The creation of a process model is primarily a formalization task that faces the challenge of constructing a syntactically correct entity, which accurately reflects the semantics of reality, and is understandable to the model reader. This article proposes a framework called "Model Judge," focused toward the two main actors in the process…

The automatic evaluation of text-based assessment items, such as short answers or essays, is an open and important research challenge. In this paper, we compare several features for the classification of short open-ended responses to questions related to a large first-year health sciences course. These features include a) traditional n-gram…

Language proficiency diagnosis is essential to extract fine-grained information about the linguistic knowledge states and skill mastery levels of test takers based on their performance on language tests. Different from comprehensive standardized tests, many language learning apps often revolve around word-level questions. Therefore, knowledge…

The trans-contextual model (TCM) offers a heuristic-based theoretical framework to understand fifth-grade Danish schoolchildren's motivation to participate in the 11 for Health in Denmark educational football concept, as well as their intention and behaviour to participate in vigorous physical activity (PA) in a leisure-time context. The…

Chinese coordinative compound words are common and unique in inter-character semantic and orthographic relationships. This study explored the inter-character orthographic similarity effects on the recognition of transparent two-morpheme coordinative compound words. Seventy-two native Chinese readers participated in a lexical decision task. The…

Two broad approaches characterize the type of evidence that mediates recognition memory: discrete state and continuous. Discrete-state models posit a thresholded memory process that provides accurate information about an item (it is detected) or, failing that, no mnemonic information about the item. Continuous models, in contrast, posit the…

The collection of very large text sources has revolutionized the study of natural language, leading to the development of several models of language learning and distributional semantics that extract sophisticated semantic representations of words based on the statistical redundancies contained within natural language (e.g., Griffiths, Steyvers,…

Comprehension substantially benefits from attending to, thinking about, and mentally representing the sources of any presented information. Such processes require mental effort and unfortunately people do not always engage in such activities. The current article presents a nascent, evolving model of discourse comprehension that formalizes…

Diversity of vocabulary knowledge and quantity of language exposure prior to literacy are key predictors of reading development. However, diversity and quantity of exposure are difficult to distinguish in behavioural studies, and so the causal relations with literacy are not well known. We tested these relations by training a connectionist…

The evaluation of text complexity is an important topic in education. While this objective has been addressed by approaches using lexical and syntactic analysis for decades, semantic complexity is less common, and the recent research works that tackle this question rely on machine learning algorithms that are hardly explainable and are not…

By the time they reach early adulthood, English speakers are familiar with the meaning of thousands of words. In the last decades, computational simulations known as distributional semantic models (DSMs) have demonstrated that it is possible to induce word meaning representations solely from word co-occurrence statistics extracted from a large…

This review examines and integrates studies of second language (L2) vocabulary instruction with adult learners in a laboratory setting, using a framework provided by a modified version of the Revised Hierarchical Model (Kroll & Stewart, 1994), the Revised Hierarchical Model-Repetition Elaboration Retrieval. By examining how various training…

To account for natural variability in cognitive processing, it is standard practice to optimize a model's parameters by fitting it to behavioral data. Although most language-related theories acknowledge a large role for experience in language processing, variability reflecting that knowledge is usually ignored when evaluating a model's fit to…

Open-ended comprehension questions are a common type of assessment used to evaluate how well students understand one of multiple documents. Our aim is to use natural language processing (NLP) to infer the level and type of inferencing within readers' answers to comprehension questions using linguistic and semantic features within their responses.…

The statistical structure of a given language likely drives our sensitivity to words' morphological structure. The current work begins to investigate to what degree morphological processing effects observed in visual word recognition can be attributed to statistical regularities between orthography and semantics in English, without any prior…