How Prediction Visualization Improves Bar Charts Interpretation and Data Recall?

Information visualization is a popular tool to help users learn about a dataset. In particular, users' interactions with their internal representations - prior beliefs and knowledge - of a dataset can significantly alter learning outcomes. This research contributes to the current literature by testing how graphically eliciting users' knowledge may enhance their understanding and recall of data, specifically for bar charts. Three elicitation conditions are included in a controlled online experiment: Predict-only, Explain-only, and Predict-Explain. The expected results are that (1) participants in the three elicitation conditions outperform the baseline, (2) participants in Predict-Explain condition will recall data better than both Predict- and Explain-only condition, and (3) the effects of prediction and self-explanation are larger for participants with a low familiarity of the dataset.