Exhibit Hall

MazeFire Games for Life and Physical Sciences: Reflective Learning Meets Neural Network Theory

Presented by: MazeFire, LLC

Strand: Higher Education

MazeFire.com offers reflective learning experiences where students navigate a virtual maze and have time to reflect upon answer choices, images, and TIPS while also acquiring and applying knowledge to solve the maze puzzle. Our website includes many open access STEM collections tailored to college and AP-high school course levels and these games are prized as self-review tools while also being fun to project and play in class. The maze environment facilitates self-critique because students are NOT given the answers, but must instead figure out the correct answers to find their way to the maze exit—where they may gain additional rewards e.g. extra credit or seeing questions that may be on an upcoming exam. 

Northeastern University’s patented Digital Maze games are one class of reflective learning experience, but we suggest that educators and EdTech companies should explore other reflective learning scenarios so as to boost neuronal and network learning processes. All cognitive advancement depends upon motivation and synaptic learning mechanisms, but the grind of incremental, forced knowledge additions is tedious and saps energy. This is because new “items” are being forced into neuronal knowledge architectures (KAs) of immense complexity. Cortical integration takes time (McClelland et al. 1995; McClelland, 2013), because our brains must sift through extant KAs while storing and evaluating new items. Our reflective Digital Maze games enable subconscious operations: each question is an independent puzzle and student motivation and focus leads to the formation of new cognitive (neuronal) connections and the concomitant strengthening of neocortical information nodes.

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