Assessing the knowledge of a student is a fundamental part of intelligent learning environments. We present a Bayesian network based approach to dealing with uncertainty when estimating a learner’s state of knowledge in the context of Qualitative Reasoning (QR). A proposal for a global architecture is given. The essentials of the belief network structure for individual scenarios are described, ...

The concept of situation awareness is essential in enhancing collaborative learning. Learners require information from different awareness aspects to deduce a learning situation for decision-making. Designing learning environments that assist learners to understand situation awareness via monitoring actions and reaction of other learners has been reported to be beneficial in enhancing collabora...

The automated scoring of second-language (L2) learner text along various writing dimensions is an increasingly active research area. In this paper, we focus on determining the topical relevance of an essay to the prompt that elicited it. Given the burden involved in manually assigning scores for use in training supervised prompt-relevance models, we develop unsupervised models and show that the...

Nowadays, inquiry learning, in which learners construct knowledge based on information they collect from real life experiments or simulations, plays an increasing role in education. Inquiry learning holds the promise of learners constructing deeper rooted knowledge as well as acquiring an inquiry competency, being better prepared for dealing with new and unknown situations and collecting and us...

We address the problem of detecting English language learner errors by using a discriminative high-order sequence model. Unlike most work in error-detection, this method is agnostic as to specific error types, thus potentially allowing for higher recall across different error types. The approach integrates features from many sources into the error-detection model, ranging from language model-ba...

In recent decades research on human emotion has revealed that affect plays a central role in human cognition. Historically, emotion was viewed as separate from cognition, and only recently has there been consensus that affect is a central component of rational behavior and social interaction (Forgas, Wyland, & Lahan, 2006). These findings have motivated the goal of designing affect-sensitive co...

Online education is an inevitable trend in the era of digital transformation, but effective implementation not easy. This research was conducted to understand relationship between interaction and perceived progress online learning, under mediated effect satisfaction. Data gathered from 223 full-time learners at nine universities Vietnam, using Google Forms. Since study had a mediating variable,...

Purpose The purpose of this study is to evaluate the effect learner–learner and learner–facilitator interactions on learner satisfaction their substitutability. Design/methodology/approach A quantitative survey research focusing 130 students was used collect data. Stratified sampling preferred for study, with a Likert type instrument being administered online. Findings Learner–learner mediate e...

An online classification system maintained by a learner can be subject to latency and filtering of training examples which can impact on its classification accuracy especially under concept drift. A life-cycle model is developed to provide a framework for studying this problem. Meta data emerges from this model which it is proposed can enhance online learning systems. In particular, the definit...

In light of the present situation researches on learner model in Adaptive Learning System at home and abroad, analyze the design principles and characteristics of Adaptive Learning System. Based on these, this paper summarizes the main problems of learner model from dimension of attention, representation method and acquisition path. It puts forward a new learner model called Advanced Learner Mo...