The primary data of many experimental studies of animal learning and performance consist of the times at which stimuli and reinforcers were delivered, and the times at which responses occurred. The articles based on most of these studies report selected data, either from some sessions or some animals, or summary measures of the animals' behavior. The primary data are sufficient to produce any of the selected and summary measures, but the selected and summarized data cannot produce many of the measures used in other experimental reports. It is now feasible to archive the primary data from animal behavior experiments so that they are accessible for others to perform secondary analysis. The value of such secondary analysis of archived data is described with a case study in which rats were trained on three fixed-interval schedules of reinforcement. The full data set may be downloaded from www.psychonomic.org/archive/.
This report presents a proposal to create archives of data from psychological research and associated metadata Web pages and link them into a heterogeneous distributed archive on the World-Wide Web. Several specific recommendations are made concerning some of the issues faced by the data archivist and data archive user hoping to use the Web. In particular, a recommendation is made to create a publicly accessible Web page for each data set and place keywords, experimental methods, data descriptions, pointers to journal articles, and pointers to other archive Web pages pertinent to this data set on this metadata Web page. If the archivist includes a special keyword (PsychologyDataArchive) on the metadata Web page, Web-based search engines will automatically be able to subset all participating data archives for indexing and semantic analysis. The secondary data analyst can then include the word PsychologyDataArchive in his Web search and will be able to effectively find relevant participating Web data archives.
A major methodological challenge in environmental sound research is to select appropriate stimuli. When an experiment involves a large number of sound sources, making custom recordings or producing sounds live is frequently impractical or, for certain sounds, impossible. Existing databases of environmental sound recordings provide a researcher with a useful alternative. However, finding and selecting suitable sounds in such databases can be difficult because of the great variety of sounds present, poor documentation, questionable recording quality, and required purchasing costs. This article describes a number of practical issues to consider during the stimulus selection process, offers a preliminary compilation of existing resources for obtaining environmental sound recordings, provides some normative perceptual data that can be used as a reference for selecting stimuli and evaluating performance, and lists required characteristics and structural aspects of a research-oriented environmental sound database.
We explored methods of using latent semantic analysis (LSA) to identify reading strategies in students’ self-explanations that are collected as part of a Web-based reading trainer. In this study, college students self-explained scientific texts, one sentence at a time. LSA was used to measure the similarity between the self-explanations andsemantic benchmarks (groups of words and sentences that together represent reading strategies). Three types of semantic benchmarks were compared: content words, exemplars, and strategies. Discriminant analyses were used to classify global and specific reading strategies using the LSA cosines. All benchmarks contributed to the classification of general reading strategies, but the exemplars did the best in distinguishing subtle semantic differences between reading strategies. Pragmatic and theoretical concerns of using LSA are discussed.
We present a set of stimuli representing human actions under point-light conditions, as seen from different viewpoints. The set contains 22 fairly short, well-delineated, and visually "loopable" actions. For each action, we provide movie files from five different viewpoints as well as a text file with the three spatial coordinates of the point lights, allowing researchers to construct customized versions. The full set of stimuli may be downloaded from www.psychonomic.org/archive/.
Interactive Strategy Training for Active Reading and Thinking (iSTART) is a Web-based application that provides young adolescent to college-age students with high-level reading strategy training to improve comprehension of science texts. iSTART is modeled after an effective, human-delivered intervention called self-explanation reading training (SERT), which trains readers to use active reading strategies to self-explain difficult texts more effectively. To make the training more widely available, the Web-based trainer has been developed. Transforming the training from a human-delivered application to a computer-based one has resulted in a highly interactive trainer that adapts its methods to the performance of the students. The iSTART trainer introduces the strategies in a simulated classroom setting with interaction between three animated characters-an instructor character and two student characters-and the human trainee. Thereafter, the trainee identifies the strategies in the explanations of a student character who is guided by an instructor character. Finally, the trainee practices self-explanation under the guidance of an instructor character. We describe this system and discuss how appropriate feedback is generated.
PMETRIC is a computer program for the analysis of observed psychometric functions. It can estimate the parameters of these functions, using either probit analysis (a parametric technique) or the Spearman-Kärber method (a nonparametric one). For probit analysis, either a maximum likelihood or a minimum χ2 criterion may be used for parameter estimation. In addition, standard errors of parameter estimates can be estimated via bootstrapping. The program can be used to analyze data obtained from either yes-no orm-alternative forced-choice tasks. To facilitate the use of PMETRIC in simulation work, an associated program, PMETGEN, is provided for the generation of simulated psychometric function data. Use of PMETRIC is illustrated with data from a duration discrimination task.
Verb subcategorization frequencies (verb biases) have been widely studied in psycholinguistics and play an important role in human sentence processing. Yet available resources on subcategorization frequencies suffer from limited coverage, limited ecological validity, and divergent coding criteria. Prior estimates of verb transitivity, for example, vary widely with corpus size, coverage, and coding criteria. This article provides norming data for 281 verbs of interest to psycholinguistic research, sampled from a corpus of American English, along with a detailed coding manual. We examine the effect on transitivity bias of various coding decisions and methods of computing verb biases.
Mathematical models of cognition often contain unknown parameters whose values are estimated from the data. A question that generally receives little attention is how informative such estimates are. In a maximum likelihood framework, standard errors provide a measure of informativeness. Here, a standard error is interpreted as the standard deviation of the distribution of parameter estimates over multiple samples. A drawback to this interpretation is that the assumptions that are required for the maximum likelihood framework are very difficult to test and are not always met. However, at least in the cognitive science community, it appears to be not well known that standard error calculation also yields interpretable intervals outside the typical maximum likelihood framework. We describe and motivate this procedure and, in combination with graphical methods, apply it to two recent models of categorization: ALCOVE (Kruschke, 1992) and the exemplar-based random walk model (Nosofsky & Palmeri, 1997). The applications reveal aspects of these models that were not hitherto known and bring a mix of bad and good news concerning estimation of these models.
Modern experiments in the behavioral sciences frequently employ several items of electronic equipment such as computers, monitoring devices, stimulus presentation equipment, and response collection systems. In many cases it would be advantageous for these items to communicate directly with each other. Such communication may facilitate greater automation of experiments (i.e., reduced experimenter influences during the experiment), more precise experiment control (i.e., superior timing and synchronization capabilities of electronic devices), and greater accuracy of data collection (i.e., reduced ambiguity of participant responses). Many electronic experiment devices already provide external interfacesthrough which communication with other devices can be implemented. The most common is based on the RS-232 protocol, which is also found in all standard PCs. Therefore, Microsoft Windows based computers can be programmed to control experiments by communicating directly with electronic experiment devices. We show how to implement this RS-232 interconnection between devices and a Windows PC using currently available software tools.
A new public archive of norms, stimuli, data, and source code,www.psychonomic.org/archive, is at the service of researchers and students in experimental psychology. The archive has received contributions from more than 60 researchers. The August and November 2004 issues ofBehavior Research Methods, Instruments, & Computers comprise articles related to the inaugural contents of the archive, which will henceforth accept contributions related to articles published in all Psychonomic Society journals.
We describe and test quantile maximum probability estimator (QMPE), an open-source ANSI Fortran 90 program for response time distribution estimation.(1) QMPE enables users to estimate parameters for the ex-Gaussian and Gumbel (1958) distributions, along with three "shifted" distributions (i.e., distributions with a parameter-dependent lower bound): the Lognormal, Wald, and Weibull distributions. Estimation can be performed using either the standard continuous maximum likelihood (CML) method or quantile maximum probability (QMP; Heathcote & Brown, in press). We review the properties of each distribution and the theoretical evidence showing that CML estimates fail for some cases with shifted distributions, whereas QMP estimates do not. In cases in which CML does not fail, a Monte Carlo investigation showed that QMP estimates were usually as good, and in some cases better, than CML estimates. However, the Monte Carlo study also uncovered problems that can occur with both CML and QMP estimates, particularly when samples are small and skew is low, highlighting the difficulties of estimating distributions with parameter-dependent lower bounds.
The 10-min psychomotor vigilance task (PVT) has often been used to assess the impact of sleep loss on performance. Due to time constraints, however, regular testing may not be practical in field studies. The aim of the present study was to examine the suitability of tests shorter than 10 min. in duration. Changes in performance across a night of sustained wakefulness were compared during a standard 10-min PVT, the first 5 min of the PVT, and the first 2 min of the PVT. Four performance metrics were assessed: (1) mean reaction time (RT), (2) fastest 10% of RT, (3) lapse percentage, and (4) slowest 10% of RT. Performance during the 10-min PVT significantly deteriorated with increasing wakefulness for all metrics. Performance during the first 5 min and the first 2 min of the PVT deteriorated in a manner similar to that observed for the whole 10-min task, with all metrics except lapse percentage displaying significant impairment across the night. However, the shorter the task sampling time, the less sensitive the test is to sleepiness. Nevertheless, the 5-min PVT may provide a viable alternative to the 10-min PVT for some performance metrics.
Tversky (1972) has proposed a family of models for paired-comparison data that generalize the Bradley—Terry—Luce (BTL) model and can, therefore, apply to a diversity of situations in which the BTL model is doomed to fail. In this article, we present a Matlab function that makes it easy to specify any of these general models (EBA, Pretree, or BTL) and to estimate their parameters. The program eliminates the time-consuming task of constructing the likelihood function by hand for every single model. The usage of the program is illustratedby several examples. Features of the algorithm are outlined. The purpose of this article is to facilitate the use of probabilistic choice models in the analysis of data resulting from paired comparisons.
AutoTutor is a learning environment that tutors students by holding a conversation in natural language. AutoTutor has been developed for Newtonian qualitative physics and computer literacy. Its design was inspired by explanation-based constructivist theories of learning, intelligent tutoring systems that adaptively respond to student knowledge, and empirical research on dialogue patterns in tutorial discourse. AutoTutor presents challenging problems (formulated as questions) from a curriculum script and then engages in mixed initiative dialogue that guides the student in building an answer. It provides the student with positive, neutral, or negative feedback on the student’s typed responses, pumps the student for more information, prompts the student to fill in missing words, gives hints, fills in missing information with assertions, identifies and corrects erroneous ideas, answers the student’s questions, and summarizes answers. AutoTutor has produced learning gains of approximately .70 sigma for deep levels of comprehension.
The aim of the present study was to provide French normative data for 112 action line drawings. The set of action pictures consisted of 71 drawings taken from Masterson and Druks (1998) and 41 additional drawings. It was standardized on six psycholinguistic variables--that is, name agreement, image agreement, image variability, visual complexity, conceptual familiarity, and age of acquisition (AoA). Naming latencies to the action pictures were collected, and a regression analysis was performed on the naming latencies, with the standardized variables, as well as with word frequency and length, taken as predictors. A reliable influence of AoA, name agreement, and image agreement on the naming latencies was observed. The findings are consistent with previous published studies in other languages. The full set of these norms may be downloaded from www.psychonomic.org/archive/.
A program called the Generalized Electronic Interviewing System (GEIS) was developed for conducting interviews, using computer-assisted telephone interview (CATI) and interactive voice response (IVR) modes without the need for a programmed interface. GEIS questionnaires were prepared using a common script syntax in all supported modes. Scripted development allowed for rapid interview development without the need for programming. A GEIS script specified the following: question texts, including variable texts; answer option texts; numeric codes for answers; range check information; logical question-branching information; interview status information; do-loop information; and IVR information, such as key codes and voice messages. GEIS thoroughly checked scripts for logical or syntactical errors. GEIS required SAS Version 8.0, and survey data were accumulated within SAS data sets. An application of GEIS to conduct a survey involving CATI, IVR, and a combined hybrid method is described. The CATI results deviated in the direction expected for sensitive questions, whereas IVR obtained a small sample size, rendering the results unreliable. However, the hybrid method was found to provide more accurate telephone survey data on alcohol consumption than did CATI alone. The program may be downloaded from the Psychonomic Society Web archive at www.psychonomic.org/archive/.
Lightness, the perceived gray shade of a surface, and the perception of self-luminous surfaces--that is, surfaces that appear to glow--have most often been studied with paper displays and computer-generated stimuli presented on CRT monitors. Although both methods are often effective, experiments that require a wide range of luminance values in the same display are often difficult to conduct with paper and computer displays alone. Also, color mode appearance is often an issue when surface color perception is the topic of research; CRT monitors are essentially light sources themselves and often appear in the luminous mode of color appearance. Here, we describe an apparatus in which the target is an undetected aperture whose luminance is adjustable. Whereas a typical CRT monitor offers a luminance range of about 100:1, much broader luminance ranges are possible with the described apparatus. Unlike a CRT monitor, the stimulus background will always appear in the surface mode of color perception, and the target(s) can appear as either surface colors or luminous colors. Apparatus modifications are possible, including the addition of a stereoscope or an embedded CRT for creating an adjustable region that is computer controlled.
We present a method for estimating parameters of connectionist models that allows the model's output to fit as closely as possible to empirical data. The method minimizes a cost function that measures the difference between statistics computed from the model's output and statistics computed from the subjects' performance. An optimization algorithm finds the values of the parameters that minimize the value of this cost function. The cost function also indicates whether the model's statistics are significantly different from the data's. In some cases, the method can find the optimal parameters automatically. In others, the method may facilitate the manual search for optimal parameters. The method has been implemented in Matlab, is fully documented, and is available for free download from the Psychonomic Society Web archive at www.psychonomic.org/archive/.
