Cross-modal semantic priming and phoneme monitoring experiments investigated processing of word-final nonreleased stop consonants (e.g., kit may be pronounced /kit/ or /ki/), which are common phonological variants in American English. Both voiced /d/ and voiceless /t/ segments were presented in release and no-release versions. A cross-modal semantic priming task (Experiment 1) showed comparable priming for /d/ and /t/ versions. A second set of stimuli ending in /s/ were presented as intact, missing /s/, or with a mismatching final segment and showed significant but reduced priming for the latter two conditions. Experiment 2 showed that phoneme monitoring reaction time for release and no-release words and onset mismatching stimuli (derived pseudowords) increased as acoustic-phonetic similarity to the intended word decreased. The results suggest that spoken word recognition does not require special mechanisms for processing no-release variants. Rather, the results can be accounted for by means of existing assumptions concerning probabilistic activation that is based on partial activation.
The present laboratory configuration addresses concerns beyond the functional workings of a computerized research system to include human factors. The logistical aspects of error-free multioperator operations are discussed along with the economics of developing, assembling, and maintaining the stations. The actual configurations (hardware and software) of the present laboratory are explained and discussed, as are the philosophies and experiences that led to a highly successful combined research and teaching operant laboratory.The primary purpose behind the development of the laboratory described in this paper was to assemble a system versatile enough to run a wide variety of operant conditioning paradigms, maximizing for ease of operation. In addition to the automation required to allow for flexibility in experimentation, human factors principles were utilized to facilitate the use of the lab by many different researchers, including various student assistants. The paradox of automation is that the more systematic the process, the less the involvement ofthe experimenters. The result is a greater potential for unnoticed problems and more opportunity for mistakes to be made due to automation-induced laxness. Finally, the less involved the student experimenter is with the process, the less he or she learns.Anyone who has ever taught an experimentallaboratory course in operant conditioning knows that it is often difficult to decide how much to have the students do "by hand." A good example would be the development of basic schedules of reinforcement. The slow emergence of the fixed-interval scallop is nearly impossible to portray enthusiastically in a lecture, and then does not easily become clear if the student in the laboratory merely puts the animal in the box, turns on the computer, and removes the animal after a session. The answer does not lie in returning to the time before the technology of today, but rather in a blend of today's technologies that optimizes error reduction and experimenter involvement. In the present laboratory, student researchers record the data by hand from the computer screen at set intervals. This on-screen data can be portrayed numerically, graphically, Correspondence should be directed to
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