Using learning decomposition to analyze instructional effectiveness in the assessment system

  • Feng M
  • Heffernan N
  • Beck J
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A basic question of instruction is how effective it is in promoting
student learning. This paper presents a study determining the relative
efficacy of different instructional content by applying an educational
data mining technique, learning decomposition. We use logistic
regression to determine how much learning caused by different methods of
presenting same skill, relative to each other. We analyze more than
60,000 performance data across 181 items from more than 2,000 students.
Our results show that items are not all as effective oil promoting
student learning. We also did preliminary Study on validating Our
results by comparing them with rankings from human experts. Our study
demonstrates an easier and quicker approach of evaluating the quality of
ITS contents than experimental studies.

Author-supplied keywords

  • Educational data mining
  • Evaluation
  • Item response theory
  • Learning curves
  • Learning decomposition
  • Student modeling

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  • Mingyu Feng

  • Neil Heffernan

  • Joseph E. Beck

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