For decades, educators have relied on readability metrics that tend to oversimplify dimensions of text difficulty. This study examines the potential of applying advanced artificial intelligence methods to the educational problem of assessing text difficulty. The combination of hierarchical machine learning and natural language processing (NLP) is…

Source-based essays are evaluated both on the quality of the writing and the content appropriate interpretation and use of source material. Hence, composing a high-quality source-based essay (an essay written based on source material) relies on skills related to both reading (the sources) and writing (the essay) skills. As such, source-based…

Research suggests that promoting metacognitive awareness can increase performance in, and learning from, intelligent tutoring systems (ITSs). The current work examines the effects of two metacognitive prompts within iSTART, a reading comprehension strategy ITS in which students practice writing quality self-explanations. In addition to comparing…

Game-based environments frequently afford students the opportunity to exert agency over their learning paths by making various choices within the environment. The combination of log data from these systems and dynamic methodologies may serve as a stealth means to assess how students behave (i.e., deterministic or random) within these learning…

Using students' process data from the game-based Intelligent Tutoring System (ITS) iSTART-ME, the current study examines students' propensity to use system currency to unlock game-based features, (i.e., referred to here as "spendency"). This study examines how spendency relates to students' interaction preferences, in-system performance,…