Plexlearning environments are more than geometric spaces.

Plexlearning environments are similar to ecological niches.  According to Julia J. C. Blau and Jeffrey B. Wagman, in their book Introduction to Ecological Psychology: A Lawful Approach to Perceiving, Acting, and Cognizing, “An ecological niche is a specific way an organism relates to the environment it inhabits, how it survives, how it finds shelter, and so on” (p. 24).  They referenced works form M. T. Turvey (2019) to argue that animals (including humans) cannot be understood without the context of their environments and that their environments (more aptly called niches) cannot be properly defined without animals that inhabit them (p. 49).  In a similar fashion, Plexlearners and their environments are inseparable.  As such, Plexlearning environments for knowing and doing consist of dynamic relationships with physical, economic, emotional, and social spaces that are also continuously being updated by socioeconomic factors (family, economics, teachers, politics, community, schools, location, time, Autonomous Technology Actors (ATA), etc.) creating a unique experience, and view of the world, for each Plexlearner.  Concepts of geometric space and Plexlearning environment are therefore rarely the same.

Plexlearning is a schooling and education framework afforded by digital environments.  The framework presumes that digital societies (environments) afford expanded cognitive ecologies and social constructs for ways of knowing and doing in the creation, conveyance, governance, management, politics, and use of knowledge.  Plexlearning is a way of life which involves “digital literacy.”  Digital literacy, along with Autonomous Technology Actors (ATA), transcends biology in a continuous teaching, learning, and aided process.  Plexlearning engagements and relationships creates Plexknowledge which includes, but not limited to, awareness of facts, familiarity with objects or situations, skills acquisitions, and ability to perform desired actions.

In Plexlearning, concepts of geometric space and environment are not always the same.

Autonomous Technology Actors (ATA) are non-human autonomous pedagogical agents in teaching and learning relationships.  ATAs afford pedagogical noticing and serve all stakeholders in teaching and learning digital environments.  Human teacher noticing of student’s learning artifacts as proxies for understanding students’ thinking is well established.  However, in PlexLearning, dashboards for noticing activities are used by all parties (teachers, learners, ATAs, and other stakeholders) to guide, manage resources, motivate, and work on behalf of the learner.  ATAs also curate learning meta-data, and knowledge-artifacts on behalf of the learner.  Knowledge-artifacts are accumulated objects representing personalized learning experiences.

The framework for cognition and learning objectives in Plexlearning is relational (not hierarchal).  This relational taxonomy of learning framework provides a basis for sub-goals, teaching strategies, developmental, and mastery assessment methodologies to meet these goals.  Activities performed to achieve those goals are curriculum specific.  Play is a learning taxonomy node in Plexlearning along with Evaluating, Remembering, Creating, Understanding, Applying, and Analyzing.

Happy couple in love outdoorsPlexlearning affordances enables cost reduction, remove barriers, fill gaps, and build useful socioeconomic infrastructure between formal education, informal learning, entrepreneurship, workforce development, sustainability, career, and vocation management for hopeful and meaningful lives.

Digital society affordances contribute to rapid and often uneven sociocultural and economic changes.   To mitigate ensuing rapid transformations in both rural village and urban neighborhood communities, PlexLearning can be integrated into Research to Practice programs and partnerships that help people achieve equity, participatory parity, and quality-of-life development.

iphone-500291_1280Plexlearning Education Methodology

Plexlearning education methodology is the study of research principles that guide computer mediated learning practices, methods, tools, and language.   The terms Cyberlearning education, mediated education, computer-aided education, and digital education are used interchangeably to describe the creation, conveyance and use of knowledge mediated by networked computing and communications technologies.   Knowledge is defined “as an integrated set of understandings that ultimately can only be constructed by and reside in the mind of the knower [human or otherwise].”

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