Pray for the fatherland! Discursive and digital strategies at play in nationalist political blogging

Political blogs have come to constitute important channels for expressing nationalist and anti-immigration political views. The new forms that this rhetoric may take, comprising an intricate intermingling of verbal, digital, (audio-)visual, and communicative elements, present challenges for qualitative research. In this article we propose a way for analysing this “new” nationalist political discourse from a qualitative social psychological perspective. The suggested approach combines analytical procedures form critical discursive and rhetorical psychology with social semiotic and rhetorical studies of images, completed with analytical tools and concepts from narrative psychology and research into online political communication. Using two empirical examples of nationalist and anti-immigration political blog-entries written during the 2015 “refugee crisis,” we show this approach enables the researcher to adequately study how such political messages are conveyed through the multitude of elements provided by the blogs. In so doing, our ultimate goal is to contribute to the analytical capacity of qualitative social psychological research into contemporary political communication and persuasion.     

The Acquisition of Qualitative Physics Knowledge During Textbook-Based Physics Training

Several earlier investigations found that teaching standard textbook physics causes only moderate change in qualitative understanding. Many investigations have tried to explain why teaching textbook physics results in so little learning of qualitative physics. In contrast, we examined cases where learning did occur and tried to understand them, hoping that this might help us to understand how to support such learning. We developed computerized simulation models of both qualitative, conceptual problem solving and quantitative problem solving and used them to assess changes in students' qualitative knowledge as they learned textbook physics. In many cases, qualitative knowledge has been acquired on the basis of information explicitly presented in the textbook. We also found cases, however, where learning of qualitative physics took place on the basis of information only implicitly addressed in the instruction. Even more important, in various cases, this newly acquired qualitative knowledge led to a less frequent use of incorrect qualitative preknowledge. This suggests that successful students not only learn what has been explicitly presented in the instruction but also learn by deriving and constructing information left implicit in the instruction, relating this information to their preknowledge and possibly refining and modifying their preknowledge in those cases where conflicts became salient.     

Experience With a Linguistic Variant Affects the Acquisition of Its Sociolinguistic Meaning: An Alien-Language-Learning Experiment

How do speakers learn the social meaning of different linguistic variants, and what factors influence how likely a particular social–linguistic association is to be learned? It has been argued that the social meaning of more salient variants should be learned faster, and that learners' pre-existing experience of a variant will influence its salience. In this paper, we report two artificial-language-learning experiments investigating this. Each experiment involved two language-learning stages followed by a test. The first stage introduced the artificial language and trained participants in it, while the second stage added a simple social context using images of cartoon aliens. The first learning stage was intended to establish participants' experience with the artificial language in general and with the distribution of linguistic variants in particular. The second stage, in which linguistic stimuli were accompanied by images of particular aliens, was intended to simulate the acquisition of linguistic variants in a social context. In our first experiment, we manipulated whether a particular linguistic variant, associated with one species of alien in the second learning phase, had been encountered in the first learning phase. In the second experiment, we manipulated whether the variant had been encountered in the same grammatical context. In both cases we predicted that the unexpectedness of a new variant or a new grammatical context for an old variant would increase the variant's salience and facilitate the learning of its social meaning. This is what we found, although in the second experiment, the effect was driven by better learners. Our results suggest that unexpectedness increases the salience of variants and makes their social distribution easier to learn, deepening our understanding of the role of individual language experience in the acquisition of sociolinguistic meaning.     

Integrating the Automatic and the Controlled: Strategies in Semantic Priming in an Attractor Network With Latching Dynamics

Semantic priming has long been recognized to reflect, along with automatic semantic mechanisms, the contribution of controlled strategies. However, previous theories of controlled priming were mostly qualitative, lacking common grounds with modern mathematical models of automatic priming based on neural networks. Recently, we introduced a novel attractor network model of automatic semantic priming with latching dynamics. Here, we extend this work to show how the same model can also account for important findings regarding controlled processes. Assuming the rate of semantic transitions in the network can be adapted using simple reinforcement learning, we show how basic findings attributed to controlled processes in priming can be achieved, including their dependency on stimulus onset asynchrony and relatedness proportion and their unique effect on associative, category‐exemplar, mediated and backward prime‐target relations. We discuss how our mechanism relates to the classic expectancy theory and how it can be further extended in future developments of the model.     

Accounting for Graded Performance within a Discrete Search Framework

This article presents a process account of some typicality effects and related similarity-dependent accuracy and response time phenomena that arise in the context of supervised concept acquisition. We describe Symbolic Concept Acquisition (SCA), a computational system that acquires and activates category prediction rules. In contrast to gradient representations, SCA performs by probing for prediction rules in a series of discrete steps. For learning new rules, it acquires general rules but then incrementally learns more specific ones. In describing SCA, we emphasize its functionality in terms of accuracy and efficiency and motivate its design within the set of symbolic mechanisms and memory structures defined by the Soar architecture (Laird, Newell & Rosenbloom, 1987). For replicating human behavior, we first show how SCA exhibits some typicality effects in the course of learning responding faster and more accurately to more typical test examples. Then, using data from human experiments, we evaluate SCA's qualitative predictions on accuracy and response time on individual dataset instances. We show how SCA's predictions correlate with human data across three experimental conditions concerning the effect of instruction on learning strategy.     

Making Sense of Groups,Computers, and Mathematics

In this article, we report the findings of research that was designed to identify factors associated with learning mathematics in groups with computers. The study was influenced by different theoretical perspectives on social interaction and learning mathematics, and we describe how we attempted to integrate these approaches into the research design. To cope with complex data based on eight groups of six students (aged 9-12 years), we developed a methodology that involved moving between quantitative and qualitative approaches in an iterative spiral. In this article, we focus on the patterns of learning associated with two group tasks incorporating the use of Logo. Quantitative analysis of learning measures indicated positive learning gains as a result of the groupwork, with no differences across gender or ability; qualitative and quantitative analysis of process factors pointed to explanations for the differing profiles of success across groups. Although balanced coconstruction at the computer, coupled with the coordination of others' perspectives, was most advantageous for learning conceptually based mathematics, this was not the case with "technology-driven" mathematics, where fragmentation and concentrated work at the computer proved to be more efficient. These findings suggest that detailed specification of the learning goal is crucial when evaluating groupwork within educational settings.     

A bias to detail: how hand position modulates visual learning and visual memory

In this report, we examine whether and how altered aspects of perception and attention near the hands affect one’s learning of to-be-remembered visual material. We employed the contextual cuing paradigm of visual learning in two experiments. Participants searched for a target embedded within images of fractals and other complex geometrical patterns while either holding their hands near to or far from the stimuli. When visual features and structural patterns remained constant across to-be-learned images (Exp. 1), no difference emerged between hand postures in the observed rates of learning. However, when to-be-learned scenes maintained structural pattern information but changed in color (Exp. 2), participants exhibited substantially slower rates of learning when holding their hands near the material. This finding shows that learning near the hands is impaired in situations in which common information must be abstracted from visually unique images, suggesting a bias toward detail-oriented processing near the hands.     

Using an AI creativity system to explore how aesthetic experiences are processed along the brain’s perceptual neural pathways

With the increased sophistication of AI techniques, the application of these systems has been expanding to ever newer fields. Increasingly, these systems are being used in modeling of human aesthetics and creativity, e.g. how humans create artworks and design products. Our lab has developed one such AI creativity deep learning system that can be used to create artworks in the form of images and videos. In this paper, we describe this system and its use in studying the human visual system and the formation of aesthetic experiences. Specifically, we show how time-based AI created media can be used to explore the nature of the dual-pathway neuro-architecture of the human visual system and how this relates to higher cognitive judgments such as aesthetic experiences that rely on these divergent information streams. We propose a theoretical framework for how the movement within percepts such as video clips, causes the engagement of reflexive attention and a subsequent focus on visual information that are primarily processed via the dorsal stream, thereby modulating aesthetic experiences that rely on information relayed via the ventral stream. We outline our recent study in support of our proposed framework, which serves as the first study that investigates the relationship between the two visual streams and aesthetic experiences.     

Photo-Elicitation Interviews with Vulnerable Populations: Practical and Ethical Considerations

Photo-elicitation is a qualitative interview technique where researchers solicit responses, reactions, and insights from participants by using photographs or other images as stimuli. Images can be researcher-generated or participant-generated and each has particular benefits and challenges. Though not new, the use of images within criminology is an underused technique. In this paper we advocate the use of photo-elicitation techniques suggesting that they offer a powerful addition to standard data collection and presentation techniques. In making our case, we draw on our experiences from an 18-month long photo-ethnography of people living in rural Alabama who use methamphetamine. The ethnography consisted of formal interviews and informal observations with 52 participants and photography of 29 of them. While we draw on our overall experiences from the project we focus specifically on the photographs generated by, and taken of, one key participant—Alice. We demonstrate the benefits and challenges of using photo elicitation interviews with vulnerable individuals such as Alice, by considering themes such as representation, empowerment and emotionality. Additionally, we highlight the practical and ethical issues that confront researchers who incorporate the visual into their research.     

Rethinking Collaborative Learning Through Participation in an Interdisciplinary Research Project: Tensions and Negotiations as Key Points in Knowledge Production

As social and cultural psychologists of learning, we are persuaded of the crucial role of interaction in development and learning. But how do we experience this assumption in our own research practices and in our collaboration with colleagues? Taking as our object of study our own participation in a European Research and Development project that aimed to enhance interactive and argumentative skills in learning settings, this study shows how collaboration among project partners is not something that is to be taken for granted, but something that is elaborated and evolves in time, takes diverse forms, and is mediated by multiple tools. The psychological processes—more particularly tensions and negotiation—involved in collaboration are developed and discussed. The study explores the processes of establishing collaboration and, through the analysis of specific zones of tensions, sheds light on the way new knowledge (on how to do research, how to communicate, how to work together) is constructed. It contributes to the understanding of the issues and conditions for the development of a community of practice.     

The origins of vocal learning: New sounds, new circuits, new cells

We do not know how vocal learning came to be, but it is such a salient trait in human evolution that many have tried to imagine it. In primates this is difficult because we are the only species known to possess this skill. Songbirds provide a richer and independent set of data. I use comparative data and ask broad questions: How does vocal learning emerge during ontogeny? In what contexts? What are its benefits? How did it evolve from unlearned vocal signals? How was brain anatomy altered to enable vocal learning? What is the relation of vocal learning to adult neurogenesis? No one has described yet a circuit or set of circuits that can master vocal learning, but this knowledge may soon be within reach. Moreover, as we uncover how birds encode their learned song, we may also come closer to understanding how we encode our thoughts.     

Event-related potentials reveal the development of stable face representations from natural variability

Natural variability between instances of unfamiliar faces can make it difficult to reconcile two images as the same person. Yet for familiar faces, effortless recognition occurs even with considerable variability between images. To explore how stable face representations develop, we employed incidental learning in the form of a face sorting task. In each trial, multiple images of two facial identities were sorted into two corresponding piles. Following the sort, participants showed evidence of having learnt the faces performing more accurately on a matching task with seen than with unseen identities. Furthermore, ventral temporal event-related potentials were more negative in the N250 time range for previously seen than for previously unseen identities. These effects appear to demonstrate some degree of abstraction, rather than simple picture learning, as the neurophysiological and behavioural effects were observed with novel images of the previously seen identities. The results provide evidence of the development of facial representations, allowing a window onto natural mechanisms of face learning.     

THE VIEW FROM DOWN HERE

In this article, graduate students and one faculty member respond to the innovative methods presented in this issue. We identify three theoretical and methodological tensions that shape our interest in and willingness to work with these methods. The first questions whether the strengths of doing qualitative research outweigh the limitations. The second involves feminist research ideals and how attainable they are. The third explores epistemological tensions between qualitative and quantitative research. Although intrigued by the data these methods generated and by their underlying epistemology, we question the status of certain qualitative research in psychology. We contend that the criteria by which qualitative research is evaluated must be made more explicitly before quantitatively trained researchers will incorporate these methods into their own work.     

Philosophy and language learning

In this paper, I explore different ways of picturing language learning in philosophy, all of them inspired by Wittgenstein and all of them concerned about scepticism of meaning. I start by outlining the two pictures of children and language learning that emerge from Kripke’s famous reading of Wittgenstein. Next, I explore how social-pragmatic readings, represented by Meredith Williams, attempt to answer the sceptical anxieties. Finally, drawing somewhat on Stanley Cavell, I try to resolve these issues by investigating what characteristically happens to our view of language learning when we do philosophy. The focus throughout is on the relation between the individual (the learning child) and the community (usually represented by the parents), and how that relation is deformed when we operate with a certain philosophical notion of ground.     

THE PHYLOGENY AND ONTOGENY OF SERIAL MEMORY:

Abstract— The study of cognitive processes in animals provides a unique opportunity to investigate the phytogeny and ontogeny of cognition, Much of our understanding of human cognition tie-rives from the intensive study of adult human subjects. Serin! learning provides an instructive example. Since Ebhing-haus, experiments on serial learning have been performed almost exclusively on subjects who have had much experience learning lists by virtue oj their formal and informal education. Recent research on serial learning in pigeons and monkeys provides a new perspective on this fundamental skill, which does not require language and which appears to he phylogenetlcally quite old. This research has also revealed qualitative differences in how pigeons and monkeys represent lists they learn to produce and provided opportunities to observe the development of list-learning strategies starting with a subject's first list.     

A visual embedding for the unsupervised extraction of abstract semantics

Vector-space word representations obtained from neural network models have been shown to enable semantic operations based on vector arithmetic. In this paper, we explore the existence of similar information on vector representations of images. For that purpose we define a methodology to obtain large, sparse vector representations of image classes, and generate vectors through the state-of-the-art deep learning architecture GoogLeNet for 20 K images obtained from ImageNet. We first evaluate the resultant vector-space semantics through its correlation with WordNet distances, and find vector distances to be strongly correlated with linguistic semantics. We then explore the location of images within the vector space, finding elements close in WordNet to be clustered together, regardless of significant visual variances (e.g., 118 dog types). More surprisingly, we find that the space unsupervisedly separates complex classes without prior knowledge (e.g., living things). Afterwards, we consider vector arithmetics. Although we are unable to obtain meaningful results on this regard, we discuss the various problem we encountered, and how we consider to solve them. Finally, we discuss the impact of our research for cognitive systems, focusing on the role of the architecture being used.     

Informal Home Education: Philosophical Aspirations put into Practice

Informal home education occurs without much that is generally considered essential for formal education—including curriculum, learning plans, assessments, age related targets or planned and deliberate teaching. Our research into families conducting this kind of education enables us to consider learning away from such imposed structures and to explore how children go about learning for themselves within the context of their own socio-cultural setting. In this paper we consider what and how children learn when no educational agenda is arranged for them and we link this manner of learning to the Deweyan ideas of learning as transactional and learning-in-context. We also use our empirical evidence to explore the notion of ZPD with regard to informal learning and to consider how children, without specific guidance, go about charting a course of learning through the ZPD. We consider the quality of informal learning particularly with regard to the educational aim of developing reflective and critical thinking, showing how these are integral to informal learning. We suggest that a much wider conception of what learning is and how it happens is needed, away from the confines of formal educational structures.     

Individual differences in metacontrast masking: A call for caution when interpreting group data

In this issue of Consciousness and Cognition, Bachmann (2010) comments on our study (Albrecht, Klapötke, & Mattler, 2010), which revealed two groups of observers with qualitative individual differences in metacontrast masking that are enhanced by perceptual learning. We are pleased that our study receives this attention and even more about Bachmann’s extremely positive comments. In this invited reply we argue that observers seem to be similar only at the beginning of the experiment but they have no choice as to which group to join. Findings strongly recommend to look at the data of individual subjects.     

What Can the Systems Community Contribute to Ensure the Survival of Civilization

Much of what we need to plan for our survival is already known, but what we know, how we know, and who knows is divided up between disciplines. Thus much of the problem of ensuring our survival is a matter of learning across the disciplines. We identify four modes through which we bring disciplinary knowledge together: the unity of science, integrated assessment, heuristic models, and distributed learning networks. Although none of them are perfect, we can learn how to put our knowledge together across the disciplines much better than we do.     

Seeing the Whole Picture

Much of what we need to plan for our survival is already known, but what we know, how we know, and who knows is divided up between disciplines. Thus much of the problem of ensuring our survival is a matter of learning across the disciplines. We identify four modes through which we bring disciplinary knowledge together: the unity of science, integrated assessment, heuristic models, and distributed learning networks. Although none of them are perfect, we can learn how to put our knowledge together across the disciplines much better than we do.