Learning analytics should not promote one size fits all: The effects of instructional conditions in predicting academic success

@inproceedings{Gaevi2016LearningAS,
  title={Learning analytics should not promote one size fits all: The effects of instructional conditions in predicting academic success},
  author={Dragan Ga{\vs}evi{\'c} and Shane Dawson and Tim B. Rogers and Danijela Gasevic},
  year={2016}
}
This study examined the extent to which instructional conditions influence the prediction of academic success in nine undergraduate courses offered in a blended learning model (n = 4134). The study illustrates the differences in predictive power and significant predictors between course‐specific models and generalized predictive models. The results suggest it is imperative for learning analytics research to account for the diverse ways technology is adopted and applied in… CONTINUE READING
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