Web-based Intelligent Tutoring Systems Research Articles

Using Web-based Intelligent Tutoring Systems in Teaching Physics Subjects at Undergraduate Level

The aim of the study is to draw attention to the importance of using web-based intelligent tutoring systems (WBITS), which have emerged as a result of artificial neural networks and technological developments (communication technology), in the teaching of physics subjects. A WBITS is an intelligent tutoring system that exhibits behavior similar to that of a teacher in the traditional educational process (classroom education), offers a flexible teaching process, defined according to user preferences, and adaptable for a specific purpose. WBITSs make important contributions to distance education and classroom education processes, because they can be used online and offline. The importance of using WBITSs in teaching physics at undergraduate level was subsumed under five headings: i). Developments in technology and artificial neural networks and the interest of young people in technology have made it important to use WBITSs in undergraduate physics education. ii) The use of WBITSs has become important in following scientific developments in traditional (classroom) physics education and eliminating problems related to individual perception capacity and insufficient class hours. iii). Online (remote) access to physics subjects via WBITSs contributes to equality of opportunity in education. iv). More time can be devoted to practice and the discussion of deeper (advanced) subjects in the classroom when basic physics subjects are taught at undergraduate (university) level using WBITSs. v). Limitations in distance physics education can be reduced using WBITSs.

Effects of Web-based Intelligent Tutoring Systems on Academic Achievement and Retention

Effects of Web-based Intelligent Tutoring Systems on Academic Achievement and Retention

Adaptive feedback in computer-based learning environments: a review

Adaptive support within a learning environment is useful because most learners have different personal characteristics such as prior knowledge, learning progress, and learning preferences. This study reviews various implementation of adaptive feedback, based on the four adaptation characteristics: means, target, goal, and strategy. This review focuses on 20 different implementations of feedback in a computer-based learning environment, ranging from multimedia web-based intelligent tutoring systems, dialog-based intelligent tutoring systems, web-based intelligent e-learning systems, adaptive hypermedia systems, and adaptive learning environment. The main objective of the review is to compare computer-based learning environments according to their implementation of feedback and to identify open research questions in adaptive feedback implementations. The review resulted in categorizing these feedback implementations based on the students’ information used for providing feedback, the aspect of the domain or pedagogical knowledge that is adapted to provide feedback based on the students’ characteristics, the pedagogical reason for providing feedback, and the steps taken to provide feedback with or without students’ participation. Other information such as the common adaptive feedback means, goals, and implementation techniques are identified. This review reveals a distinct relationship between the characteristics of feedback, features of adaptive feedback, and computer-based learning models. Other information such as the common adaptive feedback means, goals, implementation techniques, and open research questions are identified.

Rule-based Cognitive Modeling and Model Tracing in a Math Story Problem Tutor

Intelligent Tutoring Systems (ITSs) are intended to help in tutoring the students in specific domains typically by improving their problem solving skills. An important aspect of such ITSs is their ability to solve the generated problems in the same way that the student would in addition to interpreting the student actions to provide relevant feedback and help. Cognitive models that mimic the way knowledge is represented in human minds are excellent means toward achieving this goal. This paper discusses cognitive modelling in the MAth Story problem Tutor (MAST). MAST is a Web-based ITS that can generate probability story problems of different contexts, types and difficulty levels. The paper also discusses the model tracing approach of MAST to interpret the student actions in symbolizing the word problems and estimating the required probabilities to provide relevant feedback and help. A major contribution of the paper is in considering the symbolization of the probability word problems to convert them to the symbolic form and tracing the students errors in this process. As an example, the paper considers the context of rolling a die and tossing a coin. Evaluation results have shown the ability of MAST to considerably improve the probability story problem solving skills of the students.

Investigating Pre-service Mathematics Teachers' Innovation Awareness and Views Regarding Intelligent Tutoring Systems

The purpose of this study is to identify pre-service primary mathematics teachers' views regarding on Web-based Intelligent Tutoring Systems (WBITS) in relation to its usability and influence on teaching. A survey method was used. The study was conducted with 43 students attending the mathematics teaching program under the department of elementary education. The data were collected through a paper-based survey composed of three parts. In the first part of the survey, there are 9 items about demographic information demographic profile of the respondents such as name, gender, age, study styles, learning styles, and motivation styles. In the second part, there is a scale about Innovation Awareness Scale and in the third part there is a scale about views concerning the usability and the influence of WBITS on learning. The data obtained from the study were analyzed using SPSS-21 based on descriptive statistics such as frequency, percentage distribution, and arithmetic mean in addition to MANOVA, which is a parametric test, and Pearson product-moment correlation coefficient. Analysis indicated that the participants were neither negative or positive regarding both WBITS and innovation. It was seen that there was no significant relationship between participant awareness regarding innovation and their views regarding WBITS. Another important finding is that study styles, learning styles, and motivation styles are not influential variables over their views about WBITS' usability and its effect on learning attitudes towards WBITS.

Live-action mass-casualty training and virtual world training

Live-action training simulations with expert facilitators are considered by many to be the gold-standard in training environments. However, these training environments are expensive, provide many logistical challenges, and may not address the individual’s learning needs. Fortunately, advances in distance-based learning technologies have provided the foundation for inexpensive and effective learning environments that can simultaneously train and educate students on a much broader scale than live-action training environments. Specifically, intelligent tutoring systems (ITSs) have been proven to be very effective in improving learning outcomes. The Virtual Civilian Aeromedical Evacuation Sustainment Training (VCAEST) interface takes advantage of both of these technologies by enhancing a virtual world with a web-based ITS, AutoTutor LITE (Learning in Interactive Training Environments). AutoTutor LITE acts as a facilitator in the virtual world by providing just-in-time feedback, presenting essential domain knowledge, and by utilizing tutoring dialogues that automatically assess user input. This paper will discuss the results of an experimental evaluation of the VCAEST environment compared to an expert-led live-action training simulation.

Student View on Web-Based Intelligent Tutoring Systems about Success and Retention of Physics Education

Student View on Web-Based Intelligent Tutoring Systems about Success and Retention of Physics Education

Developing an Intelligent Tutoring System that has Automatically Generated Hints and Summarization for Algebra and Geometry

Intelligent tutoring systems (ITSs), which provide step-by-step guidance to students in problem-solving activities, have been shown to enhance student learning in a range of domains. However, they tend to be preestablished and cannot supply the tutoring function immediately from the diverse mathematical questions. The MITSAS (multiagent intelligent tutoring system after school) is a web-based ITS in algebra and geometry with a natural language interface which is designed to extract the hint and summarization from the detailed solving answer automatically. In this paper, its Design principles and functionality is analysed firstly. Then, the framework including the natural language understanding agent, automatic modelling agent and automatic problem-solving agent are discussed in the following in order to support the real-time problems solution. Next, the methods for automatically extracting tutoring function such as hint and summarization is given based on the difficulty of knowledge components and the type of problem acquired from the detailed answer. Finally, the effectiveness of MITSAS at improving the Chinese Students' learning gain is shown by an experiment conducted in junior school.

The Influence of Web-based Intelligent Tutoring Systems on Academic Achievement and Permanence of Acquired Knowledge in Physics Education

The Influence of Web-based Intelligent Tutoring Systems on Academic Achievement and Permanence of Acquired Knowledge in Physics Education

High-fidelity implementation of web-based intelligent tutoring system improves fourth and fifth graders content area reading comprehension

Technologies and their effectiveness are impacted by how well they are implemented. A large scale randomized controlled trial was conducted to study the efficacy of a web-based intelligent tutoring system to deliver the structure strategy to improve content area reading comprehension. We present our theory of change focusing on the theoretical framework: structure strategy, delivery approach of web-based intelligent tutoring systems, and contextual conditions for successful adoption of the tool with fidelity. Results from the optimal implementation schools show statistically significantly better performance by ITSS classrooms compared to their control counterparts with moderate to large effect sizes. Conditions for implementing technology-based interventions with fidelity in schools are discussed.

Polite web-based intelligent tutors: Can they improve learning in classrooms?

Should an intelligent software tutor be polite, in an effort to motivate and cajole students to learn, or should it use more direct language? If it should be polite, under what conditions? In a series of studies in different contexts (e.g., lab versus classroom) with a variety of students (e.g., low prior knowledge versus high prior knowledge), the politeness effect was investigated in the context of web-based intelligent tutoring systems, software that runs on the Internet and employs artificial intelligence and learning science techniques to help students learn. The goal was to pinpoint the appropriate conditions for having the web-based tutors provide polite feedback and hints (e.g., “Let’s convert the units of the first item”) versus direct feedback and hints (e.g., “Convert the units of the first item now”). In the study presented in this paper, 132 high school students in a classroom setting, grouped as low and high prior knowledge learners according to a pre-intervention knowledge questionnaire, did not benefit more from polite feedback and hints than direct feedback and hints on either an immediate or delayed posttest, both of which contained near transfer and conceptual test items. Of particular interest and contrary to an earlier lab study, low prior knowledge students did not benefit more from using the polite version of a tutor. On the other hand, a politeness effect was observed for the students who made the most errors during the intervention, a different proxy for low prior knowledge, hinting that even in a classroom setting, politeness may be beneficial for more needy students. This article presents and discusses these results, as well as discussing the politeness effect more generally, its theoretical underpinnings, and future directions.

Implementing Web-Based Intelligent Tutoring Systems in K-12 Settings: A Case Study on Approach and Challenges

Technologies for learning environments are a vital and growing market for software development and utilization. A team of designers and developers created a Web-based intelligent tutoring system to teach a reading comprehension strategy for elementary and middle school students. Our approach to designing ITSS. combined the waterfall method of technology design with prescriptions for creating cognitive tutors. This article reports on each phase of the process: analysis, design, development, and implementation of the system and the challenges and solutions at each stage.

A Framework for the Initialization of Student Models in Web-based Intelligent Tutoring Systems

Initializing a student model for individualized tutoring in educational applications is a difficult task, since very little is known about a new student. On the other hand, fast and efficient initialization of the student model is necessary. Otherwise the tutoring system may lose its credibility in the first interactions with the student. In this paper we describe a framework for the initialization of student models in Web-based educational applications. The framework is called ISM. The basic idea of ISM is to set initial values for all aspects of student models using an innovative combination of stereotypes and the distance weighted k-nearest neighbor algorithm. In particular, a student is first assigned to a stereotype category concerning her/his knowledge level of the domain being taught. Then, the model of the new student is initialized by applying the distance weighted k-nearest neighbor algorithm among the students that belong to the same stereotype category with the new student. ISM has been applied in a language learning system, which has been used as a test-bed. The quality of the student models created using ISM has been evaluated in an experiment involving classroom students and their teachers. The results from this experiment showed that the initialization of student models was improved using the ISM framework.