[full article, abstract in English; abstract in Lithuanian] Constructionists operationalize a powerful notion they share with constructivists: individual learning is facilitated by building models of specific ideas, concepts, methods, objects, environments, feelings, dreams, memories and sounds using the learner’s current stock of knowledge. Constructionists do this by building models or artifacts that can be externally manipulated, interrogated by their builder, and verbally shared with others. Constructionists believe that new knowledge is created during these discussions. Constructionism is rich with heuristic methods (...) for both finding and constructing artifacts and for discussing these artifacts privately and publicly. Constructionists argue that both constructing and discussing are necessary for deep sense-making. This paper describes one specific constructionist learning method: visual modeling. It illustrates one educator’s approach, developed in the classroom over a 40-year period. It references the relevant literature; describes its pedagogic approach, materials and outcomes; and it offers a step-by-step example of one student’s thinking process. Finally, it presents – in appropriate narrative form – 15 arguments why the visual component extends the constructionist project and should be integrated into more educational programs. (shrink)

An important question about eye-movement behavior is when the decision is made to terminate a fixation and program the following saccade. Different approaches have found converging evidence in favor of a mixed-control account, in which there is some overlap between processing information at fixation and planning the following saccade. We examined one interesting instance of mixed control in visual search: lag-2 revisits, during which observers fixate a stimulus, move to a different stimulus, and then revisit the first stimulus on (...) the next fixation. Results show that the probability of lag-2 revisits occurring increased with the number of target-similar stimuli, and revisits were preceded by a brief fixation on the intervening distractor stimulus. We developed the Efficient Visual Sampling computational model to simulate our findings and to provide insight into mixed control of fixations and the perceptual, cognitive, and motor processes that produce lag-2 revisits. (shrink)

Understanding what is distinctive about the role of models in science requires characterizing broad patterns in how these models evolve in the face of experimental results. That is, we must examine not just model statics—how the model relates to theory, or represents the world, at some point in time—but also model dynamics—how the model both generates new experimental results and is modified in response to them. Visual representations of structure play a central role in the theoretical reasoning of organic (...) chemists. Not surprisingly, these representations have changed in important ways–in response to experimental and theoretical developments– throughout the history of organic chemistry. In many cases it is appropriate to understand the visual representations used by organic chemists as models. The evolution of the structural representations of organic chemists therefore provides a clear example of the dynamics of scientific modeling. In this paper I use a conception of scientific modeling drawn from the work of Mary Hesse to examine how the concept of a molecular conformation was incorporated into the visual representations of structure used by organic chemists. (shrink)

Recent developments in vision science have resulted in several major changes in our understanding of human visual perception. For example, attention no longer appears necessary for "visual intelligence"--a large amount of sophisticated processing can be done without it. Scene perception no longer appears to involve static, general-purpose descriptions, but instead may involve dynamic representations whose content depends on the individual and the task. And vision itself no longer appears to be limited to the production of a conscious "picture"--it (...) may also guide processes outside the conscious awareness of the observer. (shrink)

In Chinese orthography, the most common character structure consists of a semantic radical on the left and a phonetic radical on the right ; the minority, opposite arrangement also exists. Recent studies showed that SP character processing is more left hemisphere lateralized than PS character processing. Nevertheless, it remains unclear whether this is due to phonetic radical position or character type frequency. Through computational modeling with artificial lexicons, in which we implement a theory of hemispheric asymmetry in perception but (...) do not assume phonological processing being LH lateralized, we show that the difference in character type frequency alone is sufficient to exhibit the effect that the dominant type has a stronger LH lateralization than the minority type. This effect is due to higher visual similarity among characters in the dominant type than the minority type, demonstrating the modulation of visual similarity of words on hemispheric lateralization. (shrink)

I have argued that orthographic processing cannot be understood and modeled without considering the manner in which orthographic structure represents phonological, semantic, and morphological information in a given writing system. A reading theory, therefore, must be a theory of the interaction of the reader with his/her linguistic environment. This outlines a novel approach to studying and modeling visual word recognition, an approach that focuses on the common cognitive principles involved in processing printed words across different writing systems. These (...) claims were challenged by several commentaries that contested the merits of my general theoretical agenda, the relevance of the evolution of writing systems, and the plausibility of finding commonalities in reading across orthographies. Other commentaries extended the scope of the debate by bringing into the discussion additional perspectives. My response addresses all these issues. By considering the constraints of neurobiology on modeling reading, developmental data, and a large scope of cross-linguistic evidence, I argue that front-end implementations of orthographic processing that do not stem from a comprehensive theory of the complex information conveyed by writing systems do not present a viable approach for understanding reading. The common principles by which writing systems have evolved to represent orthographic, phonological, and semantic information in a language reveal the critical distributional characteristics of orthographic structure that govern reading behavior. Models of reading should thus be learning models, primarily constrained by cross-linguistic developmental evidence that describes how the statistical properties of writing systems shape the characteristics of orthographic processing. When this approach is adopted, a universal model of reading is possible. (shrink)

Intermediate constructs are required as bridges between complex behaviors and realistic models of neural circuitry. For cognitive scientists in general, schemas are the appropriate functional units; brain theorists can work with neural layers as units intermediate between structures subserving schemas and small neural circuits.After an account of different levels of analysis, we describe visuomotor coordination in terms of perceptual schemas and motor schemas. The interest of schemas to cognitive science in general is illustrated with the example of perceptual schemas in (...) high-level vision and motor schemas in the control of dextrous hands.Rana computatrix, the computational frog, is introduced to show how one constructs an evolving set of model families to mediate flexible cooperation between theory and experiment. Rana computatrix may be able to do for the study of the organizational principles of neural circuitry what Aplysia has done for the study of subcellular mechanisms of learning. Approach, avoidance, and detour behavior in frogs and toads are analyzed in terms of interacting schemas. Facilitation and prey recognition are implemented as tectal-pretectal interactions, with the tectum modeled by an array of tectal columns. We show how layered neural computation enters into models of stereopsis and how depth schemas may involve the interaction of accommodation and binocular cues in anurans. (shrink)

We introduce a new version of the perceptual retouch model. This model was used for explaining properties of temporal interaction of successive objects in reaching conscious representation. The new model incorporates two interactive binding operations – binding features for objects and binding the bound feature-objects with a large scale oscillatory system that corresponds to perceptual consciousness. Here, the typical result of masking experiments – second object advantage in conscious perception – is achieved by applying the effects of a common synchronizing (...) oscillator with a delay. This delayed modulation of each of the feature-binding first-order oscillators that represent emerging and decaying neural activities of each of the objects guarantees that the oscillating synchrony of the feature-neurons of the following object is higher than the synchrony of the feature-neurons of the first presented object. Thus we model the fact that the following object dominates the preceding object in conscious perception. We also show the capacity of the model to simulate illusory misbinding of features from different objects. The third qualitative effect, the relative release of the first object from backward masking is achieved by priming the non-specific oscillatory modulation ahead in time. (shrink)

While speakers have been shown to adapt to the knowledge state of their addressee in choosing referring expressions, they often also show some egocentric tendencies. The current paper aims to provide an explanation for this “mixed” behavior by presenting a model that derives such patterns from the probabilistic combination of both the speaker's and the addressee's perspectives. To test our model, we conducted a language production experiment, in which participants had to refer to objects in a context that also included (...) a visually misleading object whose function was either known to both partners, or known just to the speaker but not the addressee. Modeling results indicate that the experimental findings cannot be explained by assuming that speakers tailor a referring expression solely to their own perspective or to the perspective of their addressee. Instead, accounting for the behavioral pattern requires an approach where both perspectives influence the choice of referring expressions. Nevertheless, in our situation, speakers consider their partner's perspective more than their own. (shrink)

Visual working memory is a construct hypothesized to store a small amount of accurate perceptual information that can be brought to bear on a task. Much research concerns the construct's capacity and the precision of the information stored. Two prominent theories of VWM representation have emerged: slot-based and continuous-resource mechanisms. Prior modeling work suggests that a continuous resource that varies over trials with variable capacity and a potential to make localization errors best accounts for the empirical data. Questions (...) remain regarding the variability in VWM capacity and precision. Using a novel eye-tracking paradigm, we demonstrate that VWM facilitates search and exhibits effects of fixation frequency and recency, particularly for prior targets. Whereas slot-based memory models cannot account for the human data, a novel continuous-resource model does capture the behavioral and eye tracking data, and identifies the relevant resource as item activation. (shrink)

The redundant-signals paradigm (RSP) is designed to investigate response behavior in perceptual tasks in which response-relevant targets are defined by either one or two features, or modalities. The common finding is that responses are speeded for redundantly compared to singly defined targets. This redundant-signals effect (RSE) can be accounted for by race models if the response times do not violate the race model inequality (RMI). When there are violations of the RMI, race models are effectively excluded as a viable account (...) of the RSE. The common alternative is provided by co-activation accounts, which assume that redundant target signals are integrated at some processing stage. However, ‘co-activation’ has mostly been only indirectly inferred and the accounts have only rarely been explicitly modeled; if they were modeled, the RSE has typically been assumed to have a decisional locus. Yet, there are also indications in the literature that the RSE might originate, at least in part, at a non-decisional or motor stage. In the present study, using a distribution analysis of sequential-sampling models (ex-Wald and Ratcliff Diffusion model), the locus of the RSE was investigated for two bimodal (audio-visual) detection tasks that strongly violated the RMI, indicative of substantial co-activation. Three model variants assuming different loci of the RSE were fitted to the quantile reaction time proportions: a decision, a non-decision, and a combined variant both to vincentized group as well as individual data. The results suggest that for the two bimodal detection tasks, co-activation has a shared decisional and non-decisional locus. These findings point to the possibility that the mechanisms underlying the RSE depend on the specifics (task, stimulus, conditions, etc.) of the experimental paradigm. (shrink)

This paper uses autocatalytic networks to model discontinuous cultural transitions involving cross-domain transfer, using as an illustrative example, artworks inspired by the oldest-known uncontested example of figurative art: the carving of the Hohlenstein-Stadel Löwenmensch, or lion-human. Autocatalytic networks provide a general modeling setting in which nodes are not just passive transmitters of activation; they actively galvanize, or “catalyze” the synthesis of novel nodes from existing ones This makes them uniquely suited to model how new structure grows out of earlier (...) structure, i.e., cumulative, generative network growth. They have been used to model the origin and early evolution of biological life, and the emergence of cognitive structures capable of undergoing cultural evolution. We conducted a study in which six individual creators and one group generated music, prose, poetry, and visual art inspired by the Hohlenstein-Stadel Löwenmensch, and answered questions about the process. The data revealed four through-lines by which they expressed the Löwenmensch in an alternative art form: lion-human hybrid, subtracting from the whole to reveal the form within, deterioration, and waiting to be found with a story to tell. Autocatalytic networks were used to model how these four spontaneously derived through-lines form a cultural lineage from Löwenmensch to artist to audience. We used the resulting data from three creators to model the cross-domain transfer from inspirational source to creative product. These four spontaneously-generated threads of cultural continuity formed the backbone of this Löwenmensch-inspired cultural lineage, enabling culture to evolve even in the face of discontinuity at the level conventional categories or domains. We know of no other theory of cultural evolution that accommodates cross-domain transfer or other forms of discontinuity. The approach paves the way for a broad scientific framework for the origins of evolutionary processes. (shrink)

We study the claim that multisensory environments are useful for visual learning because nonvisual percepts can be processed to produce error signals that people can use to adapt their visual systems. This hypothesis is motivated by a Bayesian network framework. The framework is useful because it ties together three observations that have appeared in the literature: (a) signals from nonvisual modalities can “teach” the visual system; (b) signals from nonvisual modalities can facilitate learning in the visual (...) system; and (c) visual signals can become associated with (or be predicted by) signals from nonvisual modalities. Experimental data consistent with each of these observations are reviewed. (shrink)

Arts and Humanities in Higher Education, Volume 21, Issue 3, Page 240-262, July 2022. Although the art historical canon has been the subject of fierce debate, it remains an essential construct, shaping textbooks and survey courses. Visual representations of the canon often illustrate these narratives. Students encounter diagrams in their studies and it is important to make them aware of the illusion of scientific objectivity. This paper proposes the use of the computer ontology, as a modeling tool with (...) which students can make translations of existing diagrams. This forces them to reconsider the modeling decisions underlying traditional representations. The article takes as its case study the translation of Alfred Barr’s diagram of Modern Art, using the free tool Protégé. An analysis of this process allows us to consider the ambiguous meanings of nodes, relationships and dimensions of the model. Asking students to actively recreate this network of information is shown to be a valuable addition to traditional survey courses on Modern Art. (shrink)

Recent philosophical analyses of the epistemic dimension of images in the sciences show a certain trend in acknowledging potential roles of these images beyond their merely decorative or pedagogical functions. We argue, however, that this new debate has yet paid little attention to a special type of pictures, we call ‘visual metaphor’, and its versatile heuristic potential in organizing data, supporting communication, and guiding research, modeling, and theory formation. Based on a case study of Conrad Hal Waddington’s epigenetic (...) landscape images in biology, we develop a descriptive framework applicable to heuristic roles of various visual metaphors in the sciences. (shrink)

Visual Search without Selective Attention calls into question the necessity of a covert selective attention mechanism by implementing a formal model that includes basic visual mechanisms, saccades, and simple task strategies. Across three search tasks, the model accounts for response times as well as the proportion of errors observed in human participants, including effects of item crowding in the visual stimulus.

Comparative modeling is necessary for semiotic inquiry. To better theorize such pursuits, a reflexive turn is in order: comparative modeling needs comparative modeling. In search of experientially grounded analogies better suited for understanding, validating, scrutinizing, and accounting for the situation of the semiotic inquirer, this paper applies insights from Peircean process semiotics and Göran Sonesson’s extended theory of cultural semiotics toward two ends: one theoretical, the other applied. First, I undertake a critical review of recent scholarly and (...) creative works that attempt to adapt concepts of “parallax” as a source domain for comparative modeling activities. I do this in order to continue laying groundwork for a more complex, systematic theory of reflexive semiotic modeling in human inquiry, building on my earlier work. Second, I explore a specific case study of comparative intercultural modeling: namely, nationalist ethnic classification strategies in China and Vietnam. While many researchers have considered the onomastic and geopolitical dimensions of state-sanctioned ethnic categorization programs in these two countries, little has been done to unpack the powerful visual and narratological strategies employed by both; and little has been done to compare the intercultural categories these strategies serve to legitimize. The Vietnamese classification program is clearly modeled on its Chinese counterpart historically, but important categorical mismatches emerge between the two that indicate the presence of hidden diversity. Comparing the two systems also leads to a number of discoveries with implications for further developing the theory of cultural semiotics. Ultimately, the function or purpose of parallax modeling is shown to both comprehend and point beyond nascent intercultural and intracultural models toward more complex blends, by holding all such relations in a comparative frame, not as irreconcilable positions but as a more developed composite sign indicating the presence of yet more deeply buried dynamic objects to be searched out through further collateral experience. (shrink)

A physical model was utilized to show that the neural system can memorize a target position and is able to cause motor and sensory events that move the arm to a target with more accuracy. However, this cannot indicate in which coordinates the necessary computations are carried out. Turning off the lights causes the error to increase which is accomplished by cutting off one feedback path. The geometrical properties of arm kinematics and the properties of the kinesthetic and visual (...) sensorial systems should be better known before inferences about higher levels of processing can be drawn. (shrink)

The aim of this paper is to grasp the relevant distinctions between various ways in which models and simulations in Artificial Intelligence (AI) relate to cognitive phenomena. In order to get a systematic picture, a taxonomy is developed that is based on the coordinates of formal versus material analogies and theory-guided versus pre-theoretic models in science. These distinctions have parallels in the computational versus mimetic aspects and in analytic versus exploratory types of computer simulation. The proposed taxonomy cuts across the (...) traditional dichotomies between symbolic and embodied AI, general intelligence and symbol and intelligence and cognitive simulation and human/non-human-like AI. -/- According to the taxonomy proposed here, one can distinguish between four distinct general approaches that figured prominently in early and classical AI, and that have partly developed into distinct research programs: first, phenomenal simulations (e.g., Turing’s “imitation game”); second, simulations that explore general-level formal isomorphisms in pursuit of a general theory of intelligence (e.g., logic-based AI); third, simulations as exploratory material models that serve to develop theoretical accounts of cognitive processes (e.g., Marr’s stages of visual processing and classical connectionism); and fourth, simulations as strictly formal models of a theory of computation that postulates cognitive processes to be isomorphic with computational processes (strong symbolic AI). -/- In continuation of pragmatic views of the modes of modeling and simulating world affairs, this taxonomy of approaches to modeling in AI helps to elucidate how available computational concepts and simulational resources contribute to the modes of representation and theory development in AI research—and what made that research program uniquely dependent on them. (shrink)

Recent philosophical analyses of the epistemic dimension of images in the sciences show a certain trend in acknowledging potential roles of these images beyond their merely decorative or pedagogical functions. We argue, however, that this new debate has yet paid little attention to a special type of pictures, we call ‘visual metaphor’, and its versatile heuristic potential in organizing data, supporting communication, and guiding research, modeling, and theory formation. Based on a case study of Conrad Hal Waddington’s epigenetic (...) landscape images in biology, we develop a descriptive framework applicable to heuristic roles of various visual metaphors in the sciences. (shrink)

Although benefits of design perception have been documented from the perspective of consumers on a large scale, but the perspective of employees has been ignored. This study aims to investigate the impact of design elements on employee-brand-based equity under the mediating role of the green concept. For this purpose, data are collected from the employees of the manufacturing sector and 346 responses are used for an inferential purpose. These data were collected using the survey research method through the convenience sampling (...) technique. Data has been analyzed through Smart PLS by applying the structural equation modeling technique. After assessing the measurement and structural model, the results obtained indicate that design elements of products in the manufacturing industry can influence the perception of employees and it can foster positive behavior among employees in the shape of employee-brand-based equity. The mediating role of the green concept has also been proved. Limitations and future directions are also discussed. (shrink)

Through computational modeling, here we examine whether visual and task characteristics of writing systems alone can account for lateralization differences in visual word recognition between different languages without assuming influence from left hemisphere (LH) lateralized language processes. We apply a hemispheric processing model of face recognition to visual word recognition; the model implements a theory of hemispheric asymmetry in perception that posits low spatial frequency biases in the right hemisphere and high spatial frequency (HSF) biases in (...) the LH. We show two factors that can influence lateralization: (a) Visual similarity among words: The more similar the words in the lexicon look visually, the more HSF/LH processing is required to distinguish them, and (b) Requirement to decompose words into graphemes for grapheme-phoneme mapping: Alphabetic reading (involving grapheme-phoneme conversion) requires more HSF/LH processing than logographic reading (no grapheme-phoneme mapping). These factors may explain the difference in lateralization between English and Chinese orthographic processing. (shrink)

Advances in artificial intelligence have raised a basic question about human intelligence: Is human reasoning best emulated by applying task‐specific knowledge acquired from a wealth of prior experience, or is it based on the domain‐general manipulation and comparison of mental representations? We address this question for the case of visual analogical reasoning. Using realistic images of familiar three‐dimensional objects (cars and their parts), we systematically manipulated viewpoints, part relations, and entity properties in visual analogy problems. We compared human (...) performance to that of two recent deep learning models (Siamese Network and Relation Network) that were directly trained to solve these problems and to apply their task‐specific knowledge to analogical reasoning. We also developed a new model using part‐based comparison (PCM) by applying a domain‐general mapping procedure to learned representations of cars and their component parts. Across four‐term analogies (Experiment 1) and open‐ended analogies (Experiment 2), the domain‐general PCM model, but not the task‐specific deep learning models, generated performance similar in key aspects to that of human reasoners. These findings provide evidence that human‐like analogical reasoning is unlikely to be achieved by applying deep learning with big data to a specific type of analogy problem. Rather, humans do (and machines might) achieve analogical reasoning by learning representations that encode structural information useful for multiple tasks, coupled with efficient computation of relational similarity. (shrink)

The visual world of adults consists of objects at various distances, partly occluding one another, substantial and stable across space and time. The visual world of young infants, in contrast, is often fragmented and unstable, consisting not of coherent objects but rather surfaces that move in unpredictable ways. Evidence from computational modeling and from experiments with human infants highlights three kinds of learning that contribute to infants’ knowledge of the visual world: learning via association, learning via (...) active assembly, and learning via visual-manual exploration. Infants acquire knowledge by observing objects move in and out of sight, forming associations of these different views. In addition, the infant’s own self-produced behavior—oculomotor patterns and manual experience, in particular—is an important means by which infants discover and construct their visual world. (shrink)

Analogy and similarity are central phenomena in human cognition, involved in processes ranging from visual perception to conceptual change. To capture this centrality requires that a model of comparison must be able to integrate with other processes and handle the size and complexity of the representations required by the tasks being modeled. This paper describes extensions to Structure-Mapping Engine since its inception in 1986 that have increased its scope of operation. We first review the basic SME algorithm, describe psychological (...) evidence for SME as a process model, and summarize its role in simulating similarity-based retrieval and generalization. Then we describe five techniques now incorporated into the SME that have enabled it to tackle large-scale modeling tasks: Greedy merging rapidly constructs one or more best interpretations of a match in polynomial time: O); Incremental operation enables mappings to be extended as new information is retrieved or derived about the base or target, to model situations where information in a task is updated over time; Ubiquitous predicates model the varying degrees to which items may suggest alignment; Structural evaluation of analogical inferences models aspects of plausibility judgments; Match filters enable large-scale task models to communicate constraints to SME to influence the mapping process. We illustrate via examples from published studies how these enable it to capture a broader range of psychological phenomena than before. (shrink)

An incoherent visualization is when aspects of different senses of a word are present in the same visualization. We describe and implement a new model of creating contextual coherence in the visual imagination called Coherencer, based on the SOILIE model of imagination. We show that Coherencer is able to generate scene descriptions that are more coherent than SOILIE's original approach as well as a parallel connectionist algorithm that is considered competitive in the literature on general coherence. We also show (...) that co-occurrence probabilities are a better association representation than holographic vectors and that better models of coherence improve the resulting output independent of the association type that is used. Theoretically, we show that Coherencer is consistent with other models of cognitive generation. In particular, Coherencer is a similar, but more cognitively plausible model than the C3 model of concept combination created by Costello and Keane. We show that Coherencer is also consistent with both the modal schematic indices of perceptual symbol systems theory and the amodal contextual constraints of Thagard's theory of coherence. Finally, we describe how Coherencer is consistent with contemporary research on the hippocampus, and we show evidence that the process of making a visualization coherent is serial. (shrink)

The generation and use of 3D images and visualizations through remote sensing, Building Information Modeling, and Augmented Reality technologies, have come to play a significant role in construction engineering practice. Although these technologies are promising, their potential can be misjudged when potential end-users are unaware of key assumptions that were made by developers. Realistic expectations require insights into the ways in which these technologies transform input collected into 3D visualizations and how these visualizations are possibly used on construction sites. (...) This study’s objective is hence to explore the form of technological mediation that the generation and use of 3D images and visualizations provide between a human and objects, or aspects of these objects, that would otherwise be largely imperceptible to professionals in construction practice. We show that algorithms pre- and post-process data through their technological selectivities, which function as mediators. Double mediations of augmented and engaged relationships play a dominant role in the use of 3D images and visualizations and enhance the situational awareness of professionals in construction practice. This is the first study that applies this perspective to increase the understanding of the mediating role of 3D images and visualizations in construction practice. (shrink)

The Visual World Paradigm (VWP) presents listeners with a challenging problem: They must integrate two disparate signals, the spoken language and the visual context, in support of action (e.g., complex movements of the eyes across a scene). We present Impulse Processing, a dynamical systems approach to incremental eye movements in the visual world that suggests a framework for integrating language, vision, and action generally. Our approach assumes that impulses driven by the language and the visual context (...) impinge minutely on a dynamical landscape of attractors corresponding to the potential eye-movement behaviors of the system. We test three unique predictions of our approach in an empirical study in the VWP, and describe an implementation in an artificial neural network. We discuss the Impulse Processing framework in relation to other models of the VWP. (shrink)

Sketching as a scientific practice goes beyond the simple act of inscribing diagrams onto paper. Scientists produce a wide range of representations through sketching, as it is tightly coupled to model-based reasoning. Chemists in particular make extensive use of sketches to reason about chemical phenomena and to communicate their ideas. However, the chemical sciences have a unique problem in that chemists deal with the unseen world of the atomic-molecular level. Using sketches, chemists strive to develop causal mechanisms that emerge from (...) the structure and behavior of molecular-level entities, to explain observations of the macroscopic visible world. Interpreting these representations and constructing sketches of molecular-level processes is a crucial component of student learning in the modern chemistry classroom. Sketches also serve as an important component of assessment in the chemistry classroom as student sketches give insight into developing mental models, which allows instructors to observe how students are thinking about a process. In this paper we discuss how sketching can be used to promote such model-based reasoning in chemistry and discuss two case studies of curricular projects, CLUE and The Connected Chemistry Curriculum, that have demonstrated a benefit of this approach. We show how sketching activities can be centrally integrated into classroom norms to promote model-based reasoning both with and without component visualizations. Importantly, each of these projects deploys sketching in support of other types of inquiry activities, such as making predictions or depicting models to support a claim; sketching is not an isolated activity but is used as a tool to support model-based reasoning in the discipline. (shrink)

Differences in the ability of students to judge images can be assessed by analyzing the individual preference order of images. To gain insights into potential heterogeneity in judgement of visual abstraction among students, we combine Bradley–Terry preference modeling and model-based recursive partitioning. In an experiment a sample of 1,020 high-school students ranked five sets of images, three of which with respect to their level of visual abstraction. Additionally, 24 art experts and 25 novices were given the same (...) task, while their eye movements were recorded. Results show that time spent on the task, the students’ age, and self-reported interest in visual puzzles had significant influence on rankings. Fixation time of experts and novices revealed that both groups paid more attention to ambiguous images. The presented approach makes the underlying latent scale of visual judgments quantifiable. (shrink)

Visual word recognition is facilitated by the presence of orthographic neighbors that mismatch the target word by a single letter substitution. However, researchers typically do not consider where neighbors mismatch the target. In light of evidence that some letter positions are more informative than others, we investigate whether the influence of orthographic neighbors differs across letter positions. To do so, we quantify the number of enemies at each letter position (how many neighbors mismatch the target word at that position). (...) Analyses of reaction time data from a visual word naming task indicate that the influence of enemies differs across letter positions, with the negative impacts of enemies being most pronounced at letter positions where readers have low prior uncertainty about which letters they will encounter (i.e., positions with low entropy). To understand the computational mechanisms that give rise to such positional entropy effects, we introduce a new computational model, VOISeR (Visual Orthographic Input Serial Reader), which receives orthographic inputs in parallel and produces an over‐time sequence of phonemes as output. VOISeR produces a similar pattern of results as in the human data, suggesting that positional entropy effects may emerge even when letters are not sampled serially. Finally, we demonstrate that these effects also emerge in human subjects' data from a lexical decision task, illustrating the generalizability of positional entropy effects across visual word recognition paradigms. Taken together, such work suggests that research into orthographic neighbor effects in visual word recognition should also consider differences between letter positions. (shrink)

The Emergic Cognitive Model (ECM) is a unified computational model of visual filling-in based on the Emergic Network architecture. The Emergic Network was designed to help realize systems undergoing continuous change. In this thesis, eight different filling-in phenomena are demonstrated under a regime of continuous eye movement (and under static eye conditions as well). -/- ECM indirectly demonstrates the power of unification inherent with Emergic Networks when cognition is decomposed according to finer-grained functions supporting change. These can interact to (...) raise additional emergent behaviours via cognitive re-use, hence the Emergic prefix throughout. Nevertheless, the model is robust and parameter free. Differential re-use occurs in the nature of model interaction with a particular testing paradigm. -/- ECM has a novel decomposition due to the requirements of handling motion and of supporting unified modelling via finer functional grains. The breadth of phenomenal behaviour covered is largely to lend credence to our novel decomposition. -/- The Emergic Network architecture is a hybrid between classical connectionism and classical computationalism that facilitates the construction of unified cognitive models. It helps cutting up of functionalism into finer-grains distributed over space (by harnessing massive recurrence) and over time (by harnessing continuous change), yet simplifies by using standard computer code to focus on the interaction of information flows. Thus while the structure of the network looks neurocentric, the dynamics are best understood in flowcentric terms. Surprisingly, dynamic system analysis (as usually understood) is not involved. An Emergic Network is engineered much like straightforward software or hardware systems that deal with continuously varying inputs. Ultimately, this thesis addresses the problem of reduction and induction over complex systems, and the Emergic Network architecture is merely a tool to assist in this epistemic endeavour. -/- ECM is strictly a sensory model and apart from perception, yet it is informed by phenomenology. It addresses the attribution problem of how much of a phenomenon is best explained at a sensory level of analysis, rather than at a perceptual one. As the causal information flows are stable under eye movement, we hypothesize that they are the locus of consciousness, howsoever it is ultimately realized. (shrink)