To investigate the practices of prenatal ultrasound consultation in a region of the China and to describe the rate of concordance between the suspected anomaly and the final diagnosis of the referral examination.

Retrospective analysis of 2054 cases from 24 hospitals underwent ultrasonic consultation in a tertiary prenatal diagnosis center in Beijing, China

A complex systems approach to analyzing pedagogical agents’ scaffolding of self-regulated learning within an intelligent tutoring system

The teaching quality monitoring and evaluation system in colleges and universities gives the scientific and objective evaluation of school teaching work and effectively optimizes and adjusts the important system of teaching work under the condition of deep excavation of the problems. However, the data on the teaching quality of colleges and universities in the state of static storage has seriously affected the value of data existence and the mining of laws. This paper mainly analyzes the application types of data mining technology in the college basketball teaching quality monitoring and evaluation system and discusses the data mining implementation method in the college basketball teaching quality and evaluation system, hoping to have a certain reference for relevant personnel.

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The Application Method of Big Data of Data Mining Algorithm in College Basketball Teaching

In the past decades, AI was not playing a pivotal role in technology. But now, artificial intelligence is a key part of the revolution of technology. AI has become a powerful tool in recent years, enabling machines to think and act like humans. AI helps in developing a better approach to teaching students (i.e., adaptive learning where a computer algorithm identifies the rate of learning of a student and adapts itself so that the student learns efficiently). The aim of implementing AI in education is not to replace tutors, but to assist them in understanding the potential and limitations of each student individually. This chapter will cover the introduction, existing applications, and new applications of artificial intelligence in higher education. The prime focus of the chapter will be on the approaches to different product developments and their implementation using artificial intelligence in the education sector. It provides a brief idea of how the existing applications solve the problems in higher education and new approaches to make higher education more efficient. 

Artificial Intelligence in Higher Education

—Ontology as a technology has been studied in many areas and is being used in several fields. A number of studies have utilized ontology to manage problems such as interoperability in teaching materials, modeling and enriching education resources, and personalizing learning content recommendations in the educational context. A possible reason for the lack of success may be that simply posting lecture notes on the internet does not provide enough learning and training. However, this situation can improve by using education software like an e-tutoring system. The e-tutor system has built-in modules to track students' performance and personalize learning according to an adaptation of students' learning styles, knowledge levels, and proper teaching techniques in e-learning systems. e-Tutor is an excellent area in the context of electronic instruction since it provides adequate aid for learners and becomes increasingly important for individual and collaborative learning. Thus, there has been significant interest in adopting e-tutoring to facilitate learning processes and enhance learners' performance. This paper represents a domain knowledge model for an e-tutoring system that enables knowledge to be stored in such a way separated from the domain of interest and assists in storing transfer and prerequisite knowledge relationships. This innovative technique is helpful for the students in improving their learning progress. This paper introduced a domain knowledge model for an e-tutor system to support the way of teaching and learning process. The model implementation is developed in Python and Owlready2. Two types of ontologies are provided: general concepts of the domain knowledge ontology and specific domain knowledge ontology. This solution represents the knowledge to be learned, delivers input to the expert model, and eventually provides specific feedback, selects problems, generates guidance, and supports the student model.

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Development of Ontology-based Domain Knowledge Model for IT Domain in e-Tutor Systems

Intelligent Tutoring Systems (ITSs) are educational systems that reflect knowledge using artificial intelligence implements. In this paper, we give an outline of the Programming-Tutor architectural design with the core implements on user interaction. This pilot proposal is for designing a model domain of a subset in the computer programming language. The completed project would be adequate to show the idea of a completely developed computing Intelligent Tutoring System in online programming courses to offer benefits to students in the Pacific. This proposed concept would also provide students with an immersive learning experience in an online course to assist in a formative assessment to enhance student learning. A smart tutoring system can provide prompt input of high quality which not only conveys to students about the consistency of the solution but also provides them with information on the precision of the key concerning their existing solutions expertise. This Intelligent Tutoring System (ITS) is proposed to be designed using intelligent algorithms such as optimized ant colony to be able to support the online tutoring system that can initiate the complex learning principles in computing science courses. It is also hypothesized that, based on the performance of other Intelligent Tutoring Systems, students would be able to learn to program more easily in regional campuses and acquire experiences more rapidly and efficiently than students who are taught using conventional methods in an online mode. 

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Mayuri Harkishan

Papers

Designing an intelligent tutoring system for computer programing in the Pacific