Knowledge tracing (KT) aims to predict students' future performances based on their former exercises and additional information in educational settings. KT has received significant attention since it facilitates personalized experiences in educational situations. Simultaneously, the autoregressive (AR) modeling on the sequence of former exercises…

The relationships among teachers' knowledge, use, and perceived effectiveness of inclusive instructional practices for students with emotional disturbance (ED) has implications for the provision of a free appropriate public education (FAPE). We unpacked these nuanced relationships through mediation analysis. Data for our study came from a broader…

This study's innovative objective was to develop a personalised learning model to equate students' entry level knowledge as they entered the School of Medicine and Health Sciences at Tecnologico de Monterrey in Mexico in 2019. This was necessitated by a difference in the depth and approach to preparatory content. The methodology focused on…

Personalized learning environments requiring the elicitation of a student's knowledge state have inspired researchers to propose distinct models to understand that knowledge state. Recently, the spotlight has shone on comparisons between traditional, interpretable models such as Bayesian Knowledge Tracing (BKT) and complex, opaque neural network…

This multiple case study describes a year-long implementation of a research-based coaching model designed to support changes in elementary teachers' technology integration practices. We examined coaches' perceptions of the model through the use of coaches' questionnaires, reflection notes, and meeting notes. Teachers' coaching experiences were…

Face-to-face human tutoring in classroom environments amply facilitates human tutor-learner interactions wherein the tutor gets opportunity to exercise his cognitive intelligence to understand learner's pre-knowledge level, learning pattern, specific learning difficulties, and be able to offer course content well-aligned to the learner's…

Modeling student knowledge while students are acquiring new concepts is a crucial stepping stone towards providing personalized automated feedback at scale. We believe that rich information about a student's learning is captured within her responses to open-ended problems with unbounded solution spaces, such as programming exercises. In addition,…

In this work we use prior to tutor-session data to generate an individualized student knowledge model. Intelligent learning environments use student models to individualize curriculum sequencing and help messages. Researchers decompose the learning tasks into sets of Knowledge Components (KCs) that represent individual units of knowledge; the…

Increasing availability of immersive virtual reality (IVR) systems, such as the Cave Automatic Virtual Environment (CAVE) and head-mounted displays, for use in education contexts is providing new opportunities and challenges for instructional designers. By highlighting the affordances of IVR specific to the CAVE, the authors emphasize the…

This paper presents a conceptual approach and a Web-based service that aim at supporting self-regulated learning in virtual environments. The conceptual approach consists of four components: 1) a self-regulated learning model for supporting a learner-centred learning process, 2) a psychological model for facilitating competence-based…

Personalized e-learning implementation is recognized as one of the most interesting research areas in the distance web-based education. Since the learning style of each learner is different one must fit e-learning with the different needs of learners. This paper presents an approach to integrate learning styles into adaptive e-learning hypermedia.…

One of the most important factors for improving the personalization aspects of learning systems is to enable adaptive properties to them. The aim of the adaptive personalized learning system is to offer the most appropriate learning path and learning materials to learners by taking into account their profiles. In this paper, a new approach to…

The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…

A personalized e-learning framework based on a user-interactive question-answering (QA) system is proposed, in which a user-modeling approach is used to capture personal information of students and a personalized answer extraction algorithm is proposed for personalized automatic answering. In our approach, a topic ontology (or concept hierarchy)…

Taking advantage of the continuously improving, web-based learning systems plays an important role for self-learning, especially in the case of working people. Nevertheless, learning systems do not generally adapt to learners' profiles. Learners have to spend a lot of time before reaching the learning goal that is compatible with their knowledge…