Understanding student cognitive states is essential for assessing human learning. The deep neural networks (DNN)-inspired cognitive state prediction method improved prediction performance significantly; however, the lack of explainability with DNNs and the unitary scoring approach fail to reveal the factors influencing human learning. Identifying…

Research shows that meaning-focused reading offers opportunities for incidental grammar acquisition. However, the number of such studies remains limited and none have examined the role of both in-text encounters with grammar structures and reading comprehension in this learning. The present study filled these gaps. Employing a between-group,…

From about 7 months of age onward, infants start to reliably fixate the goal of an observed action, such as a grasp, before the action is complete. The available research has identified a variety of factors that influence such goal-anticipatory gaze shifts, including the experience with the shown action events and familiarity with the observed…

In Automated Essay Scoring (AES) systems, many previous works have studied group fairness using the demographic features of essay writers. However, individual fairness also plays an important role in fair evaluation and has not been yet explored. Initialized by Dwork et al., the fundamental concept of individual fairness is "similar people…

This study investigated the interactions among different cognitive abilities, linguistic structures, and the efficacy of different corrective feedback (CF) types. The cognitive abilities examined were declarative and procedural memory. The target linguistic structures were English regular and irregular past tense forms. In terms of the…

Dialogue act (DA) classification plays an important role in understanding, interpreting and modeling dialogue. Dialogue acts (DAs) represent the intended meaning of an utterance, which is associated with the illocutionary force (or the speaker's intention), such as greetings, questions, requests, statements, and agreements. In natural language…

Background: As a non-cognitive trait, grit plays an important role in human learning. Although students higher in grit are more likely to perform well on tests, how they learn in the process has been underexamined. Objectives: This study attempted to explore how students with different levels of grit behave and learn in an exploratory learning…

This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2)…

Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…

Active learning is widely recognized as superior to traditional passive, lecture-based techniques for fostering learning in STEM courses. Interactive, hands-on learning where students interact with their peers and physical systems is an effective type of active learning. As the need for scientists and engineers continues to grow, understanding and…

Intelligent tutoring systems (ITSs) teach skills using learning-by-doing principles and provide learners with individualized feedback and materials adapted to their level of understanding. Given a learner's history of past interactions with an ITS, a learner performance model estimates the current state of a learner's knowledge and predicts her…

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.…

Existing approaches in the literature on cognitive control in conflict tasks almost exclusively target the outcome of control (by comparing mean congruency effects) and not the processes that shape control. These approaches are limited in addressing a current theoretical issue--what contribution does learning make to adjustments in cognitive…

In this study, we investigated crosslinguistic influence (CLI) at developmental stages of third language (L3) acquisition of English by Russian--Norwegian children (N = 31). We tested seven linguistic properties within three linguistic modules (morphology, syntax and syntax-semantics). We compared the L3 learners to Norwegian (N = 90) and Russian…

This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction; and…