Introduction
The growth of opportunities presented by computer technologies in the field of education has led to the emergence of such a notion as epistemic cognition. According to Johanes (2017), this concept “refers to the process of thinking about one’s forms of knowledge and ways of knowing” (p. 61). The author’s baseline is the Massively Open Online Courses (MOOCs) program that aims at providing free access to educational resources for residents from all over the world (Johanes, 2017).
The adaptive and personalized forms of education that these courses support allow students to acquire the necessary knowledge effectively and gain valuable skills that are necessary for the development of personal and professional potential. According to the author, epistemological cognition is one of the forms supported by MOOCs (Johanes, 2017). The purpose of the work is to describe the origin of this model, the existing findings, and the types of such an educational approach. As an auxiliary database, a table is used as a convenient way to display the varieties of epistemic cognition, and different studies by other authors are utilized as references.
Main body
The main essence of epistemic knowledge is the acquisition of valuable experience in people’s daily lives. Philosophical doctrines and abstract hypotheses fade into the background, and real actions aimed at gaining valuable experience become the primary object. Johanes (2017) notes that the central reason that prompts the study of this field is the lack of large-scale research on epistemic cognition and its manifestations.
Also, the author considers students the target group for using various models of this concept (Johanes, 2017). The comparative characteristics of the types of epistemic cognition are given on the basis of such criteria as the model’s visualization, their structures, and measurement methods. It is assumed that “a theoretical, empirical, and intuitive basis exists for further epistemic cognition research” (Johanes, 2017, p. 63). The constant emergence of new data contributes to the development of this science and the popularization of its research.
Johanes (2017) examines the qualities of epistemic cognition and calls them affordances. The first one relates to what affects the process of people’s learning and contributes to the acquisition of experience. According to the author, the environment is the main source for evaluating current knowledge and distinguishing assessment methodologies (Johanes, 2017). Particular attention is paid to online research as one of the central objects of work. Epistemic cognition may help to accumulate valuable experience that is necessary for the correct analysis of certain topics. Thus, the first affordance provides for the relationship between the human and the environment as a center of knowledge.
The second one refers to the principles of online pedagogical principles and the learning environment in this sphere. Since MOOCs provide distance learning services, this approach is necessary. As Johanes (2017) argues, “there are various ways that epistemic cognition research can be strategic in creating and studying inclusiveness in online learning environments” (p. 64). Various videos, discussions, projects, and other types of work offered to students contribute to the integrated development of their potential and help to gain a comprehensive view of epistemic practices. Therefore, this affordance deserves discussion and is seen as an essential quality.
Conclusion
At the end of the article, the author offers possible topics for further study of the features of epistemic cognition (Johanes, 2017). Different disciplines are considered the target subjects that allow introducing this concept into the learning process. The opportunities provided by the methodology of epistemic cognition open up significant prospects for students, and new forms of work are evaluated as the ways of increasing the potential of knowledge.
Reference
Johanes, P. (2017). Epistemic cognition: A promising and necessary construct for enriching large-scale online learning analysis. In Proceedings of the Fourth (2017) ACM Conference on Learning@ Scale (pp. 61-69). Cambridge, MA: ACM.