Personalized recommendation plays an important role on content selection during the adaptive learning process. It is always a challenge on how to recommend effective items to improve learning performance. The aim of this study was to examine the feasibility of applying adaptive testing technology for personalized recommendation. We proposed the…

Recently, automatic question generation (AQG) has been researched extensively for educational purposes. Existing approaches generally lack relevant information on the authentic context and problem diversity with various difficulty levels, so we proposed a new AQG system for generating contextualized and personalized mathematic word problems (MWP)…

This study investigates the impact of AI-assisted language learning (AIAL) strategies on cognitive load and learning outcomes in the context of language acquisition. Specifically, the study explores three distinct AIAL strategies: personalized feedback and adaptive learning, interactive exercises with speech recognition, and intelligent tutoring…

This meta-analysis extended the current literature regarding the effects of computer technology (CT) on mathematics achievement, with a particular focus on low-performing students. A total of 45 independent effect sizes extracted from 31 empirical studies based on a total of 2,044 low-performing students in K-12 classrooms were included in this…

Massive open online courses (MOOCs) show great potential to transform traditional education through the Internet. However, the high attrition rates in MOOCs have often been cited as a scale-efficacy tradeoff. Traditional educational approaches are usually unable to identify such large-scale number of at-risk students in danger of dropping out in…

The falling learning outcome is one of the major challenges faced by most of the educational systems. Adaptive educational systems (AESs) are viewed as catalyst to reinforce learning. Several AESs have been developed considering only single aspect of learners, for example, learning styles. The impact of learning style-based AESs in terms of…

The learner-centered paradigm of instruction differs in such fundamental ways from the teacher-centered paradigm that it requires technology to serve very different functions. In 2006, a research team at Indiana University began to work on identifying those functions and published their results in 2008. Subsequently, the team elaborated and…

Newtonian mechanics is a core module in technology courses, but is difficult for many students to learn. Computerized tutoring can assist the teachers to provide individualized instruction. This article presents the application of decision theory to develop a tutoring system, "iTutor", to select optimal tutoring actions under uncertainty of…

Demonstrates how Bayesian reasoning can be used to adjust the length of computer-guided practice exercises and computer-based tests to help make mastery or nonmastery decisions. Individualization of instruction is discussed, and the results of an empirical study that used the sequential probability ratio test (SPRT) are presented. (25 references)…

Describes study that examined the effects of combining word processors, spelling checkers, and spelling drill and practice programs to individualize spelling instruction for fifth- and sixth-grade students. Treatments for the experimental and control groups are explained, selection of software is discussed, and suggestions for software development…

Discussion of peer-based collaborative learning focuses on two related studies: a micro-structure comparative analysis of students' psycho-social behaviors in computer-based collaborative learning experiments conducted in face-to-face and distributed learning environments; and an examination of cognitive effects of peer-based collaborative…