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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