Grapheme-color synaesthesia benefits rule-based Category learning

Researchers have long suspected that grapheme-color synaesthesia is useful, but research on its utility has so far focused primarily on episodic memory and perceptual discrimination. Here we ask whether it can be harnessed during rule-based Category learning. Participants learned through trial and error to classify grapheme pairs that were organized into categories on the basis of their associated synaesthetic colors. The performance of synaesthetes was similar to non-synaesthetes viewing graphemes that were physically colored in the same way. Specifically, synaesthetes learned to categorize stimuli effectively, they were able to transfer this learning to novel stimuli, and they falsely recognized grapheme-pair foils, all like non-synaesthetes viewing colored graphemes. These findings demonstrate that synaesthesia can be exploited when learning the kind of material taught in many classroom settings.     

SOS! An algorithm and software for the stochastic optimization of stimuli

The characteristics of the stimuli used in an experiment critically determine the theoretical questions the experiment can address. Yet there is relatively little methodological support for selecting optimal sets of items, and most researchers still carry out this process by hand. In this research, we present SOS, an algorithm and software package for the stochastic optimization of stimuli. SOS takes its inspiration from a simple manual stimulus selection heuristic that has been formalized and refined as a stochastic relaxation search. The algorithm rapidly and reliably selects a subset of possible stimuli that optimally satisfy the constraints imposed by an experimenter. This allows the experimenter to focus on selecting an optimization problem that suits his or her theoretical question and to avoid the tedious task of manually selecting stimuli. We detail how this optimization algorithm, combined with a vocabulary of constraints that define optimal sets, allows for the quick and rigorous assessment and maximization of the internal and external validity of experimental items. In doing so, the algorithm facilitates research using factorial, multiple/mixed-effects regression, and other experimental designs. We demonstrate the use of SOS with a case study and discuss other research situations that could benefit from this tool. Support for the generality of the algorithm is demonstrated through Monte Carlo simulations on a range of optimization problems faced by psychologists. The software implementation of SOS and a user manual are provided free of charge for academic purposes as precompiled binaries and MATLAB source files at http://sos.cnbc.cmu.edu.     

eDom: Norming software and relative meaning frequencies for 544 English homonyms

Words that are homonyms??that is, for which a single written and spoken form is associated with multiple, unrelated interpretations, such as COMPOUND, which can denote an <?enclosure?> or a <?composite?> meaning??are an invaluable class of items for studying word and discourse comprehension. When using homonyms as stimuli, it is critical to control for the relative frequencies of each interpretation, because this variable can drastically alter the empirical effects of homonymy. Currently, the standard method for estimating these frequencies is based on the classification of free associates generated for a homonym, but this approach is both assumption-laden and resource-demanding. Here, we outline an alternative norming methodology based on explicit ratings of the relative meaning frequencies of dictionary definitions. To evaluate this method, we collected and analyzed data in a norming study involving 544 English homonyms, using the eDom norming software that we developed for this purpose. Dictionary definitions were generally sufficient to exhaustively cover word meanings, and the methods converged on stable norms with fewer data and less effort on the part of the experimenter. The predictive validity of the norms was demonstrated in analyses of lexical decision data from the English Lexicon Project (Balota et al., Behavior Research Methods, 39, 445?C459, 2007), and from Armstrong and Plaut (Proceedings of the 33rd Annual Meeting of the Cognitive Science Society, 2223?C2228, 2011). On the basis of these results, our norming method obviates relying on the unsubstantiated assumptions involved in estimating relative meaning frequencies on the basis of classification of free associates. Additional details of the norming procedure, the meaning frequency norms, and the source code, standalone binaries, and user manual for the software are available at http://edom.cnbc.cmu.edu.     

Effect of an Automated Training Presentation on Pre-service Behavior Analysts’ Implementation of Trial-based Functional Analysis

The trial-based functional analysis (FA) is a useful alternative to the traditional FA in contexts in which it is challenging to establish environmental control for extended periods of time. Previous researchers have demonstrated that others can be trained to conduct trial-based FAs with high procedural fidelity by providing a didactic presentation, small group instruction, and then a performance evaluation. However, one barrier to replicating this training sequence is that didactic presentations are not standardized and presentations can vary considerably across different groups of trainers or researchers. We designed an automated didactic presentation with video models embedded throughout for trainers and researchers to use when training others to conduct trial-based FAs. The purpose of this study was to evaluate the effect of this presentation on participant fidelity to trial-based FA procedures. Results demonstrate improved fidelity following the presentation. However, the presentation alone was insufficient to establish consistently high levels of fidelity across all conditions for all participants. Thus, additional training components are required when teaching others to conduct trial-based FAs.     

Temporal characteristics of overt attentional behavior during category learning

Many theories of category learning incorporate mechanisms for selective attention, typically implemented as attention weights that change on a trial-by-trial basis. This is because there is relatively little data on within-trial changes in attention. We used eye tracking and mouse tracking as fine-grained measures of attention in three complex visual categorization tasks to investigate temporal patterns in overt attentional behavior within individual categorization decisions. In Experiments 1 and 2, we recorded participants’ eye movements while they performed three different categorization tasks. We extended previous research by demonstrating that not only are participants less likely to fixate irrelevant features, but also, when they do, these fixations are shorter than fixations to relevant features. We also found that participants’ fixation patterns show increasingly consistent temporal patterns. Participants were faster, although no more accurate, when their fixation sequences followed a consistent temporal structure. In Experiment 3, we replicated these findings in a task where participants used mouse movements to uncover features. Overall, we showed that there are important temporal regularities in information sampling during category learning that cannot be accounted for by existing models. These can be used to supplement extant models for richer predictions of how information is attended to during the buildup to a categorization decision.     

Evaluating Check-In Check-Out With Peer Tutors for Children With Attention Maintained Problem Behaviors

School Wide Positive Behavior Support provides schools with three tiers of support to address both academic and behavior challenges. The purpose of this study was to evaluate the use of peer tutors with three elementary students when applied to a Tier 2 intervention known as Check-In Check-Out (CICO). Peer tutors performed the morning check-in with the tutees by setting the expectations for the day and giving the tutees their Daily Progress Report (DPR) form. Throughout the day, the tutees took the DPR form to each class where they received a score from the teacher. At the end of the class period, the peer tutors provided the tutees with feedback on the scores received on the DPR form. Once the school day finished, the peer tutees checked-out with the tutors and received a reward if they met their percentage goal. The results of this study showed that CICO implemented by peers improved classroom behavior for all three participants.