Abstract
Control of online evaluations online modality using artificial vision is a qualitative study that is based on the method of analysis and bibliographic conceptualization of 59 scientific articles taken from a total of 123 existing in the various bibliographic databases. The study began by addressing the issues concerned from the importance and understanding of online assessment control in the academic context to the types of computer vision algorithms and the main applications. To achieve this, the guided bibliographic technique was used through four research questions: What problems exist in online evaluations? What techniques have been used to detect plagiarism in online evaluations? What machine vision algorithms are used? What are the main detection and monitoring tasks that computer vision algorithms are capable of performing? The research questions allowed us to investigate problems of academic dishonesty, ease of committing plagiarism, online assessment control techniques, plagiarism detection techniques, object tracking algorithms, region-based algorithms, grid-based algorithms, face detection, detection of gestures and object detection. To determine the most relevant articles, three phases were considered. Phase one took into account inclusion criteria such as scientific articles, reviews, conferences evaluated by peers, studies carried out on the artificial vision algorithm, as well as online evaluations. The second phase gave the word search chain greater relevance to the bibliographic review and to provide it with adequate capacity to answer the four research questions, was ordered by year of publication, the topic, abstract and keywords were reviewed. Phase three reviewed by sections corresponding to the introduction and conclusion to know if the information contributes and if it is related to the research questions. The results of the information extracted from the scientific articles show that there is a need for supervision of students during online assessments, which can occur through computer vision algorithms, since there have been significant advances in these areas.
Highlights
IntroductionUniversal Journal of Educational Research 9(5): 1000-1013, 2021 took over university classrooms facilitating student participation and minimizing the use of resources changing traditional learning models and evaluating practices [1]
It has been three years since everyone in the world has become internet savvy
Technological advances applied to online evaluations are favorable to educational environments, there have been negative practices such as academic plagiarism since there is not an adequate control system that prevents such practices yet
Summary
Universal Journal of Educational Research 9(5): 1000-1013, 2021 took over university classrooms facilitating student participation and minimizing the use of resources changing traditional learning models and evaluating practices [1] This innovative tendency is enthusiastically welcome, there is resistance to change since online tests by some. Technological advances applied to online evaluations are favorable to educational environments, there have been negative practices such as academic plagiarism since there is not an adequate control system that prevents such practices yet For this reason, the use of the latest artificial vision mechanisms seem optimum since they are capable of analyzing facial expressions and identifying over 9000 types objects used to obtain information in real time helping the test taker [3]. This tool offers a clear balance between speed and precision offering satisfactory results within an extensive range
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