scholarly journals ONLINE FUNCTIONAL LITERACY, INTELLIGENT TUTORING SYSTEMS AND SCIENCE EDUCATION

2015 ◽  
Vol 14 (2) ◽  
pp. 162-171
Author(s):  
Kosta Dolenc ◽  
Boris Aberšek ◽  
Metka Kordigel Aberšek
Keyword(s):  
Elementary School ◽  
Reading Comprehension ◽  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Educational Process ◽  
Tutoring Systems ◽  
8Th Grade ◽  
On Line ◽  
Print Reading

We live in a time of transition from print reading (off-line) to screen reading (on-line), where the role of the book and other literature is being taken over by different types of electronic devices (computers, tablets, smart phones). In the lives of young people, there is less and less printed media, because it is being pushed out by electronic media. Most written media that is still used is thus bound to the classroom. However, in recent years schools have also become more like e-schools. It is almost impossible to find a school that does not use e-material in its educational process. Research indicates that there are differences in reading comprehension when reading off-line and on-line. In a study in which 78 students from the 8th grade of elementary school participated at the course Technology and science (n=77; 53.2% female), it was shown that in order to overcome this difference, individualised and adaptive Intelligent Tutoring Systems (ITS) can be used. The evaluation of the results also indicates that, for such a form of ITS, there is still plenty of space for optimisation, which is a permanent method of improvement and upgrade in such systems. Key words: reading comprehension, Technology and science, ITS, elementary school.

Artificial Intelligence in Education

2021 ◽  
pp. 256-277
Author(s):  
Rashmi Khazanchi ◽  
Pankaj Khazanchi
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Pedagogical Practices ◽  
Student Centered ◽  
Tutoring Systems ◽  
Artificial Intelligence In Education ◽  
K 12 ◽  
Insight Into

Current educational developments in theories and practices advocate a more personalized, student-centered approach to teach 21st-century skills. However, the existing pedagogical practices cannot provide optimal student engagement as they follow a ‘one size fits all' approach. How can we provide high-quality adaptive instructions at a personalized level? Intelligent tutoring systems with embedded artificial intelligence can assist both students and teachers in providing personalized support. This chapter highlights the role of artificial intelligence in the development of intelligent tutoring systems and how these are providing personalized instructions to students with and without disabilities. This chapter gives insight into the challenges and barriers posed by the integration of intelligent tutoring systems in K-12 classrooms.

Artificial Tutoring Systems: What Computers Can and Can't Know

1997 ◽  
Vol 16 (2) ◽  
pp. 107-124 ◽  
Author(s):  
Theodore W. Frick
Keyword(s):  
Intelligent Tutoring Systems ◽  
Clinical Evidence ◽  
Intelligent Tutoring ◽  
Computer Systems ◽  
Classroom Teachers ◽  
Language Understanding ◽  
Tutoring Systems ◽  
Natural Systems ◽  
Teachers And Students

After more than four decades, development of artificially intelligent tutoring systems has been constrained by two interrelated problems: knowledge representation and natural language understanding. G. S. Maccia's epistemology of intelligent natural systems implies that computer systems will need to develop qualitative intelligence before these problems can be solved. Recent research on how human nervous systems develop provides evidence for the significance of qualitative intelligence. Qualitative intelligence is required for understanding of culturally bound meanings of signs used in communication among intelligent natural systems. S. I. Greenspan provides neurological and clinical evidence that emotion and sensation are vital to the growth of mind—capabilities that computer systems do not currently possess. Therefore, we must view computers in education as media through which a multitude of teachers can convey their messages. This does not mean that the role of classroom teachers is diminished. Teachers and students can be empowered by these additional learning resources.

scholarly journals Fuzzy Logic for Refining the Evaluation of Learners’ Performance in Online Engineering Education

2019 ◽  
Vol 4 (6) ◽  
pp. 50-56 ◽  
Author(s):  
Akrivi Krouska ◽  
Christos Troussas ◽  
Cleo Sgouropoulou
Keyword(s):  
Fuzzy Logic ◽  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Intelligent Tutoring System ◽  
Educational Process ◽  
Logic Model ◽  
Traditional Learning ◽  
Student Centered ◽  
Student Centered Learning ◽  
Tutoring Systems

Intelligent tutoring systems have been widely used for optimizing the educational process by creating a student-centered learning environment. As a matter of fact, an integral part of intelligent tutoring systems is the evaluation of the learners’ performance. In traditional learning, the instructors calculate the grade of the students derived from the assessment units and other factors, such as the difficulty of the exercises or their effort, in order to produce the final students’ score in the course. However, in most cases, the evaluation of learners’ performance in intelligent tutoring systems takes place by calculating an average grade of students without taking into account the aforementioned factors. In view of the above, this paper presents a novel way for refining the evaluation of students’ performance using fuzzy logic. As a testbed for our research, we have designed and implemented an intelligent tutoring system holding social networking characteristic for teaching the engineering course of “Compilers”. More specifically, the system is responsible for acquiring information about students such as their grades, the kinds of misconceptions, the level of tests’ difficulty as well as their effort including their social interaction, i.e. participation in forums, making comments in posts and posting regarding the educational process. Taking these into consideration, fuzzy logic model diagnoses the accuracy of students’ grade and the system suggests that the instructor redefine students’ grade properly. Our system was evaluated using t-test and the results show high accuracy and objectivity in the evaluation of students’ performance.

The effectiveness of intelligent tutoring systems on K‐12 students' reading comprehension: A meta‐analysis

2019 ◽  
Vol 50 (6) ◽  
pp. 3119-3137 ◽  
Author(s):  
Zhihong Xu ◽  
Kausalai (Kay) Wijekumar ◽  
Gilbert Ramirez ◽  
Xueyan Hu ◽  
Robin Irey
Keyword(s):  
Reading Comprehension ◽  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Meta Analysis ◽  
Tutoring Systems ◽  
K 12

scholarly journals A method for learning scenario determination and modification in intelligent tutoring systems

2011 ◽  
Vol 21 (1) ◽  
pp. 69-82 ◽  
Author(s):  
Adrianna Kozierkiewicz-Hetmańska ◽  
Ngoc Nguyen
Keyword(s):  
Learning Styles ◽  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Educational Process ◽  
Learning System ◽  
Optimal Learning ◽  
Tutoring Systems ◽  
Learning Path ◽  
E Learning ◽  
Using Data

A method for learning scenario determination and modification in intelligent tutoring systemsComputers have been employed in education for years. They help to provide educational aids using multimedia forms such as films, pictures, interactive tasks in the learning process, automated testing, etc. In this paper, a concept of an intelligent e-learning system will be proposed. The main purpose of this system is to teach effectively by providing an optimal learning path in each step of the educational process. The determination of a suitable learning path depends on the student's preferences, learning styles, personal features, interests and knowledge state. Therefore, the system has to collect information about the student, which is done during the registration process. A user is classified into a group of students who are similar to him/her. Using information about final successful scenarios of students who belong to the same class as the new student, the system determines an opening learning scenario. The opening learning scenario is the first learning scenario proposed to a student after registering in an intelligent e-learning system. After each lesson, the system tries to evaluate the student's knowledge. If the student has a problem with achieving an assumed score in a test, this means that the opening learning scenario is not adequate for this user. In our concept, for this case an intelligent e-learning system offers a modification of the opening learning scenario using data gathered during the functioning of the system and based on a Bayesian network. In this paper, an algorithm of scenario determination (named ADOLS) and a procedure for modifying the learning scenario AMLS with auxiliary definitions are presented. Preliminary results of an experiment conducted in a prototype of the described system are also described.

scholarly journals Artificial Intelligence and Its Role in Education

2021 ◽  
Vol 13 (22) ◽  
pp. 12902
Author(s):  
Sayed Fayaz Ahmad ◽  
Mohd. Khairil Rahmat ◽  
Muhammad Shujaat Mubarik ◽  
Muhammad Mansoor Alam ◽  
Syed Irfan Hyder
Keyword(s):  
Artificial Intelligence ◽  
Significant Role ◽  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Education Sector ◽  
Access To Education ◽  
Tutoring Systems ◽  
Smart Learning ◽  
Modern Methods

The objective of this study is to explore the role of artificial intelligence applications (AIA) in education. AI applications provide the solution in many ways to the exponential rise of modern-day challenges, which create difficulties in access to education and learning. They play a significant role in forming social robots (SR), smart learning (SL), and intelligent tutoring systems (ITS) to name a few. The review indicates that the education sector should also embrace the modern methods of teaching and the necessary technology. Looking into the flow, the education sector organizations need to adopt AI technologies as a necessity of the day and education. The study needs to be tested statistically for better understanding and to make the findings more generalized in the future.

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