A Model of an Online Evaluation System for STEM Education

Đurović, Gordan; Dlab, Martina Holenko; Hoić-Božić, Nataša

doi:10.23919/mipro.2019.8756675

Cited by 7 publications

(3 citation statements)

References 11 publications

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“…Firstly, researchers are trying to highlight some common grounds for the effectiveness of such programs and on their basis develop a universal methodology or structure that would allow creating working and easy-to-implement training sequences [3,11,23,30]. Secondly, methods for assessing the real effectiveness of such programs are being studied, in particular, evaluation teachers' work, whose role in STEM is especially great [2,20]. Thirdly, there is a discussion about the boundaries of using online STEM courses and how actually such an approach can be applied to this teaching methodology [6,26].…”

Section: Discussionmentioning

confidence: 99%

“…The online courses can include the use of YouTube videos, as well as special videos posted in the cloud-based resources with limited access, recorded classroom lessons according to the STEM methodology, also, teacher's comments and solutions to their tasks online in Records [18]. All these types of video materials are widely used in structured STEM programs developed and implemented by European and American universities [19,20]. Researchers note that the video materials are the most popular and easy to perceive by the latest generations of students who are already accustomed to this format of presenting information in general on the Internet [21].Videos act as an incorporating aspects of visible personal experience into the learning process [17].…”

Section: Introductionmentioning

confidence: 99%

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Online Technologies in STEM Education

Liu

Чубаркова

Kharakhordina

2020

Int. J. Emerg. Technol. Learn.

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STEM education has become the normative base for teaching natural sciences, physical-mathematical disciplines and engineering sciences in a number of coun-tries. This technique has become the basis for a series of reforms for secondary and higher education in the USA, Australia, and some other countries. The meth-od involves the integration of training in the fields of mathematics, technical spe-cialties, scientific research and engineering. The widespread use of this technique and its active research throughout the world over the past ten years is due to the need to improve the quality of technical education and the ever-increasing rate of technological progress. This research is devoted to studying the impact of the STEM education introduction for 3rd year students of technical and pedagogical departments for improving the quality of training. The study involved two groups of students from two universities in Russia and China. The sample consisted of 316 people from each university, and the same amount was for control group to verify the results. The two study groups underwent training using two different STEM methodologies - “amalgam” and “interconnect”, which involve varying degrees of integration of various academic subjects within the coordinated STEM education. Both study groups used online-education integrated with STEM that helped to significantly increase the involvement of students in the learning pro-cess. All three groups passed pre-tests and post-tests on the learning outcomes before and after the introduction of the STEM education. The average grades re-ceived by students on studied disciplines show that the STEM education increas-es the academic performance with the statistical error of the study exceeded. The introduction of the “interconnect” method, which implies a greater integration of subjects during the training, showed provably higher results than the “amalgam” method. However, this study cannot be used to assess the quality and capabilities of each of these methods, since such an assessment requires additional research.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Online Technologies in STEM Education

Liu

Чубаркова

Kharakhordina

2020

Int. J. Emerg. Technol. Learn.

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“…With the continuous development of Internet communication technology and computer technology, traditional classroom teaching model is constantly impacted by online education model [1][2][3][4][5]. Currently, the best education and teaching resources can be shared across the globe, and the number of online learning courses is on the rise [6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

An Evaluation Model of Online Autonomous English Learning Efficiency Using an Artificial Neural Network

Zhao¹,

Li²,

Feng³

2022

Int. J. Emerg. Technol. Learn.

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Traditional classroom teaching model is constantly impacted by online education model. To enhance the online English learning efficiency of college students, one of the primary paths is to cultivate their autonomous learning ability. However, the existing research is limited to quantitative research. Therefore, this paper devises an evaluation model of online autonomous English learning efficiency based on artificial neural network. Firstly, the students participating in online English learning were classified, the evaluation indices of online autonomous English learning efficiency were determined and weighed, and the classification method was introduced for the evaluation results. Next, the improved particle swarm optimization (PSO) was adopted to optimize the traditional backpropagation neural network (BPNN). The improved BPNN was employed to evaluate the online autonomous English learning efficiency. The superiority of the improved model was demonstrated through experiments.

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A systemic review of AI for interdisciplinary learning: Application contexts, roles, and influences

Cai,

Zhu,

2024

Educ Inf Technol

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A Model of an Online Evaluation System for STEM Education

Cited by 7 publications

References 11 publications

Online Technologies in STEM Education

Online Technologies in STEM Education

An Evaluation Model of Online Autonomous English Learning Efficiency Using an Artificial Neural Network

A systemic review of AI for interdisciplinary learning: Application contexts, roles, and influences

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