document: Web-based experiments controlled by JavaScript : an example from probability learning JavaScript programs can be used to control Web experiments . This technique is illustrated by an experiment that tested the effects of advice on performance in the classic probability-learning paradigm . Previous research reported that people tested via the Web or in the lab tended to match the probabilities of their responses to the probabilities that those responses would be reinforced . The optimal strategy , however , is to consistently choose the more frequent event ; probability matching produces suboptimal performance . We investigated manipulations we reasoned should improve performance . A horse race scenario in which participants predicted the winner in each of a series of races between two horses was compared with an abstract scenario used previously . Ten groups of learners received different amounts of advice , including all combinations of -LRB- 1 -RRB- explicit instructions concerning the optimal strategy , -LRB- 2 -RRB- explicit instructions concerning a monetary sum to maximize , and -LRB- 3 -RRB- accurate information concerning the probabilities of events . The results showed minimal effects of horse race versus abstract scenario . Both advice concerning the optimal strategy and probability information contributed significantly to performance in the task . This paper includes a brief tutorial on JavaScript , explaining with simple examples how to assemble a browser-based experiment
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