Intelligent tutoring system

About: Intelligent tutoring system is a research topic. Over the lifetime, 3472 publications have been published within this topic receiving 58217 citations. The topic is also known as: ITS.

Benefits of Handwritten Input for Students Learning Algebra Equation Solving

Abstract: Building on past results establishing a benefit for using handwriting when entering mathematics on the computer, we hypothesize that handwriting as an input modality may be able to provide significant advantages over typing in the mathematics learning domain. We report the results of a study in which middle and high school students used a software tutor for algebra equation solving with either typing or handwriting as the input modality. We found that handwriting resulted in similar learning gains in much less time than typing. We also found students seem to experience a higher degree of transfer in handwriting than in typing based on performance during training. This implies that students could achieve farther goals in an intelligent tutoring system curriculum when they use handwriting interfaces vs. typing. Both of these results encourage future exploration of the use of handwriting interfaces for mathematic instruction online.

Sherlock 2: An Intelligent Tutoring System Built on the LRDC Tutor Framework

Abstract: The Sherlock story began about a decade ago when our research and development team responded to the US Air Force’s need for an efficient training technology. Budget cutbacks across the armed services, as well as a shrinking pool of enlisted soldiers prompted the Air Force to look to Intelligent Tutoring Systems as a tool for training avionics technicians expediently in the skills needed to do their jobs, namely, diagnosing faults in, and repairing, faulty aircraft and the systems used to maintain them. Perhaps most importantly, the student can ask for advice at any point while troubleshooting. Sherlock provides advice at both the circuit path and individual component levels of investigation. The design of Sherlock 2 was also driven by the principles of apprenticeship learning upon which its predecessor, Sherlock, was based, that is, modeling of expert troubleshooting behavior, student-initiated coaching on the most difficult parts of the task, gradual fading of support as expertise is acquired.

Abdullah: An Intelligent Arabic Conversational Tutoring System for Modern Islamic Education

Abstract: This paper focuses on the development of a novel Arabic Conversational Intelligent Tutoring System (CITS) called Abdullah the tutor, Abdullah CITS is an online system that teaches students aged 10 to 12 years old the essential topics in Islam utilizing supportive evidence from the Quran and Hadith, allowing conversation, discussion and interpretation with verses in classical Arabic language by engaging in dialogue using Modern Arabic language. The proposed framework for developing Abdullah CITS is based on a Pattern Matching approach to handle the user's conversations, and to solve the complexity and ambiguity of processing the Arabic language. This paper describes the architecture of Abdullah and introduces the novel scripting language that has also been developed. The results of a pilot study are reported where the evaluation has indicated promising results.

Is Adaptive Learning Effective? A Review of the Research

Abstract: This study examines the evidence for the effectiveness of adaptive learning. It first analyses the different classifications of adaptive learning systems existing in the literature, to focus later on Intelligent Tutoring System (ITS) and Adaptive Hypermedia Systems (AHS) describing some examples of both types of systems. Next, the Effect Size (ES) tool is adopted as a standard way to compare the results of one pedagogical experiment to another. ES is used to analyse the effectiveness of the systems previously described, in order to demonstrate that adaptive learning can provide significant improvements in the learning process of students. Finally, a number of conclusions and future trends are discussed.

Supporting Students in Making Sense of Connections and in Becoming Perceptually Fluent in Making Connections among Multiple Graphical Representations.

Abstract: Prior research shows that multiple representations can enhance learning, provided that students make connections among them. We hypothesized that support for connection making is most effective in enhancing learning of domain knowledge if it helps students both in making sense of these connections and in becoming perceptually fluent in making connections. We tested this hypothesis in an experiment with 428 4th- and 5th-grade students who worked with different versions of an intelligent tutoring system for fractions learning. Results did not show main effects for sense-making or fluency-building support but an interaction effect, such that a combination of sense-making and fluency-building support is most effective in enhancing fractions knowledge. Causal path analysis of log data from the system shows that sense-making support enhances students’ benefit from fluency-building support, but fluency-building support does not enhance their benefit from sense-making support. Our results suggest that both understanding of connections and perceptual fluency in connection making are critical aspects of learning of domain knowledge with multiple graphical representations. Findings from the causal path analysis lead to the testable prediction that instruction should provide sense-making support and fluency-building support for connection making.