Integration of an intelligent tutoring system in a course of computer network design

Verdú, Elena; Regueras, Luisa M.; Gal, Eran; Castro, Javier de; Verdú, María Jesús; Kohen-Vacs, Dan

doi:10.1007/s11423-016-9503-0

Cited by 28 publications

(12 citation statements)

References 38 publications

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“…In the last years, medical education has adopted active learning models to a progressive adaptation to the requirements of the Bologna Process. The current scenario of extensive use of computers and the Internet has created opportunities to improve education by applying different e-learning techniques in courses [ 1 , 2 ]. Consequently, blended learning is replacing traditional face-to-face education and learning spaces (both virtual and physical) are being redesigned to support emerging strategies such as flipped classroom or gamification.…”

Section: Introductionmentioning

confidence: 99%

Effects of competitive learning tools on medical students: A case study

et al. 2018

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ObjectiveCompetitive learning techniques are being successfully used in courses of different disciplines. However, there is still a significant gap in analyzing their effects in medical students competing individually. The authors conducted this study to assess the effectiveness of the use of a competitive learning tool on the academic achievement and satisfaction of medical students.MethodsThe authors collected data from a Human Immunology course in medical students (n = 285) and conducted a nonrandomized (quasi-experimental) control group pretest-posttest design. They used the Mann-Whitney U-test to measure the strength of the association between two variables and to compare the two student groups.ResultsThe improvement and academic outcomes of the experimental group students were significantly higher than those of the control group students. The students using the competitive learning tool had better academic performance, and they were satisfied with this type of learning. The study, however, had some limitations. The authors did not make a random assignment to the control and experimental groups and the groups were not completely homogenous.ConclusionThe use of competitive learning techniques motivates medical students, improves their academic outcomes and may foster the cooperation among students and provide a pleasant classroom environment. The authors are planning further studies with a more complete evaluation of cognitive learning styles or incorporating chronometry as well as team-competition.

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Section: Introductionmentioning

confidence: 99%

Effects of competitive learning tools on medical students: A case study

et al. 2018

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“…The microcanonical Monte Carlo simulation method is based on the concept of microcanonical system [15]. In this simulation technology, β is no longer directly dependent, and the form of the distribution function Z becomes…”

Section: Design and Development Methods Ofmentioning

confidence: 99%

Hybrid Element Heuristic Algorithm Optimizing Neural Network‐Based Educational Courses

Liu

Zheng

2021

Wireless Communications and Mobile Computing

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The rapid development of computer networks has enabled information technology to penetrate many fields, providing unprecedented opportunities for all aspects of our lives. In order to allow students to acquire necessary knowledge and skills through efficient learning, this article studies the design and development of educational technology courses based on hybrid metaheuristic algorithms to optimize neural networks. This paper proposes a metaheuristic algorithm and explains the simulated annealing algorithm and microregular annealing algorithm in detail. Using these algorithms, a mathematical model of the normal scheduling problem was also constructed, and the mathematical model was applied to the design and development of educational technology courses. In addition, the neuron model in the neural network and the activation function of the neural network are discussed from various aspects. In the experiment, according to the needs of students, a learning platform for educational technology courses was designed and developed. The experimental results of this article show that there are significant differences in the starting point of the ability level of learners for different majors. Education majors have a higher level of understanding of educational technology courses; 38.20% of students know well, while art majors have a low level of understanding of education technology courses, with 36.05% of students majoring in art.

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“…A novel framework for curriculum generation (Singh, Ahuja, & Kumar, 2018) was done based on mathematical model and then implemented on field of geo-physics. INTUITEL approach [10] includes an intelligent tutoring system that gives learners recommendations and feedback about what the best learning sequence is for them according to their profile, learning progress, context and environmental influences. Results of INTUITEL show that developed learning sequence for different learners are more suitable for them.…”

Section: Related Workmentioning

confidence: 99%

Ontology-Based Recommender System for a Learning Sequence in Programming Languages

Shishehchi

Zin

Seman

2021

Int. J. Emerg. Technol. Learn.

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The same learning process in educational systems could be boring and time consuming for some learners. This problem arises from the lack of personalized learning sequence for learners with different knowledge level. Recommender systems play an important role in assisting the learners to find suitable learning materials and personalized learning sequence. Use of ontology for knowledge representation in knowledge-based recommender systems would facilitate sharing, reuse and common terminology. Since programming concepts have logical relationships among together so, traditional education systems are more stressful and very time-consuming. This paper aims to propose an ontology based recommender system to present a Personalized Learning Sequence in Programming (PLSP) domain which is depended to learner's knowledge level. A recommender module and, the knowledge base module are integrated together in the proposed framework. The recommender module as the main module in the framework, has three stages which is working based on semantic rules and ontology representation. Evaluation of the system was carried out by comparing the non-recommender system (web-based search) using 32 ICT respondents. Results demonstrate that the participants who used the proposed system spent 1119 seconds to find the suitable learning path in comparison to those who used a non-recommender system (3480 seconds) in the same learning material. It means that learners who follow learning path with PLSP, are more suitable for them. Furthermore, the average mean value of usability test is 4.47, (5 maximum scale) which indicates that the system proved to be useful, was easy to use, and satisfied the users.

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Integration of an intelligent tutoring system in a course of computer network design

Cited by 28 publications

References 38 publications

Effects of competitive learning tools on medical students: A case study

Effects of competitive learning tools on medical students: A case study

Hybrid Element Heuristic Algorithm Optimizing Neural Network‐Based Educational Courses

Ontology-Based Recommender System for a Learning Sequence in Programming Languages

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