Analysis and Design of Personalized Learning System Based on Decision Tree Technology

2020 ◽  
pp. 119-126
Author(s):  
Qiaoying Ming ◽  
Ran Li
Keyword(s):  
Decision Tree ◽  
Personalized Learning ◽  
Learning System ◽  
Analysis And Design

Applying design patterns to decision tree learning system

1998 ◽  
Vol 23 (6) ◽  
pp. 111-120 ◽  
Author(s):  
Gou Masuda ◽  
Norihiro Sakamoto ◽  
Kazuo Ushijima
Keyword(s):  
Decision Tree ◽  
Design Patterns ◽  
Learning System ◽  
Decision Tree Learning

Design of English reading and learning management system in college education based on artificial intelligence

2021 ◽  
pp. 1-10
Author(s):  
Fen Zhang ◽  
Min She
Keyword(s):  
Artificial Intelligence ◽  
Model Performance ◽  
College Education ◽  
Personalized Learning ◽  
Learning System ◽  
Model Function ◽  
English Reading ◽  
Function Modules ◽  
Learning Platforms ◽  
Learning Management

English reading learning in college education is an efficient means of English learning. However, most of the current English reading learning platforms in colleges and universities only put different English books on the platform in electronic form for students to read, which leads to blindness of reading. Based on artificial intelligence algorithms, this paper builds model function modules according to the needs of English reading and learning management in college education and implements system functions based on artificial intelligence algorithms. Moreover, according to the above design principles of personalized learning model and the characteristics of personalized network learning, this paper designs a personalized learning system based on meaningful learning theory. In addition, this article verifies and analyzes the model performance. The research results show that the model proposed in this paper has a certain effect.

Machine-learning algorithm as a prognostic tool in non-obstructive acute-on-chronic kidney disease in the cat

2021 ◽  
pp. 1098612X2110012
Author(s):  
Jade Renard ◽  
Mathieu R Faucher ◽  
Anaïs Combes ◽  
Didier Concordet ◽  
Brice S Reynolds
Keyword(s):  
Machine Learning ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Decision Tree ◽  
Diagnostic Performance ◽  
Clinical Signs ◽  
Learning System ◽  
Clinical Severity ◽  
Medium Term ◽  
Term Survival

Objectives The aim of this study was to develop an algorithm capable of predicting short- and medium-term survival in cases of intrinsic acute-on-chronic kidney disease (ACKD) in cats. Methods The medical record database was searched to identify cats hospitalised for acute clinical signs and azotaemia of at least 48 h duration and diagnosed to have underlying chronic kidney disease based on ultrasonographic renal abnormalities or previously documented azotaemia. Cases with postrenal azotaemia, exposure to nephrotoxicants, feline infectious peritonitis or neoplasia were excluded. Clinical variables were combined in a clinical severity score (CSS). Clinicopathological and ultrasonographic variables were also collected. The following variables were tested as inputs in a machine learning system: age, body weight (BW), CSS, identification of small kidneys or nephroliths by ultrasonography, serum creatinine at 48 h (Crea48), spontaneous feeding at 48 h (SpF48) and aetiology. Outputs were outcomes at 7, 30, 90 and 180 days. The machine-learning system was trained to develop decision tree algorithms capable of predicting outputs from inputs. Finally, the diagnostic performance of the algorithms was calculated. Results Crea48 was the best predictor of survival at 7 days (threshold 1043 µmol/l, sensitivity 0.96, specificity 0.53), 30 days (threshold 566 µmol/l, sensitivity 0.70, specificity 0.89) and 90 days (threshold 566 µmol/l, sensitivity 0.76, specificity 0.80), with fewer cats still alive when their Crea48 was above these thresholds. A short decision tree, including age and Crea48, predicted the 180-day outcome best. When Crea48 was excluded from the analysis, the generated decision trees included CSS, age, BW, SpF48 and identification of small kidneys with an overall diagnostic performance similar to that using Crea48. Conclusions and relevance Crea48 helps predict short- and medium-term survival in cats with ACKD. Secondary variables that helped predict outcomes were age, CSS, BW, SpF48 and identification of small kidneys.

scholarly journals The system of personalized instruction in school education: problems of implementation and adaptation

2020 ◽  
pp. 142-152
Author(s):  
Polina O. Kraynova ◽  
Alexey S. Obukhov
Keyword(s):  
General Education ◽  
Personal Characteristics ◽  
Personalized Learning ◽  
Educational Process ◽  
Learning System ◽  
High Quality Research ◽  
Global Trends ◽  
Learning Platform ◽  
The Usa ◽  
The Individual

In the context of global trends in the humanization of education, issues of differentiation, individualization and personalization of education are actively discussed. At the same time, the key question remains – how to preserve the individual capabilities, interests and needs of each student while maintaining collective learning formats? How to take into account the personal characteristics and capabilities of each when passing and mastering general education programs? One such solution was the PCBL personalized learning platform developed in the USA. Currently, the Khoroshevskaya school is introducing and adapting this platform to the Russian conditions of education. The article examines the specific case of implementing a system of personalized competency-based education in a separate school – what problems, barriers and difficulties are encountered in its implementation. The study is built in the logic of qualitative research on the basis of high-quality research interviews with the main participants in the educational process in the context of introducing a personalized learning system.

scholarly journals A design of a multi-agent recommendation system using ontologies and rule-based reasoning: pandemic context

2022 ◽  
Vol 12 (1) ◽  
pp. 515
Author(s):  
Amina Ouatiq ◽  
Kamal ElGuemmat ◽  
Khalifa Mansouri ◽  
Mohammed Qbadou
Keyword(s):  
Mental State ◽  
Adaptive Systems ◽  
Recommendation System ◽  
Unified Modeling Language ◽  
Social Situation ◽  
Personalized Learning ◽  
Learning Objects ◽  
Learning System ◽  
Holistic View ◽  
Rule Based

Learners attend their courses in remote or hybrid systems find it difficult to follow one size fits all courses. These difficulties have increased with the pandemic, lockdown, and the stress they cause. Hence, the role of adaptive systems to recommend personalized learning resources according to the learner's profile. The purpose of this paper is to design a system for recommending learning objects according learner's condition, including his mental state, his COVID-19 history, as well as his social situation and ability to connect to the e-learning system on a regular basis. In this article, we present an architecture of a recommendation system for personalized learning objects based on ontologies and on rule-based reasoning, and we will also describe the inference rules required for the adaptation of the educational content to the needs of the learners, taking into account the learner’s health and mental state, as well as his social situation. The system designed, and validated using the unified modeling language (UML). It additionally allows teachers to have a holistic view of learners’ progress and situations.

scholarly journals Methodological aspects of the web course of chemical disciplines for non-chemical specialties in universities

2020 ◽  
Vol 1 (1) ◽  
pp. 37-42
Author(s):  
Naila Guliyeva ◽  
Keyword(s):  
Inorganic Chemistry ◽  
Online Training ◽  
Personalized Learning ◽  
Learning System ◽  
Learning Platform ◽  
Web Course ◽  
Effective Use ◽  
Methodological Aspects ◽  
Theoretical Foundations ◽  
The Web

The article analyzes the possibilities of effective use of interactive learning elements, which is a learning platform designed to provide teachers, administrators and students with a reliable, safe and comprehensive learning system to create a personalized learning environment. It is acknowledged that the utilization of online training tools has shown to be effective for studying the “Theoretical Foundations of Chemistry” and “Inorganic Chemistry” disciplines.

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