first half means)

0.04

0.36

6.7

3.6

NT-f (the second half means)

0.02

0.02

6.9

4.9

3 variablesd

0.04

0.08

6.6

5.1

  1. NT-f: Means of features of NT(WD, CV, ID and AD)
  2. aFour features of overall means in NT-f and other 13 features of characteristics
  3. bSelected features of NT-f (Mean WD and AD in the first half sessions, and Mean ID in the second half sessions)
  4. cFour features of NT-f in the first half sessions, NT-F3, and Mean ID in the second half sessions
  5. dIPIP2, LE-1, and Mean AD in the first sessions