The Jeong (2020) study found that greater use of backward and depth-first processing was associated with higher scores on students' argument maps and that analysis of only the first five nodes students placed in their maps predicted map scores. This study utilized the jMAP tool and algorithms developed in the Jeong (2020) study to determine if the…

Prompting students to generate constructed responses as they read provides a window into the processes and strategies that they use to make sense of complex text. In this study, Markov models examined the extent to which: (1) patterns of strategies; and (2) strategy combinations could be used to inform computational models of students' text…

Among the various kinds of learning analytics emerging especially in the latest decade, clicking patterns cover a prominent role, fostered by their success in analyzing several types of data concerning activity on the web. They can be defined as sets of clicks performed by users, in which every set is treated as the basic unit. Few research has…

A learner model reflects learning patterns and characteristics of a learner. A learner model with learning history and its effectiveness plays a significant role in supporting a learner's understanding of their strengths and weaknesses of their way of learning in order to make proper adjustments for improvement. Nowadays, learners have been…

In this paper, we propose a novel approach to combine domain modelling and student modelling techniques in a single, automated pipeline which does not require expert knowledge and can be used to predict future student performance. Domain modelling techniques map questions to concepts and student modelling techniques generate a mastery score for a…

Machine learning methods for predictive analytics have great potential for uncovering trends in educational data. However, simple linear models still appear to be most widely used, in part, because of their interpretability. This study aims to address the issues of interpretability of complex machine learning classifiers by conducting feature…

In educational applications, "Knowledge Tracing" (KT) has been widely studied for decades as it is considered a fundamental task towards adaptive online learning. Among proposed KT methods, Deep Knowledge Tracing (DKT) and its variants are by far the most effective ones due to the high flexibility of the neural network. However, DKT…

The search for rigor in learning analytics applications has placed survey data in the suspect's corner, favoring more objective trace data. A potential lack of objectivity in survey data is the existence of response styles, the tendency of respondents to answer survey items in a particular biased manner, such as yeah saying or always disagreeing.…

To understand how learner metacognition and goal orientation affect learner problem-solving in a Serious Game (SG) environment, this study examined 12 undergraduate students' metacognition, goal orientations, and problem-solving performances and processes while playing a SG that adopts problem-based learning pedagogy to teach space science.…

This paper demonstrates how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. We examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance prediction; and (2) what types of in-game features were associated with student…

One significant challenge in the field of measuring ability is measuring the current ability of a learner while they are learning. Many forms of inference become computationally complex in the presence of time-dependent learner ability, and are not feasible to implement in an online context. In this paper, we demonstrate an approach which can…

Due to the COVID-19 restrictions, high-schools in Spain are having both online and in-class lectures. As a result, the students can use not only the information provided by the teachers in class, but they can also use several other methods such as videos and online examples that allow the students to have materials from different places. In this…

This article introduces self-regulation features with Partial and Synchronized Caption (PSC) for practicing listening skills and fostering self-paced and autonomous learning. PSC generates a partial caption by focusing on acoustically and lexically difficult words and synchronizes each word's appearance with the speaker's speech. The aim is to…

The needs for precisely estimating a student's academic performance have been emphasized with an increasing amount of attention paid to Intelligent Tutoring System (ITS). However, since labels for academic performance, such as test scores, are collected from outside of ITS, obtaining the labels is costly, leading to label-scarcity problem which…

Each year, roughly 30% of first-year students at US baccalaureate institutions do not return for their second year and billions of dollars are spent educating these students. Yet, little quantitative research has analyzed the causes and possible remedies for student attrition. What's more, most of the previous attempts to model attrition at…