The majority of research in computational psycholinguistics on sentence processing has focused on word-by-word incremental processing within sentences, rather than holistic sentence-level representations. This study introduces two novel computational approaches for quantifying sentence-level processing: sentence surprisal and sentence relevance.…

This case study examines employee attrition, its detrimental effects on businesses, and the potential of data analytics to address this challenge. By employing Latent Dirichlet Allocation (LDA), a sophisticated NLP technique, we delve into the underlying reasons for employee departures. Additionally, we explore using RapidMiner to develop…

Numerous developmental findings suggest that infants and toddlers engage predictive processing during language comprehension. However, a significant limitation of this research is that associative (bottom-up) and predictive (top-down) explanations are not readily differentiated. Following adult studies that varied predictiveness relative to…

A significant body of recent research in the field of Learning Analytics has focused on leveraging machine learning approaches for predicting at-risk students in order to initiate timely interventions and thereby elevate retention and completion rates. The overarching feature of the majority of these research studies has been on the science of…

Prediction-based accounts of language acquisition have the potential to explain several different effects in child language acquisition and adult language processing. However, evidence regarding the developmental predictions of such accounts is mixed. Here, we consider several predictions of these accounts in two large-scale developmental studies…

Recent investigations on how people derive meaning from language have focused on task-dependent shifts between two cognitive systems. The symbolic (amodal) system represents meaning as the statistical relationships between words. The embodied (modal) system represents meaning through neurocognitive simulation of perceptual or sensorimotor systems…

Designing and constructing pedagogical tests that contain items (i.e. questions) which measure various types of skills for different levels of students equitably is a challenging task. Teachers and item writers alike need to ensure that the quality of assessment materials is consistent, if student evaluations are to be objective and effective.…

Prediction error plays a pivotal role in theories of learning, including theories of language acquisition and use. Researchers have investigated whether and under which conditions children, like adults, use prediction to facilitate language comprehension at different levels of linguistic representation. However, many aspects of the reciprocal…

Purpose: Children with congenital hearing loss (HL) have auditory impairments that may place them at increased risk for delays or variability in language development. However, obtaining reliable brain markers for early classification of young children with HL versus those with normal hearing (NH), as well as for precise assessment of HL children's…

Meaning in language emerges from multiple words, and children are sensitive to multi-word frequency from infancy. While children successfully use cues from single words to generate linguistic predictions, it is less clear whether and how they use multi-word sequences to guide real-time language processing and whether they form predictions on the…

Some theories of sentence processing make a distinction between two kinds of meaning: a linguistic meaning encoded at the lexicon (i.e., selectional restrictions), and an extralinguistic knowledge derived from our everyday experiences (i.e., world knowledge). According to such theories, the former meaning is privileged over the latter in terms of…

There is currently much interest in the role of prediction in language processing, both in L1 and L2. For language acquisition researchers, this has prompted debate on the role that predictive processing may play in both L1 and L2 language learning, if any. In this conceptual review, we explore the role of prediction and prediction error as a…

Linguistic phenomena (e.g., words and syntactic structure) co-occur with a wide variety of meanings. These systematic correlations can help readers to interpret a text and create predictions about upcoming material. However, to what extent these correlations influence discourse processing is still unknown. We address this question by examining…

Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…

One of the basic tenets of predictive theories of language processing is that of misprediction cost. Post-N400 positive event-related potential (ERP) components are suitable for studying misprediction cost but are not adequately described, especially in older adults, who show attenuated N400 ERP effects. We report a secondary analysis of a…