Constructing theoretically informed measures of pause duration in experimentally manipulated writing

Abstract

This paper argues that traditional threshold-based approaches to the analysis of pauses in writing fail to capture the complexity of the cognitive processes involved in text production. It proposes that, to capture these processes, pause analysis should focus on the transition times between linearly produced units of text. Following a review of some of the problematic features of traditional pause analysis, the paper is divided into two sections. These are designed to demonstrate: (i) how to isolate relevant transitions within a text and calculate their durations; and (ii) the use of mixture modelling to identify structure within the distributions of pauses at different locations. The paper uses a set of keystroke logs collected from 32 university students writing argumentative texts about current affairs topics to demonstrate these methods. In the first section, it defines how pauses are calculated using a reproducible framework, explains the distinction between linear and non-linear text transitions, and explains how relevant sections of text are identified. It provides Excel scripts for automatically identifying relevant pauses and calculating their duration. The second section applies mixture modelling to linear transitions at sentence, sub sentence, between-word and within-word boundaries for each participant. It concludes that these transitions cannot be characterised by a single distribution of “cognitive” pauses. It proposes, further, that transitions between words should be characterised by a three-component distribution reflecting lexical, supra-lexical and reflective processes, while transitions at other text locations can be modelled by two-component distributions distinguishing between fluent and less fluent or more reflective processing. The paper concludes by recommending that, rather than imposing fixed thresholds to distinguish processes, researchers should instead impose a common set of theoretically informed distributions on the data and estimate how the parameters of these distributions vary for different individuals and under different conditions.

Revision of Business Content on Corporate Social Responsibility

“…At the high level, keystroke logging has been used to understand the cognitive processesincluding mental effortinvolved in writing and revision. The analysis of pauses is especially central in most keystroke logging studies (see Hall et al (2022) for an overview). Pauses (namely interruptions in the flow of typing that can be recorded by keystroke logging tools) have been linked with effortful processes.…”