Chapter 16 - Eye Movement Measures to Study Global Text Processing
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This chapter describes the applicability of the eye-tracking method in studying global text processing. Eye tracking is used to study basic reading processes and syntactic parsing, but there are few studies where eye tracking is employed to examine global text processing. As one moves from the study of lexical processing to syntactic processing, the potential units of analysis increase in both number and size. There are four relevant levels of processing in the study of syntactic processing: (1) the word at which a parsing choice is expected to be made or a syntactic ambiguity to reveal itself, (2) the phrase, (3) the clause, and (4) the whole sentence. Related to the increase in the number and size of potentially interesting units of analysis, the mental processing associated with syntactic processes is more complex and varied than the mental processing associated with lexical processing. Thus, syntactic effects on eye movements are correspondingly more complex than lexical effects on eye movements.
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An interpretable English reading proficiency detection model in an online learning environment: A study based on eye movement
2024, Learning and Individual DifferencesAiming at the low English reading proficiency of ESL (English as second language) students in online learning environments, this study proposed an eye-movement-based machine learning monitoring model to detect English reading proficiency in real time. Eye-movement data from 43 students while completing online English reading tasks were recorded and 31 eye-movement features were extracted from the taxonomy of fixation, saccade, movement direction and gaze velocity. During the model training phase, LightGBM achieved an accuracy of 96.51 % in detection. An interpretable model, SHAP (SHapley Additive exPlanation), was used to explain the main effects of eye-movement features in detection, where high gaze velocity, absolute saccade direction, and average saccade duration were found to be strong indicators of English reading proficiency. Furthermore, SHAP analysis allows the identification of individual factors contributing to differences in English reading proficiency. This study demonstrated the effectiveness of the combination of eye-movement data with machine learning methods to identify students with low English reading proficiency in online reading and provided insights into the intrinsic correlation between eye movements and reading.
Liversedge, Drieghe, Li, Yan, Bai and Hyönä (2016) reported an eye movement study that investigated reading in Chinese, Finnish and English (languages with markedly different orthographic characteristics). Analyses of the eye movement records showed robust differences in fine grained characteristics of eye movements between languages, however, overall sentence reading times did not differ. Liversedge et al. interpreted the entire set of results across languages as reflecting universal aspects of processing in reading. However, the study has been criticized as being statistically underpowered (Brysbaert, 2019) given that only 19–21 subjects were tested in each language. Also, given current best practice, the original statistical analyses can be considered to be somewhat weak (e.g., no inclusion of random slopes and no formal comparison of performance between the three languages). Finally, the original study did not include any formal statistical model to assess effects across all three languages simultaneously. To address these (and some other) concerns, we tested at least 80 new subjects in each language and conducted formal statistical modeling of our data across all three languages. To do this, we included an index that captured variability in visual complexity in each language. Unlike the original findings, the new analyses showed shorter total sentence reading times for Chinese relative to Finnish and English readers. The other main findings reported in the original study were consistent. We suggest that the faster reading times for Chinese subjects occurred due to cultural changes that have taken place in the decade or so that lapsed between when the original and current subjects were tested. We maintain our view that the results can be taken to reflect universality in aspects of reading and we evaluate the claims regarding a lack of statistical power that were levelled against the original article.
The influence of methods of selecting concepts of an expository text on different reading representations' predictive ability
2023, Acta PsychologicaIn this study, we compared two experimental methods of selecting terms in expository text to generate reading representations and tested how well these reading representations predicted reading comprehension. The two experimental methods were the traditional method of using all terms (all keywords) to create participants' representation networks, and the terms categorization (TC) method of using only important terms (core and branch words). Representation networks were assessed using participants' adjacency scores, ratings of relatedness in pairs of terms, and using summary (summary writing) by all turms. An in-subject design was performed in experiments 1 and 2, and an inter-subject design was performed in experiment 3 to test the hypothesis. With the same sample in exp1 and epx2, a different sample in each exp3. Experiment 1 showed that when using only the traditional way of selecting terms, adjacency was better than relatedness in predicting reading comprehension. Reading representations generated based on the summary method could not predict participants' reading comprehension ability, so this method was excluded from subsequent studies. Experiment 2 showed that the terms selected in Experiment 1 were stronger predictors of reading comprehension when the word pairs included a core term (central to understanding of full text) or a branch term (key to understanding paragraph), relative to a detail term (not affect the understanding full text). Experiment 3 found that whereas the two methods were equally effective in generating representations measured by adjacency, TC was superior in generating representations measured by relatedness. These conclusions have important implications for future research and application.
Ironic language is challenging for many people to understand, and particularly for children. Comprehending irony is considered a major milestone in children's development, as it requires inferring the intentions of the person who is being ironic. However, the theories of irony comprehension generally do not address developmental changes, and there are limited data on children's processing of verbal irony. In the present pre-registered study, we examined, for the first time, how children process and comprehend written irony in comparison to adults. Seventy participants took part in the study (35 10-year-old children and 35 adults). In the experiment, participants read ironic and literal sentences embedded in story contexts while their eye movements were recorded. They also responded to a text memory question and an inference question after each story, and children's levels of reading skills were measured. Results showed that for both children and adults comprehending written irony was more difficult than for literal texts (the “irony effect”) and was more challenging for children than for adults. Moreover, although children showed longer overall reading times than adults, processing of ironic stories was largely similar between children and adults. One group difference was that for children, more accurate irony comprehension was qualified by faster reading times whereas for adults more accurate irony comprehension involved slower reading times. Interestingly, both age groups were able to adapt to task context and improve their irony processing across trials. These results provide new insights about the costs of irony and development of the ability to overcome them.
The eye-mind of processing written feedback: Unraveling how students read and use feedback for revision
2023, Learning and InstructionThis research aims to promote our understanding of feedback engagement processes in writing tasks using a combination of online and offline measures, including eye-tracking, thinking-aloud, and text-analyses. Study 1 explored how sixteen students read, evaluate, and use feedback for revision. Results revealed three feedback processing strategies: (1) superficial processing (n = 6), which is characterized by reading feedback in a linear way, without critically rereading or revising the text, (2) local processing (n = 6) in which students switched between reading the comments and the commented text, and (3) deep processing (n = 4) in which students integrated the feedback with both commented and uncommented parts of the text and made more substantial revisions. In Study 2, we investigated the local and deep feedback reading strategy in more detail with 41 students using a within-subject design with different types of feedback. Results demonstrated the same strategies among students, but also that the focus of feedback affected students' revision behavior, above and beyond an individual feedback processing strategy. This finding is in line with previous research that emphasized the effects of feedback characteristics on students’ use of feedback. By triangulating various process measures, this research is one of the first that provides empirical evidence for different feedback processing strategies among students. These novel insights in individual feedback engagement processing can be used to extend and refine current theories on how, when, and why feedback works and for whom.
Do easy-to-read adaptations really facilitate sentence processing for adults with a lower level of education? An experimental eye-tracking study
2023, Learning and InstructionThe Easy-to-Read guidelines recommend visual support and lexical simplification to facilitate text processing, but few studies have empirically verified the efficacy of these guidelines. This study examined the influence of these recommendations on sentence processing by examining eye movements at the text- and word-level in adult readers. We tested 30 non-university adults (low education level) and 30 university adults (high education level). The experimental task consisted of 60 sentences. Half were accompanied by an image and half were not, and half contained a low-frequency word and half a high-frequency word. Results showed that visual support and lexical simplification facilitated processing in both groups of adults, and non-university adults were significantly slower than university adults at sentence processing. However, lexical simplification resulted in faster processing in the non-university adults’ group. Conclusions focus on the mechanisms in which both adaptations benefit readers, and practical implications for reading comprehension.