Ramscar, Yarlett, Dye, Denny, and Thorpe (2010) showed how, consistent with the predictions of error-driven learning models, the order in which stimuli are presented in training can affect category learning. Specifically, learners exposed to artificial language input where objects preceded their labels learned the discriminating features of…

For offering adaptive learning to learners in intelligent tutoring systems, one of the fundamental tasks is knowledge tracing (KT), which aims to assess learners' learning states and make prediction for future performance. However, there are two crucial issues in deep learning-based KT models. First, the knowledge concepts are used to predict…

Recent studies have found that infants show relational learning in the first year. Like older children, they can abstract relations such as "same" or "different" across a series of exemplars. For older children, language has a major impact on relational learning: labeling a shared relation facilitates learning, while labeling…

Recent context-control learning studies have shown that switch costs are reduced in a particular context predicting a high probability of switching as compared to another context predicting a low probability of switching. These context-specific switch probability effects suggest that control of task sets, through experience, can become associated…

It is well known that information from spoken language is integrated into reading processes, but the nature of these links and how they are acquired is less well understood. Recent evidence has suggested that predictions about the written form of newly learned spoken words are already generated prior to print exposure. We extend this work to…

Anticipation Guides (AGs) help learners to activate prior knowledge before an instructional unit. As a pre-learning strategy, AGs motivate learners to explore learning materials by challenging, activating, or corroborating their prior knowledge and predictions about a subject. While AGs have mostly been used in reading instruction, in this study,…

Bayesian Knowledge Tracing (BKT) is a commonly used approach for student modeling, and Long Short Term Memory (LSTM) is a versatile model that can be applied to a wide range of tasks, such as language translation. In this work, we directly compared three models: BKT, its variant Intervention-BKT (IBKT), and LSTM, on two types of student modeling…

Over the past few decades, many studies conducted in the field of learning science have described that scaffolding plays an important role in human learning. To scaffold a learner efficiently, a teacher should predict how much support a learner must have to complete tasks and then decide the optimal degree of assistance to support the learner's…

Children recognize that people who know more are better informants than those who know less. How does an individual's prior knowledge affect children's decisions about whom to inform? In 3 experiments, 3- to 6-year-old children were invited to share a novel piece of information with 1 of 2 potential recipients who differed in their recent history…

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…

This dissertation explores the processes that drive perceptual adaptation to variation in speech by examining how sources of prediction and uncertainty modulate perceptual learning processes. In particular, we examined how the perceptual system leverages different types of information during adaptation, varying in the degree to which they predict…

People learn from prior experiences. We first learn how to use a spoon and then know how to use a different size of spoon. We first learn how to sew and then learn how to embroider. Transferring knowledge from one situation to another related situation often increases the speed of learning. This observation is relevant to human learning, as well…

The purpose of this study is to investigate and conceptualize the ranks of importance of social cognitive variables on university students' computer programming performances. Spatial ability, working memory, self-efficacy, gender, prior knowledge and the universities students attend were taken as variables to be analyzed. The study has been…

As online courses become more common, practitioners are in need of clear guidance on how to translate best educational practices into web-based instruction. Moreover, student engagement is a pressing concern in online courses, which often have high levels of dropout. Our goals in this work were to experimentally study routine instructional design…

Recent research on early word learning suggests that children's behavior when-generalizing novel nouns integrates their prior vocabulary knowledge with the specifics of the task. This study examines how these factors interact on the moment-to-moment time scale of the training children receive and the sequence of stimuli they are shown. In 1…