As humans, we use language with ease and speed, solving the complex computational problem of processing form and meaning seemingly without effort. This dissertation studies how the properties of language enable us to achieve this, by investigating what is computationally difficult about language, and what is easy. We first investigate the…

Automated Essay Scoring (AES) using neural networks has helped increase the accuracy and efficiency of scoring students' written tasks. Generally, the improved accuracy of neural network approaches has been attributed to the use of modern word embedding techniques. However, which word embedding techniques produce higher accuracy in AES systems…

Aim/Purpose: This paper examines the potential of ChatGPT-assisted retrieval practice to enhance students' final exam performance. ChatGPT was utilized to generate questions and deliver timely feedback during retrieval practice, supporting learning in large class settings where providing personalized feedback is often challenging. Background:…

Ambridge calls for exemplar-based accounts of language acquisition. Do modern neural networks such as transformers or word2vec -- which have been extremely successful in modern natural language processing (NLP) applications -- count? Although these models often have ample parametric complexity to store exemplars from their training data, they also…

In 'Against Stored Abstractions,' Ambridge uses neural and computational evidence to make his case against abstract representations. He argues that storing only exemplars is more parsimonious -- why bother with abstraction when exemplar models with on-the-fly calculation can do everything abstracting models can and more -- and implies that his…

Students' school requirements and learning activities engage many different cognitive processes, including language processing, memory, learning, attention, reasoning, decision-making, and social interaction. However, students rarely learn about these cognitive processes, or the brain mechanisms underlying them and therefore lack the critical…

Purpose: Explore how different automated scoring (AS) models score reliably the expressive language and vocabulary knowledge in depth of young second grade Latino English learners. Design/methodology/approach: Analyze a total of 13,471 English utterances from 217 Latino English learners with random forest, end-to-end memory networks, long…

We have developed a process model that learns in multiple ways while finding faults in a simple control panel device. The model predicts human participants' learning through its own learning. The model's performance was systematically compared to human learning data, including the time course and specific sequence of learned behaviors. These…

As an alternative to dominant cognitive-constructivist approaches to educational technology, this article makes the case for what has been termed a discursive, or postcognitive, psychological research paradigm. It does so by adapting discursive psychological analyses of conversational activity to the study of educational technology use. It applies…

"The Handbook of Latent Semantic Analysis" is the authoritative reference for the theory behind Latent Semantic Analysis (LSA), a burgeoning mathematical method used to analyze how words make meaning, with the desired outcome to program machines to understand human commands via natural language rather than strict programming protocols.…

Presents a computer simulation testing semantic networks and spreading activation models of human memory. Describes how a sentence is encoded by building a working memory structure from its words and from semantic memory concepts related to its meaning. Retrieval processes use cue words or sentences to locate working memory structures. (Author/MES)

The principal recent models of semantics, conceptual, and lexical memory are explicated and criticized. A description of long-term is developed in terms of these models. (Text is in French.) (DB)

The 34 summaries contained in this collection represent the theoretical positions and the empirical studies of a wide variety of investigators currently working in the field of language comprehension. The entries summarize contributions from the areas of assessment, artificial intelligence, cognition (including schema theory), instruction,…