Intelligent Tutoring Systems (ITS) are computer-based learning environments that aim to imitate to the greatest possible extent the behavior of a human tutor in their capacity as a pedagogical and subject expert. One of the major challenges of these systems is to know how to adapt the training both to changing requirements of all kinds and to…

Learners' choices as to whether and how to use visual representations during learning are an important yet understudied aspect of self-regulated learning. To gain insight, we developed a "choice-based" intelligent tutor in which students can choose whether and when to use diagrams to aid their problem solving in algebra. In an…

This study addresses the challenge of teaching genetics effectively to high school students, a topic known to be particularly challenging. Leveraging the growing importance of artificial intelligence (AI) in education, the research explores the perspectives, attitudes, and behavioral intentions of pre-service teachers regarding the integration of…

Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…

In recent years, we have seen the continuous and rapid increase of job openings in Science, Technology, Engineering and Math (STEM)-related fields. Unfortunately, these positions are not met with an equal number of workers ready to fill them. Efforts are being made to find durable solutions for this phenomena, and they start by encouraging young…

This study aims to identify effective affective states and behaviors of middle-school students' online mathematics learning in predicting their choices to study science, technology, engineering, and mathematics (STEM) in higher education based on a "positive-affect-to-success hypothesis." The dataset (591 students and 316,974 actions)…

Given the increasing need for skilled workers in science, technology, engineering, and mathematics (STEM), there is a burgeoning interest to encourage young students to pursue a career in STEM fields. Middle school is an opportune time to guide students' interests towards STEM disciplines, as they begin to think about and plan for their career…

If we wish to embed assessment for accountability within instruction, we need to better understand the relative contribution of different types of learner data to statistical models that predict scores and discrete achievement levels on assessments used for accountability purposes. The present work scales up and extends predictive models of math…

We show how the novel use of a semantic representation based on Osgood's semantic differential scales can lead to effective features in predicting short- and long-term learning in students using a vocabulary learning system. Previous studies in students' intermediate knowledge states during vocabulary acquisition did not provide much information…

This poster reports on a study that compared three types of summaries at the end of natural-language tutorial dialogues and a no-dialogue control, to determine which type of summary, if any, best predicted learning gains. Although we found no significant differences between conditions, analyses of gender differences indicate that female students…

Self-explanations are commonly used to assess on-line reading comprehension processes. However, traditional methods of analysis ignore important temporal variations in these explanations. This study investigated how dynamical systems theory could be used to reveal linguistic patterns that are predictive of self-explanation quality. High school…

For at least the last century researchers have advocated the use of student confidence as a form of educational assessment and the growth of online and mobile educational software has made the implementation of this measurement far easier. The following short paper discusses our first study of the dynamics of student confidence in an online math…

This study empirically evaluated the effectiveness of the instructional design, learning tools, and role of the teacher in three versions of a semester-long, high-school remedial Algebra I course to determine what impact self-regulated learning skills and learning pattern training have on students' self-regulation, math achievement, and…

The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…

The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…