In automated essay scoring (AES), essays are automatically graded without human raters. Many AES models based on various manually designed features or various architectures of deep neural networks (DNNs) have been proposed over the past few decades. Each AES model has unique advantages and characteristics. Therefore, rather than using a single-AES…

Automated Essay Scoring (AES) technologies provide innovative solutions to score the written essays with a much shorter time span and at a fraction of the current cost. Traditionally, AES emphasized the importance of capturing the "coherence" of writing because abundant evidence indicated the connection between coherence and the overall…

Thurstonian forced-choice modeling is considered to be a powerful new tool to estimate item and person parameters while simultaneously testing the model fit. This assessment approach is associated with the aim of reducing faking and other response tendencies that plague traditional self-report trait assessments. As a result of major recent…

The effectiveness of feedback in enhancing learning outcomes is well documented within Educational Data Mining (EDM). Various prior research have explored methodologies to enhance the effectiveness of feedback to students in various ways. Recent developments in Large Language Models (LLMs) have extended their utility in enhancing automated…

Argumentation is fundamental to science education, both as a prominent feature of scientific reasoning and as an effective mode of learning--a perspective reflected in contemporary frameworks and standards. The successful implementation of argumentation in school science, however, requires a paradigm shift in science assessment from the…

In automated essay scoring (AES), scores are automatically assigned to essays as an alternative to grading by humans. Traditional AES typically relies on handcrafted features, whereas recent studies have proposed AES models based on deep neural networks to obviate the need for feature engineering. Those AES models generally require training on a…

The Big Data for Education Spoke of the NSF Northeast Big Data Innovation Hub and ETS co-sponsored an educational data mining competition in which contestants were asked to predict efficient time use on the NAEP 8th grade mathematics computer-based assessment, based on the log file of a student's actions on a prior portion of the assessment. In…

Background: Validity is a notable concept in language testing which has concerned many researchers and scholars in the field of language testing due to its importance in decision making process. Tests' results always introduce consequences to test takers' lives which emphasizes the need to ensure their validity. Detecting and delineating the…

Teachers are thrown open to abundance of free text answers which are very daunting to read and evaluate. Automatic assessments of open ended answers have been attempted in the past but none guarantees 100% accuracy. In order to deal with the overload involved in this manual evaluation, a new tool becomes necessary. The unique superlative model…

In general, newer educational assessments are deemed more demanding challenges than students are currently prepared to face. Two types of factors may contribute to the test scores: (1) factors or dimensions that are of primary interest to the construct or test domain; and, (2) factors or dimensions that are irrelevant to the construct, causing…

Purpose: The purpose of this paper is to focus on assessing individuals' problems in learning groups/teams and should lead to the assessment of the group/team itself as a learning entity. Design/methodology/approach: In this paper, an extension of the IMS-Learning Design (IMS-LD) meta-model is proposed in order to support the assessment of…

The heightened importance of foreign languages (L2) in the post 9-11 world demands more L2 listening research as listening is considered the most critical skill for most American military linguists. Some larger studies show that lexical knowledge can positively affect L2 listening (Chang, 2007; Mehrpour & Rahimi, 2010; Staehr, 2009), yet…

Despite calls for engaging assessments targeting young language learners (YLLs) between 8 and 13 years old, what makes assessment tasks engaging and how such task characteristics affect measurement quality have not been well studied empirically. Furthermore, there has been a dearth of validity research about technology-enhanced speaking tests for…

Science standards have been a topic in educational research in Austria for about ten years now. Starting in 2005, competency structure models have been developed for junior and senior classes of different school types. After evaluating these models, prototypic tasks were created to point out the meaning of the models to teachers. At the moment,…

The present study examines the relative importance of attributes within and across items by applying four cognitive diagnostic assessment models. The current study utilizes the function of the models that can indicate inter-attribute relationships that reflect the response behaviors of examinees to analyze scored test-taker responses to four forms…