How can learning be distributed and accelerated with access to digital resources and specialized tools and what are several implications of learning of math and science just in time and on demand?
Knowledge is actively built and socially constructed upon prior conceptions and personal theories. Learning views do not require specific pedagogy necessarily, though invented constructs imposed on phenomena are socially negotiated, then validated as public knowledge. Technology enhances distributed learning, challenging ideas through discrepant events while introducing multiple ways of seeing. Learners form communities of practices through cultural apprenticeship co-constructing knowledge (Driver et al., 1994), though inquiry requires guidance being unlikely that inexperienced students learn through pure discovery. Teachers gradually withdraw support as students connect plausible mental representations towards symbolic convention, where intervention helps make sense of further action. Meaning is constructed in conversation resolving disequilibrium knowledge schemas, inducing cognitive conflict along with social interaction to provide multiple perspectives. Teachers recognize students hold plural conceptions given social context, structuring tasks to internalize and enculture experiential evidence. Students develop common sense reasoning using everyday language and pragmatic understanding rather than adopting coherent world picture, leveraging models for scope.
Globe provides universal access to employ natural curiosity, actively participating with distributed collaborators, researching spatial-temporal data. For accuracy, training the trainer ensures first line of defense against erroneous data (Butler and MacGregot, 2003). Systems provides integrated understanding with graphical, visual and technical tools, enabling international cooperation with multiple languages across isolated communities. Student interaction with adult professionals offers authenticity, enhancing commitment and quality assurance. Given uniform classification systems and protocols, sampling techniques perform over 80% accuracy, where ongoing collection allows for durable, low-cost, long-term stability, empowering students to do responsible science. Active research projects and learner involvement become valuable incentive to improve analytical interpretation, supplementing classroom activities to make informed inferences. Motivational factors like challenge, fantasy and curiosity sustain goal-directed behaviour, with challenge neither too steep or simple providing novelty, interest and importance (Srinivasan et al., 2006). Working memory allows for simultaneous processing and information preservation, providing various worked out examples as effective strategy. Challenges with time availability and systematic schedules need to be overcome, focusing on fundamental science content and method. Debugging breadboard components is time consuming, fraught with variables to address prior knowledge, ability and motivation. Curiously although simulations were less cost expensive, participants deemed software as fake unable to provide authentic experience, resulting in little quantitative difference between physical equipment (Srinivasan et al., 2006). Users described how not knowing background made practical training difficult let alone theoretical, where both real hardware and simulation laboratory provide incomplete solutions.
Science in visiting hands-on interactive centers allow free-choice learning guided by well-formed interests. Leisure settings provide brief, moderately structured activity while retaining considerable personal control. Visitors as active meaning seekers balance learning and entertainment categorized into five broad motivational categories: Explorers, Facilitators, Hobbyists, Experience seekers, Rechargers (Falk and Storksdieck, 2010). Recollections of exhibits highlight personal curiosity, excitement, allowing faster and better learning, motivated by personal curiosity. Instead of disliking school for reading without application and witness in real life, free-choice learning offers realistic expectations over compulsory. Fascinating objects help crystallize meaning to pursue learning satisfaction without external validation, where genuine openness to learn immersed within setting minimizes performance mentality.
Butler, D. M., & MacGregor, I. D. (2003). globe: Science and education. Journal of Geoscience Education, 51(1), 9-20. doi:10.5408/1089-9995-51.1.9
Driver, R., Asoko, H., Leach, J., Mortimer, E., & Scott, P. (1994). Constructing scientific knowledge in the classroom. Educational Researcher, 23(7), 5-12.
Falk, J. H., & Storksdieck, M. (2010). Science learning in a leisure setting. Journal of Research in Science Teaching, 47(2), 194-212.
Srinivasan, S., Pérez, L. C., Palmer, R. D., Brooks, D. W., Wilson, K., & Fowler, D. (2006). Reality versus simulation. Journal of Science Education and Technology, 15(2), 137-141.