Purpose: The aim of this study was to advance the analysis of written language transcripts by validating an automated scoring procedure using an automated open-access tool for calculating morphological complexity (MC) from written transcripts. Method: The MC of words in 146 written responses of students in fifth grade was assessed using two…

The authors describe Monster, PI, which is an app-based, gamified assessment that measures language skills (knowledge of morphology, vocabulary, and syntax) of students in grades 5-8 and provides teachers with interpretable score reports to drive instruction that improves vocabulary, reading, and writing ability. Specifically, the authors describe…

Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…

Purpose: Our aim was to evaluate the psychometric properties of the online administered format of the Test of Narrative Language--Second Edition (TNL-2; Gillam & Pearson, 2017), given the importance of assessing children's narrative ability and considerable absence of psychometric studies of spoken language assessments administered online.…

Artificial Intelligence (AI) based assessments are commonly used in a variety of settings including business, healthcare, policing, manufacturing, and education. In education, AI-based assessments undergird intelligent tutoring systems as well as many tools used to evaluate students and, in turn, guide learning and instruction. This chapter…

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…

The "Framework" and NGSS bring to the forefront the role of language in doing science and in learning from doing science. Yet, most existing science assessments for elementary learners do not integrate or attend to aspects of scientific language and literacy that are essential components of science proficiency. Accordingly, there is a…

Background: Middle school students use the information conveyed by morphemes (i.e., units of meaning such as prefixes, root words and suffixes) in different ways to support their literacy endeavours, suggesting the likelihood that morphological knowledge is multidimensional. This has important implications for assessment. Methods: The current…

Automated scoring for divergent thinking (DT) seeks to overcome a key obstacle to creativity measurement: the effort, cost, and reliability of scoring open-ended tests. For a common test of DT, the Alternate Uses Task (AUT), the primary automated approach casts the problem as a semantic distance between a prompt and the resulting idea in a text…

In this paper, we extracted content-based and structure-based features of text to predict human annotations for claims and nonclaims in argumentative essays. We compared Logistic Regression, Bernoulli Naive Bayes, Gaussian Naive Bayes, Linear Support Vector Classification, Random Forest, and Neural Networks to train classification models. Random…

Effective personalization of education requires knowing how each student will perform under certain conditions, given their specific characteristics. Thus, the demand for interpretable and precise estimation of heterogeneous treatment effects is ever-present. This paper outlines a new approach to this problem based on the Leave-One-Out Potential…

Text summarization is an effective reading comprehension strategy. However, summary evaluation is complex and must account for various factors including the summary and the reference text. This study examines a corpus of approximately 3,000 summaries based on 87 reference texts, with each summary being manually scored on a 4-point Likert scale.…

Intelligence Tutoring Systems (ITSs) focus on promoting knowledge acquisition, while providing relevant feedback during students' practice. Self-explanation practice is an effective method used to help students understand complex texts by leveraging comprehension. Our aim is to introduce a deep learning neural model for automatically scoring…

Purpose: This study explores the roles of morphological skills (Morphological Awareness, Morphological-Syntactic-Knowledge, Morphological-Semantic-Knowledge, and Morphological-Orthographic/Phonological-Knowledge), vocabulary (knowledge of definitions, relationships between words, and polysemous meanings), and syntax in contributing to adolescent…

Rapid advancements in computing have enabled automatic analyses of written texts created in educational settings. The purpose of this symposium is to survey several applications of computerized text analyses used in the research and development of productive learning environments. Four featured research projects have developed or been working on:…