We explore the following two cognitive questions regarding crosslinguistic variation in lexical semantic systems: Why are some linguistic categories—that is, the associations between a term and a portion of the semantic space—harder to learn than others? How does learning a language‐specific set of lexical categories affect processing in that semantic domain? Using a computational word‐learner, and the domain of color as a testbed, we investigate these questions by modeling both child acquisition of color terms and adult behavior on a non‐ (...) class='Hi'>verbal color discrimination task. A further goal is to test an approach to lexical semantic representation based on the principle that the more languages label any two situations with the same word, the more conceptually similar those two situations are. We compare such a crosslinguistically based semantic space to one based on perceptual similarity. Our computational model suggests a mechanistic explanation for the interplay between term frequency and the semantic closeness of learned categories in developmental error patterns for color terms. Our model also indicates how linguistic relativity effects could arise from an acquisition mechanism that yields language‐specific topologies for the same semantic domain. Moreover, we find that the crosslinguistically inspired semantic space supports these results at least as well as—and in some aspects better than—the purely perceptual one, thus confirming our approach as a practical and principled method for lexical semantic representation in cognitive modeling. (shrink)

Sequential action makes up the bulk of human daily activity, and yet much remains unknown about how people learn such actions. In one motor learning paradigm, the serial reaction time (SRT) task, people are taught a consistent sequence of button presses by cueing them with the next target response. However, the SRT task only records keypress response times to a cued target, and thus it cannot reveal the full time‐course of motion, including predictive movements. This paper describes a mouse movement (...) trajectory SRT task in which the cursor must be moved to a cued location. We replicated keypress SRT results, but also found that predictive movement—before the next cue appears—increased during the experiment. Moreover, trajectory analyses revealed that people developed a centering strategy under uncertainty. In a second experiment, we made prediction explicit, no longer cueing targets. Thus, participants had to explore the response alternatives and learn via reinforcement, receiving rewards and penalties for correct and incorrect actions, respectively. Participants were not told whether the sequence of stimuli was deterministic, nor if it would repeat, nor how long it was. Given the difficulty of the task, it is unsurprising that some learners performed poorly. However, many learners performed remarkably well, and some acquired the full 10‐item sequence within 10 repetitions. Comparing the high‐ and low‐performers’ detailed results in this reinforcement learning (RL) task with the first experiment's cued trajectory SRT task, we found similarities between the two tasks, suggesting that the effects in Experiment 1 are due to predictive, rather than reactive processes. Finally, we found that two standard model‐free reinforcement learning models fit the high‐performing participants, while the four low‐performing participants provide better fit with a simple negative recency bias model. (shrink)

Supraspan verbal list-learning tests, such as the Rey Auditory Verbal Learning Test (RAVLT), are classic neuropsychological tests for assessing verbal memory. In this study, we investigated the impact of the meaning of the words to be learned on 3 memory stages (short-term recall, learning, and delayed recall) in a cohort of 447 healthy adults. First, we compared scores obtained from the RAVLT (word condition) to those of an alternative version of this test using phonologically similar but meaningless (...) items (pseudoword condition) and observed how each score varied as a function of age and sex. Then, we collected the participants’ self-reported strategies to retain the word and pseudoword lists and examined if these strategies mediated the age and sex effects on memory scores. The word condition resulted in higher memory scores than pseudoword condition at each memory stage and even canceled out, for the learning stage, the detrimental effect of age that was observed for the short-term and delayed recall. When taking sex into account, the word advantage was observed only in women for short-term recall. The self-reported strategies, which were similar for words and pseudowords, were based on the position of the item on the list (word: 53 %, pseudoword: 37%) or the meaning of the item (word: 64%, pseudoword: 58%) and were used alone or in combination. The best memory performance was associated with the meaning strategy in the word condition and with the combination of the meaning and position strategies in the pseudoword condition. Finally, we found that the word advantage observed in women for short-term recall was mediated by the use of the meaning strategy. The RAVLT scores were thus highly dependent on word meaning, notably because it allowed efficient semantic knowledge-based strategies. Within the framework of Tulving’s declarative memory model, these results are at odds with the depiction of the RAVLT as a verbal episodic memory test as it is increasingly referred to in the literature. (shrink)

Sequential action makes up the bulk of human daily activity, and yet much remains unknown about how people learn such actions. In one motor learning paradigm, the serial reaction time (SRT) task, people are taught a consistent sequence of button presses by cueing them with the next target response. However, the SRT task only records keypress response times to a cued target, and thus it cannot reveal the full time‐course of motion, including predictive movements. This paper describes a mouse movement (...) trajectory SRT task in which the cursor must be moved to a cued location. We replicated keypress SRT results, but also found that predictive movement—before the next cue appears—increased during the experiment. Moreover, trajectory analyses revealed that people developed a centering strategy under uncertainty. In a second experiment, we made prediction explicit, no longer cueing targets. Thus, participants had to explore the response alternatives and learn via reinforcement, receiving rewards and penalties for correct and incorrect actions, respectively. Participants were not told whether the sequence of stimuli was deterministic, nor if it would repeat, nor how long it was. Given the difficulty of the task, it is unsurprising that some learners performed poorly. However, many learners performed remarkably well, and some acquired the full 10‐item sequence within 10 repetitions. Comparing the high‐ and low‐performers’ detailed results in this reinforcement learning (RL) task with the first experiment's cued trajectory SRT task, we found similarities between the two tasks, suggesting that the effects in Experiment 1 are due to predictive, rather than reactive processes. Finally, we found that two standard model‐free reinforcement learning models fit the high‐performing participants, while the four low‐performing participants provide better fit with a simple negative recency bias model. (shrink)

Transitive inference is claimed to be “deductive”. Yet every group/species ever reported apparently uses it. We asked 58 adults to solve five-term transitive tasks, requiring neither training nor premise learning. A computer-based procedure ensured all premises were continually visible. Response accuracy and RT (non-discriminative nRT ) were measured as is typically done. We also measured RT confined to correct responses ( cRT ). Overall, very few typical transitive phenomena emerged. The symbolic distance effect never extended to premise recall and (...) was not at all evident for nRT ; suggesting the use of non-deductive end-anchor strategies. For overall performance, and particularly the critical B ? D inference, our findings indicate that deductive transitive inference is far more intellectually challenging than previously thought. Contrasts of our present findings against previous findings suggest at least two distinct transitive inference modes, with most research and most computational models to date targeting an associative mode rather than their desired deductive mode. This conclusion fits well with the growing number of theories embracing a “dual process” conception of reasoning. Finally, our differing findings for nRT versus cRT suggest that researchers should give closer consideration to matching the RT measure they use to the particular conception of transitive inference they pre-held. (shrink)

We owe most scientific knowledge to methods of inquiry that are never formally analyzed. The analysis of behavior does not call for hypothetico-deductive methods. Statistics, taught in lieu of scientific method, is incompatible with major features of much laboratory research. Squeezing significance out of ambiguous data discourages the more promising step of scrapping the experiment and starting again. As a consequence, psychologists have taken flight from the laboratory. They have fled to Real People and the human interest of “real life,” (...) to Mathematical Models and the elegance of symbolic treatments, to the Inner Man and the explanatory preoccupation with inferred internal mechanisms, and to Laymanship and its appeal to “common sense.” An experimental analysis provides an alternative to these divertissements.The “theories” to which objection is raised here are not the basic assumptions essential to any scientific activity or statements that are not yet facts, but rather explanations which appeal to events taking place somewhere else, at some other level of observation, described in different terms, and measured, if at all, in different dimensions. Three types of learning theories satisfy this definition: physiological theories attempting to reduce behavior to events in the nervous system; mentalistic theories appealing to inferred inner events; and theories of the Conceptual Nervous System offered as explanatory models of behavior. It would be foolhardy to deny the achievements of such theories in the history of science. The question of whether they are necessary, however, has other implications.Experimental material in three areas illustrates the function of theory more concretely. Alternatives to behavior ratios, excitatory potentials, and so on demonstrate the utility of rate or probability of response as the basic datum in learning. Functional relations between behavior and environmental variables provide an account of why learning occurs. Activities such as preferring, choosing, discriminating, and matching can be dealt with solely in terms of behavior, without referring to processes in another dimensional system. The experiments are not offered as demonstrating that theories are not necessary but to suggest an alternative. Theory is possible in another sense. Beyond the collection of uniform relationships lies the need for a formal representation of the data reduced to a minimal number of terms. A theoretical construction may yield greater generality than any assemblage of facts; such a construction will not refer to another dimensional system. (shrink)

Cognitive diagnosis models (CDMs) allow classifying respondents into a set of discrete attribute profiles. The internal structure of the test is determined in a Q-matrix, whose correct specification is necessary to achieve an accurate attribute profile classification. Several empirical Q-matrix estimation and validation methods have been proposed with the aim of providing well-specified Q-matrices. However, these methods require the number of attributes to be set in advance. No systematic studies about CDMs dimensionality assessment have been conducted, which contrasts with (...) the vast existing literature for the factor analysis framework. To address this gap, the present study evaluates the performance of several dimensionality assessment methods from the factor analysis literature in determining the number of attributes in the context of CDMs. The explored methods were parallel analysis, minimum average partial, very simple structure, DETECT, empirical Kaiser criterion, exploratory graph analysis, and a machine learning factor forest model. Additionally, a model comparison approach was considered, which consists in comparing the model-fit of empirically estimated Q-matrices. The performance of these methods was assessed by means of a comprehensive simulation study that included different generating number of attributes, item qualities, sample sizes, ratios of the number of items to attribute, correlations among the attributes, attributes thresholds, and generating CDM. Results showed that parallel analysis (with Pearson correlations and mean eigenvalue criterion), factor forest model, and model comparison (with AIC) are suitable alternatives to determine the number of attributes in CDM applications, with an overall percentage of correct estimates above 76% of the conditions. The accuracy increased to 97% when these three methods agreed on the number of attributes. In short, the present study supports the use of three methods in assessing the dimensionality of CDMs. This will allow to test the assumption of correct dimensionality present in the Q-matrix estimation and validation methods, as well as to gather evidence of validity to support the use of the scores obtained with these models. The findings of this study are illustrated using real data from an intelligence test to provide guidelines for assessing the dimensionality of CDM data in applied settings. (shrink)

The process dissociation procedure (PDP) of implicit sequence learning states that the correct inclusion-task response contains the incorrect exclusion-task response. However, there has been no research to test the hypothesis. The current study used a single variable (Stimulus Onset Asynchrony SOA: 850 ms vs. 1350 ms) between-subjects design, with pre-task resting-state fMRI, to test and improve the classical PDP to the mutually exclusive theory (MET). (1) Behavioral data and neuroimaging data demonstrated that the classical PDP has not been (...) validated. In the SOA = 850 ms group, the correct inclusion-task response was at chance, but the incorrect exclusion-task response occurred greater than chance. In the SOA = 850 ms group, the two responses were not correlated, but in the SOA = 1,350 ms group and putting the two groups together, the two responses were in contrast to each other. In each group, brain areas whose amplitude of low frequency fluctuations (ALFFs) in the resting-state related to the two responses were either completely different or opposite to one another. However, the results were perfectly consistent with the MET proposed by the present study which suggests that the correct inclusion-task response is equal to the correct exclusion-task response is equal toC+A1, and the incorrect exclusion-task response is equal toA2.Cdenotes the controlled response andA1andA2denote two different automatic responses. (2) The improved PDP was proposed to categorize the 12 kinds of triplets as delineating four knowledge types, namely non-acquisition of knowledge, uncontrollable knowledge, half-controllable knowledge, and controllable knowledge with the MET. ALFFs in the resting-state could predict the four knowledge types of the improved PDP among two groups. The participants’ control of the four knowledge types (degree of consciousness) gradually improved. Correspondingly, the brain areas in the resting-state positively related to the four knowledge types, gradually changed from the sensory and motor network to the somatic sensorimotor network, and then to the implicit learning network, and then to the consciousness network. The brain areas in the resting-state negatively related to the four knowledge types gradually changed from the consciousness network to the sensory and motor network. As SOA increased, the brain areas associated with almost all the four knowledge types changed. (3) The inhomogeneous hypothesis of the MET is best suited to interpret behavioral and neuroimaging data; it states that the same components among the four knowledge types are not homogeneous, and the same knowledge types are not homogeneous between the two SOA groups. (shrink)

The subject of the study is the socio-cultural threats to the information security of Russian citizens associated with ChatGPT technologies (Chat Generative Pre-trained Transformer, a machine-generated text response generator simulating a dialogue). The object of research − evaluation of the ratio of advantages and threats of generative language models based on "machine learning" in modern (2021-2023) scientific literature (journals HAC K1, K2 and Scopus Q1, Q2). The scientific novelty of the research lies in the culturological approach to the analysis of (...) threats to the security of Russian citizens associated with the use of ChatGPT as one of the technologies of "artificial intelligence". The formulation of the problem of the classical Turing test "to distinguish a person from a machine" is characterized as a scholastic abstraction, instead a more correct and productive approach is proposed: a socio-cultural assessment of the value (based on cultural axiology) of new computer technologies. The starting point of the analysis is the determination of socio-cultural value (or, conversely, damage) as a result of the use of generative language models based on machine learning. Further, the contribution and responsibility of various socio-cultural subjects of its creation and application are revealed − user, creator and developer. The result of the application of the proposed approach is the deconstruction of the discourse of the "philosophy of artificial intelligence" in terms of uncritical translation of developer declarations intended for marketing and attracting financing. Hypertrophied perception, precariously balancing on the edge of utopia and dystopia, is assessed as a risk of incorrect identification and ranking of threats to information security. Assumptions about the hypothetical "superweapon of psychological warfare" mask modern incidents of cross-border leakage of confidential data, the risks of being held accountable for publishing deliberately false information and illegal content as a result of using ChatGPT. National security measures are recommended, including restrictive measures and increasing the general civil culture of information security of users, as well as the orientation of domestic developments of solutions of this type on traditional values, socio-cultural identity and interests of Russian citizens. (shrink)

Wayfinding is defined as the ability to learn and remember a route through an environment. Previous researchers have shown that young children have difficulties remembering routes. However, very few researchers have considered how to improve young children's wayfinding abilities. Therefore, we investigated ways to help children increase their wayfinding skills. In two studies, a total of 72 5-year olds were shown a route in a six turn maze in a virtual environment and were then asked to retrace this route by (...) themselves. A unique landmark was positioned at each junction and each junction was made up of two paths: a correct path and an incorrect path. Two different strategies improved route learning performance. In Experiment 1, verbally labeling on-route junction landmarks during the first walk reduced the number of errors and the number of trials to reach a learning criterion when the children retraced the route. In Experiment 2, encouraging children to attend to on-route junction landmarks on the first walk reduced the number of errors when the route was retraced. This was the first study to show that very young children can be taught route learning skills. The implications of our results are discussed. (shrink)

The closure of schools as a result of COVID-19 has been a critical global incident from which to rethink how education works in all our countries. Among the many changes generated by this crisis, all teaching became mediated by digital technologies. This paper intends to analyze the activities carried out during this time through digital technologies and the conceptions of teaching and learning that they reflect. We designed a Likert-type online questionnaire to measure the frequency of teaching activities. It (...) was answered by 1,403 teachers from Spain. The proposed activities varied depending on the learning promoted, the learning outcomes, the type of assessment to which the activities were directed, and the presence of cooperative activities. The major result of this study was that teachers used reproductive activities more frequently than constructive ones. We also found that most activities were those favoring verbal and attitudinal learning. The cooperative activities were the least frequent. Finally, through a cluster analysis, we identified four teaching profiles depending on the frequency and type of digital technologies use: Passive, Active, Reproductive, and Interpretative. The variable that produced the most consistent differences was previous digital technologies use These results show that Information and Communication Technologies uses are reproductive rather than constructive, which impedes effective digital technologies integration into the curriculum so that students gain 21st-century competencies. (shrink)

Five-year-old children categorized as skilled versus unskilled counters were given verbal estimation and number word comprehension tasks with numerosities 20 – 120. Skilled counters showed a linear relation between number words and nonsymbolic numerosities. Unskilled counters showed the same linear relation for smaller numbers to which they could count, but not for larger number words. Further tasks indicated that unskilled counters failed even to correctly order large number words differing by a 2 : 1 ratio, whereas they performed well (...) on this task with smaller numbers, and performed well on a nonsymbolic ordering task with the same numerosities. These findings provide evidence that large, approximate numerosity representations become linked to number words around the time that children learn to count to those words reliably. (shrink)

Sequence learning is fundamental to a wide range of cognitive functions. Explaining how sequences—and the relations between the elements they comprise—are learned is a fundamental challenge to cognitive science. However, although hundreds of articles addressing this question are published each year, the actual learning mechanisms involved in the learning of sequences are rarely investigated. We present three experiments that seek to examine these mechanisms during a typing task. Experiments 1 and 2 tested learning during typing single letters on each trial. (...) Experiment 3 tested for “chunking” of these letters into “words.” The results of these experiments were used to examine the mechanisms that could best account for them, with a focus on two particular proposals: statistical transitional probability learning and discriminative error-driven learning. Experiments 1 and 2 showed that error-driven learning was a better predictor of response latencies than either n-gram frequencies or transitional probabilities. No evidence for chunking was found in Experiment 3, probably due to interspersing visual cues with the motor response. In addition, learning occurred across a greater distance in Experiment 1 than Experiment 2, suggesting that the greater predictability that comes with increased structure leads to greater learnability. These results shed new light on the mechanism responsible for sequence learning. Despite the widely held assumption that transitional probability learning is essential to this process, the present results suggest instead that the sequences are learned through a process of discriminative learning, involving prediction and feedback from prediction error. (shrink)