Artificial intelligence-enabled adaptive learning systems (AI-ALS) are increasingly being deployed in education to enhance the learning needs of students. However, educational stakeholders are required by policy-makers to conduct an independent evaluation of the AI-ALS using a small sample size in a pilot study, before that AI-ALS can be approved…

This study examines the effects of teachable agents' expressed self-efficacy on students. A total of 166 students, 10- to 11-years-old, used a teachable agent-based math game focusing on the base-ten number system. By means of data logging and questionnaires, the study compared the effects of high vs. low agent self-efficacy on the students'…

"Sensor-free" detectors of student affect that use only student activity data and no physical or physiological sensors are cost-effective and have potential to be applied at large scale in real classrooms. These detectors are trained using student affect labels collected from human observers as they observe students learn within…

A common goal of Intelligent Tutoring Systems (ITS) is to provide learning environments that adapt to the varying abilities and characteristics of users. This type of adaptivity is possible only if the ITS has information that characterizes the learning behaviors of its users and can adjust its pedagogy accordingly. This study investigated an…

How can we test whether state-of-the-art generative models, such as Blender and GPT-3, are good AI teachers, capable of replying to a student in an educational dialogue? Designing an AI teacher test is challenging: although evaluation methods are much-needed, there is no off-the-shelf solution to measuring pedagogical ability. This paper reports…

Previous studies have demonstrated the effectiveness of intelligent tutoring systems (ITS) in facilitating English learning. However, no empirical research has been conducted on secondary students' intention to use ITSs in the language domain. This study proposes an extended technology acceptance model (TAM) to predict secondary students'…

Second language acquisition (SLA) is complex and multidimensional. Using the framework of the unified competition model (UCM), the current study explores how robust learning and testing of Chinese Pinyin are fostered by optimal integration of different kinds of feedback in an intelligent computer-assisted language learning (CALL) environment…

The U.S. Army is interested in extending the application of intelligent tutoring systems (ITS) beyond cognitive problem spaces and into psychomotor skill domains. In this paper, we present a methodology and validation procedure for creating expert model representations in the domain of rifle marksmanship. GIFT (Generalized Intelligent Framework…

Based on the sharable content object concept of advanced distributed learning, an ontology-based intelligent content object (ICO) that can automatically reason and be reused is proposed. Then, by extending the advanced distributed learning or sharable content object reference model (SCORM) specification, an interoperable model for the ICO is…

To provide personalized help to students who are working on code-writing problems, we introduce a data-driven tutoring system, ITAP (Intelligent Teaching Assistant for Programming). ITAP uses state abstraction, path construction, and state reification to automatically generate personalized hints for students, even when given states that have not…

Educational artificial intelligence (EAI) refers to the use of artificial intelligence (AI) to support personalized and automated feedback and guidance in the educational field. Inevitably, it serves as a more important part of the educational system in the coming years. However, novel development in this field has been inadequately reviewed and…

Learning involves a substantial amount of cognitive, social and emotional states. Therefore, recognizing and understanding these states in the context of learning is key in designing informed interventions and addressing the needs of the individual student to provide personalized education. In this paper, we explore the automatic detection of…

Reading to learn is a quintessentially self-regulated activity. In order to provide effective support for this activity it is necessary for us to understand how students adapt their self-regulation behaviors within disciplinary reading environments. In this paper, we utilize student response data from a digital literacy platform to examine the…

In an era of widespread automation--from grocery store self-checkout machines to selfdriving cars--it is not outrageous to wonder: can teachers be automated? And more specifically, can automated computer teachers instruct students how to write? Automated computer programs have long been used in summative writing evaluation efforts, such as scoring…

This study aimed to investigate the effectiveness of interactive learning module technology (ILMT) in teaching Kazakh as a second language in secondary schools in the Republic of Kazakhstan. This research was carried out at Russian-medium secondary schools during the academic year 2021-2022. There were two groups in the sample: the experimental…