We introduce a short answer scoring engine made up of an ensemble of deep neural networks and a Latent Semantic Analysis-based model to score short constructed responses for a large suite of questions from a national assessment program. We evaluate the performance of the engine and show that the engine achieves above-human-level performance on a…

Technology has paved the way for new modalities in language learning, teaching, and assessment. However, there is still a great deal of work to be done to develop such tools for oral communication, specifically tools that address suprasegmental features in pronunciation instruction. Therefore, this critical literature review examines how…

Purpose: This study builds a new system for automatically assessing learners' speech elicited from an oral discourse completion task (DCT), and evaluates the prediction capability of the system with a view to better understanding factors deemed influential in predicting speaking proficiency scores and the pedagogical implications of the system.…

The test view is on the Duolingo English Test (DET), an alternative online English proficiency test with a machine-driven characteristic. The review covers essential information of the DET such as test purpose, usage, score-mapping with CEFR scale, price, and publisher. Meanwhile, the test usefulness is discussed with focuses on reliability,…

The rating of proficiency tests that use the Inter-agency Roundtable (ILR) and American Council on the Teaching of Foreign Languages (ACTFL) guidelines claims that each major level is based on hierarchal linguistic functions that require mastery of multidimensional traits in such a way that each level subsumes the levels beneath it. These…

Recent advances in machine learning have made automated scoring of learner speech widespread, and yet validation research that provides support for applying automated scoring technology to assessment is still in its infancy. Both the educational measurement and language assessment communities have called for greater transparency in describing…

Despite an emphasis on oral communication in most foreign language classrooms, the resource-intensive nature (i.e. time and manpower) of speaking tests hinder regular oral assessments. A possible solution is the development of a (semi-) automated scoring system. When it is used in conjunction with human raters, the consistency of computers can…

Dynamic Assessment (DA) is proposed as a workable diagnostic tool in second or foreign language context. Compared to traditional non-dynamic testing, DA presents a more comprehensive account of human beings' abilities through addressing both the fully internalized abilities and the abilities that are in the process of being internalized. However,…

We present work in progress on a multimodal dialog system for English language assessment using a modular cloud-based architecture adhering to open industry standards. Among the modules being developed for the system, multiple modules heavily exploit machine learning techniques, including speech recognition, spoken language proficiency rating,…

As a branch of artificial intelligence, automated speech recognition (ASR) technology is increasingly used to detect speech, process it to text, and derive the meaning of natural language for various learning and assessment purposes. ASR inaccuracy may pose serious threats to valid score interpretations and fair score use for all when it is…

This report is the fifth in a series concerning English language proficiency (ELP) assessments for English learners (ELs) in kindergarten through 12th grade in the United States. The series, produced by Educational Testing Service (ETS), is intended to provide theory and evidence-based principles and recommendations for improving next-generation…

This article describes the development and validation of the new CATSS (Computer Adaptive Test of Size and Strength), which measures vocabulary knowledge in four modalities -- productive recall, receptive recall, productive recognition, and receptive recognition. In the first part of the paper we present the assumptions that underlie the test --…

Automated essay scoring (AES) generally computes essay scores as a function of macrofeatures derived from a set of microfeatures extracted from the text using natural language processing (NLP). In the "e-rater"® automated scoring engine, developed at "Educational Testing Service" (ETS) for the automated scoring of essays, each…

This article investigates ways to improve the assessment of English learner students' English language proficiency given the current movement of creating next-generation English language proficiency assessments in the Common Core era. In particular, this article discusses the integration of scaffolding strategies, which are prevalently utilized as…

The purpose of the present study is to assess second language (L2) spoken English using automated scoring techniques. Automated scoring aims to classify a large set of learners' oral performance data into a small number of discrete oral proficiency levels. In automated scoring, objectively measurable features such as the frequencies of lexical and…