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Tackling many of the global, national and local challenges will require communities that are skilled in science-related disciplines. Against a backdrop of climate change, an overdependence on fossil fuels, various concerns about biodiversity loss and global Space trends, future societies will face considerable challenges (Cooper & Berry, 2020). On the other hand, the technical progress is impossible without an appropriate scientific education. As one considers possible scenarios, scientific advances are essential to solve the future prospects. Nowadays the distance learning is an important tool in scientific education (Zawacki-Richter & Naidu, 2016; DeMarco, 2015). The acquisition and analysis of extensive experimental data as well as the control of complex experiments are barely imaginable without the use of computer simulations for both electronic structures and nanoscale models to explore the laws of physics and technology.
In the era of high technologies, many problems of both scientific and technological progress could be solved utilising very complex, often unique, technological equipments and scientific instruments. Therefore, the use of such tools, often costly, becomes a key for effective educational process. Moreover, to ensure the efficiency of studying process, scientific educational qualifications have been developed on the outcomes based criteria and proficiency, while taking advantage of new pedagogical strategies and educational technologies.
During the past 30 years of the web and information technology development, the e-learning systems have been widely used in higher University’s education of students (Kim & Bonk, 2006; Keengwe et al., 2012; Andoh et al., 2020; Krasnova L.V. et al., 2020; Vicente et al., 2021). Some studies examine how students’ scientific competencies are affected by their outlooks (see, for instance, in Zhu, 2019). In particularly, interest in science directly affects the efficiency for the science education and other aspects as well. Growing the e-learning use results in dedicated research on the factors influencing student’s attitudes toward e-learning (Fuller, 2012; Kennepohl et al., 2005).
Experimental work by students at the initial levels of scientific education has been traditionally arranged in rediscovering established concepts and ideas, in demonstration of the concepts taught in the classroom or, in the case of inquiry‐based scientific programs, in teaching the concepts. On the contrary, non‐laboratory practical works, especially simulations at any levels, could be used for total different reasons. Making complex natural and scientific systems accessible through computer-based models, students can practice in their ability for evidence-based predictions and communication understanding (Lally & Forbes, 2019). They are best used to help students in achieving specific cognitive skills (such as analysis, synthesis and evaluation) needed for both practicing science and carrying out scientific inquiry.
Interactive software simulations enter the mainstream science education. Their effects on cognition and learning are often framed interacting the information processing that underlines the scientific problem solution and conceptual organization of the learning. It should be underlined that many research papers (Lindgren & Schwartz, 2009; Kathleen & Smetana, 2012; Chen et al., 2020; Aslan et al., 2021) report evaluation of simulations impact on perception and spatial learning, because most simulations are of a 3D-spatial format, while the pedagogical goal is in promoting an interest for learning.