Blended Learning Technology Realization Using a Basic Online Course

Lisitsyna, Lubov S.; Senchilo, Marina S.; Efimchik, Evgeniy A.

doi:10.1007/978-981-15-5584-8_15

Cited by 5 publications

(3 citation statements)

References 9 publications

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“…The data captured by sensors are primarily in different formats. 4. Data generation: The sensors embedded in the SLE capture instantaneous information generated at a fast rate.…”

Section: Data Formatsmentioning

confidence: 99%

A Deep Learning Model for Education Analytics – A Short Review

Kuppusamy¹,

K.²

2022

CTRJ

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Integrating deep learning with learning management systems can result in intelligent course material and high accuracy without any manual intervention. This paper reviews factors that influence deep learning in education, and hence this article aims to achieve deep learning on a large scale in the smart education system with a deep learning model to predict. The proposed model can reduce development and maintenance costs, reduce risks, and facilitate communication between stakeholders.

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“…The data captured by sensors are primarily in different formats. 4. Data generation: The sensors embedded in the SLE capture instantaneous information generated at a fast rate.…”

Section: Data Formatsmentioning

confidence: 99%

A Deep Learning Model for Education Analytics – A Short Review

Kuppusamy¹,

K.²

2022

CTRJ

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“…For effective training of specialists in various sectors of the economy, including in the food industry, Russian and foreign authors presented research and development in the field of computer simulators for personnel training [2,3] and other similar automated control systems for the educational process [4][5][6][7]. One of the most important functions of such systems -monitoring knowledge and skills during the learning process -in practice often comes down to either knowledge testing [8], which has shortcomings, or to time-consuming "manual" checking by the teacher of the results of assignments.…”

Section: Introductionmentioning

confidence: 99%

Automated evaluation models and algorithms for optimizing exercise assessments in food production training complexes

Polevshchikov,

Litvinova

2024

ITM Web Conf.

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The article is devoted to the development of models and algorithms of intelligent training complexes for training engineering specialists in the food industry. A method has been developed for comprehensive assessment of the quality of performing exercises on optimization problems in virtual environment. The method differs from the known ones in many parameters that determine the structure and specificity of these problems. It is formalized based on of fuzzy sets that describe incomplete knowledge when comparing the mathematical model of the problem created by the student with the reference one. The use of intelligent training complexes, in the software of which the presented method is implemented, will allow for ongoing monitoring and self-monitoring of students’ knowledge and skills when studying disciplines in the field of developing software for automated control systems for production processes. The use of intelligent training complexes ensures the collection and analysis of data on the dynamics in the formation of professional knowledge and skills among students in the development of mathematical software for automated control systems. Accordingly, the time for conducting control activities for the teacher is reduced, and the accuracy of the results of monitoring the formation of knowledge and skills among students is increased.

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“…The fulfillment of this task is largely facilitated by such a trend in modern education as the development and use of automated educational process management systems. Among the scientific works relevant to the problems of development and application of these systems in training the above specialists, one can highlight works in the field of e-learning and distance technologies [1][2][3], automation of assessment of knowledge and skills [4][5][6], modeling of processes of knowledge and skills formation [7], creation of virtual laboratories [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Automated skills control of food production specialists using a training system

Polevshchikov,

Kravchenko

2023

E3S Web of Conf.

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The article is devoted to the development of information technologies for monitoring knowledge and skills in the training of engineering specialists in the field of food production. A methodology for monitoring the initial skills of these specialists has been developed based on a training and teaching subsystem. The technique consists of automatically generating and evaluating practical tasks using mathematical models of objects of professional activity. The use of an automated information system in the educational process, which includes implementing the specified training and education subsystem functions, will allow to reduce the teacher’s time for preparing and checking assignments; increase the accuracy of assessment of assignments during control, reduce the subjectivity of assessment (compared to checking an assignment by a teacher); reduce the time a student waits for an assessment. The considered methodology will be implemented in the form of automated information system software modules for monitoring knowledge and skills during the training of specialists. The automated information system prototype is currently used at ROSBIOTECH and MSUTU n.a. K.G. Razumovsky when training students in areas of training in the field of automation, informatization, robotization of technological and business processes.

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Blended Learning Technology Realization Using a Basic Online Course

Cited by 5 publications

References 9 publications

A Deep Learning Model for Education Analytics – A Short Review

A Deep Learning Model for Education Analytics – A Short Review

Automated evaluation models and algorithms for optimizing exercise assessments in food production training complexes

Automated skills control of food production specialists using a training system

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