In this study, we developed a classification system of programming errors based on the historical data of 680,540 programming records collected on the Online Judge platform. The classification system described six types of programming errors (i.e., syntax, logical, type, writing, misunderstanding, and runtime errors) and their connections with…

Purpose: ParAlg (Paraphasia Algorithms) is a software that automatically categorizes a person with aphasia's naming error (paraphasia) in relation to its intended target on a picture-naming test. These classifications (based on lexicality as well as semantic, phonological, and morphological similarity to the target) are important for…

This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…

There is a general consensus in theories of human speech recognition that humans engage in predictive processing during online speech processing. There are also claims that predictive processing indicates the operation of a predictive coding (PC) mechanism (Rao & Ballard, 1999). Formally, PC is a generative model where top-down signals consist…

We present two empirical studies with 241 and 211 pre-service teachers that evaluate the explanatory power of word order matching and static comparison as models for the reversal error. We used tasks consisting of generating an algebraic equation representing a comparison given in a verbal statement. We introduce the types of magnitude involved in…

We present computational modeling results based on a self-paced reading study investigating number attraction effects in Eastern Armenian. We implement three novel computational models of agreement attraction in a Bayesian framework and compare their predictive fit to the data using k-fold cross-validation. We find that our data are better…

Age of acquisition (AoA) is a measure of word complexity which refers to the age at which a word is typically learned. AoA measures have shown strong correlations with reading comprehension, lexical decision times, and writing quality. AoA scores based on both adult and child data have limitations that allow for error in measurement, and increase…

Most current models of sentence comprehension assume that the human parsing mechanism (HPM) algorithmically computes detailed syntactic representations as basis for extracting sentence meaning. These models share the assumption that the representations computed by the HPM accurately reflect the linguistic input. This assumption has been challenged…

Henson (1996) provided a number of demonstrations of error patterns in serial recall that contradict chaining models. Chaining models predict that when participants erroneously recall an item too early, recall should proceed from the point of error. In contradiction to such a prediction, Henson found evidence for a fill-in effect: participants…

Automatic essay scoring (AES) refers to the process of scoring free text responses to given prompts, considering human grader scores as the gold standard. Writing such essays is an essential component of many language and aptitude exams. Hence, AES became an active and established area of research, and there are many proprietary systems used in…

The time required to determine the larger of 2 digits decreases with their numerical distance, and, for a given distance, increases with their magnitude (Moyer & Landauer, 1967). One detailed quantitative framework to account for these effects is provided by random walk models. These chronometric models describe how number-related noisy…

The processing of morphological information during Chinese word memorization was investigated in the present study. Participants were asked to study words presented to them on a computer screen in the studying phase and then judge whether presented words were old or new in the test phase. In addition to parent words (i.e. the words studied in the…

Novel phonotactic constraints can be acquired by hearing or speaking syllables that follow a novel constraint. When learned from hearing syllables, these newly learned constraints generalize to syllables that were not experienced during training. However, generalization of phonotactic learning to novel syllables has never been persuasively…

Modeling student knowledge is a fundamental task of an intelligent tutoring system. A popular approach for modeling the acquisition of knowledge is Bayesian Knowledge Tracing (BKT). Various extensions to the original BKT model have been proposed, among them two novel models that unify BKT and Item Response Theory (IRT). Latent Factor Knowledge…

Analyzing examinees' responses using cognitive diagnostic models (CDMs) has the advantage of providing diagnostic information. To ensure the validity of the results from these models, differential item functioning (DIF) in CDMs needs to be investigated. In this article, the Wald test is proposed to examine DIF in the context of CDMs. This study…