Work

Analysis and machine learning adaptation of a cognitive model for human memory

Year: 2026

Type: article

Abstract: In this paper, we use the Duolingo SLAM dataset to analyze several cognitive models of second language acquisition and develop new approaches for enhanced performance. In particular, we consider the Predictive Performance Equation and some of its underlying power laws. Leveraging insights from machine learning, we develop simple one-feature models as building blocks for combined models that match or in certain cases outperform the existing models at much reduced computational cost. In addition, a neural network with one fully connected hidden layer is constructed that outperforms all other models on sufficiently large datasets.

Source: Results in Applied Mathematics

DOI: 10.1016/j.rinam.2026.100730

Authors: Trevor Cross, Aihua W. Wood

Institutions: Wright-Patterson Air Force Base, U.S. Air Force Institute of Technology

Language: English

Topic: Second Language Acquisition and Learning

Subfield: Developmental and Educational Psychology

Field: Psychology

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $1,770

OpenAlex ID: W7165125243

FWCI:

Cites: 10

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