The ability to self-regulate learning (SRL) is a skill theorized to transfer across learning environments. Students with this ability can consider a learning task, identify a goal, develop a plan to achieve it, execute that plan, and monitor and adapt learning until the goal is met. This paper examines the educational implications of developing…

We explore the nature of forgetting in a corpus of 125,000 students learning Spanish using the Rosetta Stone® foreign-language instruction software across 48 lessons. Students are tested on a lesson after its initial study and are then retested after a variable time lag. We observe forgetting consistent with power function decay at a rate that…

Swarm intelligence approaches, such as ant colony optimization (ACO), are used in adaptive e-learning systems and provide an effective method for finding optimal learning paths based on self-organization. The aim of this paper is to develop an improved modeling of adaptive tutoring systems using ACO. In this model, the learning object is…

Despite the promise of research conducted at the intersection of computer-assisted language learning (CALL), natural language processing, and second language acquisition, few studies have explored the potential benefits of using intelligent CALL systems to deepen our understanding of the process and products of second language (L2) learning. The…

This study investigated how the frequency and level of assistance provided to students interacted with prior knowledge to affect learning in the "Voyage to Galapagos" ("VTG") science inquiry-learning environment. "VTG" provides students with the opportunity to do simulated science field work in Galapagos as they…

Researchers are trying to develop assessments for inquiry practices to elicit students' deep science learning, but few studies have examined the relationship between students' "doing," i.e. "performance assessment," and "writing," i.e. "open responses," during inquiry. Inquiry practices include generating…

In this paper, we investigate the relationship between students' learning gains and their compliance with prompts fostering self-regulated learning (SRL) during interaction with MetaTutor, a hypermedia-based intelligent tutoring systems (ITS). When possible, we evaluate compliance from student explicit answers on whether they want to follow the…

To be able to provide better support for collaborative learning in Intelligent Tutoring Systems, it is important to understand how collaboration patterns change. Prior work has looked at the interdependencies between utterances and the change of dialogue over time, but it has not addressed how dialogue changes during a lesson, an analysis that…

We show that student learning can be accurately modeled using a mixture of learning curves, each of which specifies error probability as a function of time. This approach generalizes Knowledge Tracing [7], which can be viewed as a mixture model in which the learning curves are step functions. We show that this generality yields order-of-magnitude…

There is increasing evidence that fine-grained aspects of student performance and interaction within educational software are predictive of long-term learning. Machine learning models have been used to provide assessments of affect, behavior, and cognition based on analyses of system log data, estimating the probability of a student's particular…

Tutorial dialogue systems often simulate tactics used by experienced human tutors such as restating students' dialogue input. We investigated whether the amount of tutor restatement that supports student inference interacts with students' incoming knowledge level in predicting how much students learn from a system. We found that students with…

Although restating part of a student's correct response correlates with learning and various types of restatements have been incorporated into tutorial dialogue systems, this tactic has not been tested in isolation to determine if it causally contributes to learning. When we explored the effect of tutor restatements that support inference on…

Background: This study investigated learning outcomes and user perceptions from interactions with a hybrid intelligent tutoring system created by combining the AutoTutor conversational tutoring system with the Assessment and Learning in Knowledge Spaces (ALEKS) adaptive learning system for mathematics. This hybrid intelligent tutoring system (ITS)…

Speaking in Chinese is problematic for all learners, particularly for beginners and more so during online interaction. Despite the fact that interaction has been identified as crucial for the development of speaking skills, it can be hindered by students' lack of language competence or their anxiety. Teacher-centred practices in tutorials can…

Pearson sought to explore whether the use of Mastering Biology, an online tutorial system used in higher education general introductory courses, is related to students' exam results. This Research Report presents findings from one research study: a correlational study we conducted at a North American state-related, land-grant, doctoral university,…