Evolving Educational Landscape: Anticipated Changes for 2060

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Table of Contents

Portfolio for the 2060 Educational Environment
Learning Analytics and Educational Assessment in 2060
Works Cited

Portfolio for the 2060 Educational Environment

The changes to occur in the realm of education are going to be quite drastic as the latest technological innovations along with the strategies based on the emergent learning and teaching theories are incorporated into the educational framework. It is assumed that the 2060 educational environment is going to be more communication-driven because of the opportunities that innovative technology has to offer (Gloor 19).

Opportunistic Social-Idea Network

In a very peculiar manner, the focus on the learners individuality and the unique needs that each of the students has is combined with the need to cater to the entire group. Herein the significance of the modern media and the opportunity to create networks for students to work in lies.

Rotating Leadership

The concept of the rotating leadership should also be included in the framework of the 2060 educational process. Particularly, the teacher as an educator and the student as a learner will have to swap their roles to enhance the process of information acquisition and training of the required skills. For instance, learners will need to assume the role of educators in the course of peer assessment, which is an essential tool for promoting active learning and cooperation in a team (Gan and Zhu. 213). The instructors, in their turn, will have to consider the idea of lifelong learning as the means of improving their teaching skills and evolving as educators.

Collective Responsibility

As it has been stressed above, the process of balancing between the needs of students as individuals and the specifics of working with a group can be rather tricky in the educational environment. Therefore, the learners must be aware of the significance of working in a team and being able to cooperate. The specified requirement does not mean that students should put their individual needs aside for the sake of the team; instead, it presupposes that the learners should be capable of cooperating along with articulating their concerns.

Promoting the idea of responsibility as the basis for the students decision-making, it creates the setting in which the target audience can acquire the necessary skills and knowledge willingly and enthusiastically and enjoy performing different kinds of tasks, be it a group work or an individual assignment. On a larger scale, the concept of collective responsibility can be interpreted as the basis for the ethical values of teachers and learners (Chen, Bereiter, and Scardamalia 5).

Technology in the Classroom and How It Affects Social Relations

There is no need to stress that technology defines the efficacy with which teachers demonstrate the application of theory to practice. Visual aid as well as the latest technological innovations that students can view the former with are essential to the successful perception of the material. However, apart from displaying a certain idea, a phenomenon, or a concept, technology can be used as the means of encouraging the communication process between the students and the teacher as well as among the students. Forums, discussion boards, and other tools used for prompting the conversation among the participants of a specific course contribute significantly to the enhancement of communication and, therefore, prompt the knowledge sharing process (Norman 113).

Learning Analytics and Educational Assessment in 2060

Learning analytics is bound to have a huge impact on the process and efficacy of educational assessment in 2060 due to the opportunities of identifying the unique characteristics of learners and incorporating them into the analysis to define the success of their performance. Particularly, the specified tool helps navigate a very large amount of data on learners, including their performance, behavior, learning styles, social, educational, and cultural background, etc. Since the specified information can and should be used as the basis for developing a comprehensive approach toward a group of learners (Jain et al. 577), its significance in the learning environment of 2060 is doubtless.

With a tighter focus on the unique characteristics of learners, the significance of learning analysis si quite obvious; helping identify the characteristics of a student, it prompts the teacher the tools that can be used to help the student improve the current academic score and informs on the further choice of the teaching strategies. In other words, the tool in question can be considered foundational in creating the premises for efficient teaching (Marlone et al. 5).

The process of carrying out the learning analysis, in its turn, can be viewed as quite challenging due to the amount of data that needs to be processed. At this point, the importance of technological innovations, particularly, online databases, deserves to be mentioned. By organizing the necessary information accordingly, one is likely to retrieve a set of essential pieces of information that will ultimately help understand the needs of learners better and come up with the strategy that will promote the further acquisition of knowledge and prompt metacognition and self-directed learning among the students. Therefore, it is likely that the learning analytics strategy is going to become a powerful tool for the choice of a teaching strategy and the enhancement of the learners performance.

Works Cited

Chen, Bodong, Marlene Bereiter, and Carl Scardamalia. Advancing knowledge building discourse through judgments of promising ideas. International Journal of CSCL 10.4 (2015): 127. Print.

Gan, Yongcheng, and Zhiting Zhu. A Learning Framework for Knowledge Building and Collective Wisdom Advancement in Virtual Learning Communities. Educational Technology & Society 10.1 (2007): 206-226. Print.

Gloor, Peter A. Swarm Creativity: A Competitive Advantage Through Collaborative Innovation Networks. New York, NY: Oxford University Press, 2005. Print.

Jain, Lakhmi C., Himansu Sekhar Behera, Jyotsna Kumar Mandal, and Durga Prasad Mohapatra. Computational Intelligence in Data Mining. New York, NY: Springer, 2014. Print.

Marlone, Thomas W., Robert Laubacher, and Chrysanthos Dellarocas. Harnessing Crowds: Mapping the Genome of Collective Intelligence. Boston, MA: Center for Collective Intelligence, 2009. Print.

Norman, Don A. Design of Everyday Things: Revised and Expanded. New York: Basic Books. London: MIT Press (UK edition), 2013. Print.

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