A highly controlled laboratory experiment was conducted that suggested computer-based image training of rock classifications can provide a useful supplement to physical rock training. Two groups of participants learned to classify samples of 12 major types of rocks during a training phase. One group was trained using computer images of the rock samples, and another group was trained with physical rock samples. A third group that was familiarized with images of the samples but did not receive initial classification training served as a control. The participants' ability to generalize their training to the classification of novel, physical rock samples from the 12 types was then assessed in a test phase. All groups received trial-by-trial feedback during this test phase; still, the image-based and physical rock training groups maintained a significant performance advantage (75.2% correct) compared to the control group (37.5% correct). The group that received physical rock training performed only slightly better overall (77.8% correct) than the image-based training group (72.5% correct), although the advantage for the physical rock training group was substantial for some specific types of rocks from the complete set. The results provide documentation for the potential benefits of using image-based classification-training methods as a means of supplementing physical rock classification-training methods.