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Curriculum-Based Measurement progress data: Effects of graph pattern on ease of interpretation.

Christine A EspinNadira SaabRon Pat-ElPriscilla D M BoenderJoost van der Veen
Published in: Zeitschrift fur Erziehungswissenschaft : ZfE (2018)
Curriculum-Based Measurement (CBM) is a system for monitoring the progress of and evaluating instructional program effectiveness for students with learning difficulties. Although a large amount of research has been conducted on CBM, little has focused on the interpretation and use of the data for instructional decision-making, despite the fact that it is data use that leads to performance gains. In this study, we examine factors affecting the interpretation of CBM data. Specifically, we examine the effect of CBM graph patterns on ease of graph interpretation. Thirty college/university students completed a two-part study in which they viewed various slope-to-goal and slope-to-slope patterns of CBM-graphed data and answered decision-making questions. Response times and accuracy were measured. Results revealed that graph patterns differed in terms of ease of interpretation. Differences depended on the type of question. Implications for interpretation and use of CBM data for decision-making are discussed.
Keyphrases
  • decision making
  • electronic health record
  • big data
  • systematic review
  • randomized controlled trial
  • convolutional neural network
  • artificial intelligence
  • neural network
  • deep learning