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Learning analytics enable automated feedback to students through dashboards, reports and alerts. The underlying untested assumption is that providing analytics will be sufficient to improve self-regulated learning. Working within a feedback recipience framework, we begin to test this assumption by examining the impact of learning analytics messages on student affect and academic resilience. Three hundred and twenty undergraduate students completed an online survey and were exposed to three randomly assigned learning analytics alerts (High Distinction, Pass, and Fail grades). Multivariate analyses of variance indicated significant differences between grade levels (large effects), with higher positive affect and lower resilience in response to High Distinction alerts than Pass or Fail alerts. Within each hypothetical grade level, there were no differences in student affect and academic resilience. Based upon …