Investigating Properties of Phonotactic Knowledge Through Web-Based Experimentation

The goal of this dissertation is to advance the state of the art of research in constraint-based phonotactics. It takes a two-pronged approach: a technological contribution intended to facilitate future research, and experiments which seek to shed light on high-level questions about the properties of phonotactic models that can guide the development of theoretical work. The technological contribution is a software package called Speriment which allows experimenters to create and run experiments over the internet without advanced programming techniques. This software is particularly well suited to the kinds of experiments often run in phonotactic research, but can also be used for experiments in other domains of linguistics and the social sciences. It is hoped that this software will make it faster and easier to conduct phonotactic and other experiments as well as encourage experimenters to increase the reproducibility and transparency of their research. The experiments presented here address questions that assume constraint-based phonotactic frameworks, but that do not rely on particular theories of the content of the constraint set. That is, they apply to constraint-based frameworks for theories of phonotactics, with the first study seeking to distinguish between two such frameworks, a linear version of Harmonic Grammar and Maximum Entropy, while the second investigates whether phonotactic knowledge is independent of knowledge of phonological alternations. These coarse-grained questions about phonotactic knowledge on how pieces of phonotactic knowledge interact with each other and with another part of the grammar are intended to add to the groundwork on which phonotactic models and models of all phonological knowledge are built. Their findings have implications for which constraint-based frameworks should be used for future theories and how these theories can be reliably tested

Use or Consequences: Probing the Cognitive Difference Between Two Measures of Divergent Thinking

Recent studies have highlighted both similarities and differences between the cognitive processing that underpins memory retrieval and that which underpins creative thinking. To date, studies have focused more heavily on the Alternative Uses task, but fewer studies have investigated the processing underpinning other idea generation tasks. This study examines both Alternative Uses and Consequences idea generation with a methods pulled from cognitive psychology, and a novel method for evaluating the creativity of such responses. Participants were recruited from Amazon Mechanical Turk using a custom interface allowing for requisite experimental control. Results showed that both Alternative Uses and Consequences generation are well approximated by an exponential cumulative response time model, consistent with studies of memory retrieval. Participants were also slower to generate their first consequence compared with first responses to Alternative Uses, but inter-response time was negatively related to pairwise similarity on both tasks. Finally, the serial order effect is exhibited for both tasks, with Consequences earning more creative evaluations than Uses. The results have implications for burgeoning neuroscience research on creative thinking, and suggestions are made for future areas of inquiry. In addition, the experimental apparatus described provides an equitable way for researchers to obtain good quality cognitive data for divergent thinking tasks

Experimenting with online governance

To solve the problems they face, online communities adopt comprehensive governance methods including committees, boards, juries, and even more complex institutional logics. Helping these kinds of communities succeed will require categorizing best practices and creating toolboxes that fit the needs of specific communities. Beyond such applied uses, there is also a potential for an institutional logic itself to evolve, taking advantage of feedback provided by the fast pace and large ecosystem of online communication. Here, we outline an experimental strategy aiming at guiding and facilitating such an evolution. We first review the advantages of studying collective action using recent technologies for efficiently orchestrating massive online experiments. Research in this vein includes attempts to understand how behavior spreads, how cooperation evolves, and how the wisdom of the crowd can be improved. We then present the potential usefulness of developing virtual-world experiments with governance for improving the utility of social feedback. Such experiments can be used for improving community rating systems and monitoring (dashboard) systems. Finally, we present a framework for constructing large-scale experiments entirely in virtual worlds, aimed at capturing the complexity of governance dynamics, to empirically test outcomes of manipulating institutional logic.Received: 14 November 2020; Accepted: 23 March 2021; Published: 26 April 2021

Correction Without Consciousness in Complex Tasks: Evidence from Typing

Published: 07 January 2022It has been demonstrated that with practice, complex tasks can become independent of conscious control, but even in those cases, repairing errors is thought to remain dependent on conscious control. This paper reports two studies probing conscious awareness over repairs in nearly 15,000 typing errors collected from 145 participants in a single-word typing-to-dictation task. We provide evidence for subconscious repairs by ruling out alternative accounts, and report two sets of analyses showing that a) such repairs are not confined to a specific stage of processing and b) that they are sensitive to the final outcome of repair. A third set of analyses provides a detailed comparison of the timeline of trials with conscious and subconscious repairs, revealing that the difference is confined to the repair process itself. We propose an account of repair processing that accommodates these empirical findings.This project was supported by the Therapeutic Cognitive Neurology Fund to Johns Hopkins School of Medicine, Department of Neurology, Division of Cognitive Neurology