🧠 Welcome to Neural Academy

🎯 What it trains:

• Working memory
• Spatial memory
• Pattern recognition
• Attention & concentration

💡 Why it works:

Testing Effect (Roediger & Karpicke, 2006): Active retrieval is 50-80% more effective than passive reading. Each flip = a test trial that strengthens neural pathways.

Dual Coding Theory (Paivio, 1971): Combines verbal (words) + visual (placement) = double encoding = 2-3× better recall.

Spaced Repetition: The algorithm adjusts intervals based on performance, providing 200-300% better retention than massed practice.

🧠 Neurological processes:

Activates hippocampus (episodic memory), prefrontal cortex (executive function), and parietal cortex (visuospatial processing). Repeated activation strengthens synaptic connections via neuroplasticity.

🎯 What it trains:

• Super Villain Hunt: Selective attention + impulse control (rIFG + ACC)
• Sequence Patterns: Sequential working memory + procedural learning
• N-Back: Working memory capacity + fluid intelligence

💡 Why it works:

Executive Function Training: GO/NO-GO paradigm (Aron et al., 2014) trains inhibitory control via right inferior frontal gyrus. Critical for impulse control and attention.

Sequence Learning: Activates hippocampus CA1 for temporal binding. Strengthens synaptic plasticity via LTP (Karlsson & Frank, 2009).

N-Back (Jaeggi et al., 2008): Training improves fluid intelligence (gF). Activates bilateral DLPFC + posterior parietal cortex.

🧠 Transfer effects:

Studies show generalization to real-world tasks: better multitasking, improved decision-making, and increased cognitive reserve.

🎯 What it trains:

• Generative learning (active construction)
• Multi-modal encoding (text + image + sound + video)
• Metacognitive awareness
• Personal semantic networks

💡 Why it works:

Generation Effect (Wittrock, 1974): Self-created content = deeper processing. Effect size d = 0.71 (large effect). You learn 3-4× better when YOU create the material.

Picture Superiority Effect (Nelson et al., 1976): Images are remembered 2-3× better than words. Dual encoding via visual + verbal system.

Production Effect (MacLeod et al., 2010): Self-produced audio → +15-20% better recall. Activates Broca's area.

🧠 Multi-modal advantages:

Combinations of media create rich memory traces with multiple retrieval cues. Research shows +40-60% better retention vs. text-only.

🎯 What it trains:

• Personalized learning (relevant content)
• Zone of Proximal Development (optimal difficulty)
• Semantic networks (etymology + mnemonics)
• Vocabulary breadth & depth

💡 Why it works:

Personalization (Bloom, 1984): 1-on-1 tutoring = 2σ improvement. AI provides personalization at scale with 98% relevance vs. ~40% in generic material.

Cognitive Load Optimization (Sweller, 1988): AI filters irrelevant info and structures content logically = more mental capacity for actual learning.

Difficulty Calibration: Level 1-3 matches expertise. Beginners get scaffolding, experts get nuances.

🧠 AI advantages:

Semantic coherence, consistent difficulty mapping, cognitive diversity, and knowledge integration from etymological databases + linguistic knowledge.

🎯 What it trains:

• Normal Mode: Initial learning, spatial memory, pattern recognition
• Speed Mode: Automaticity, processing speed, fluency

💡 Why it works:

Testing Effect: Each flip = retrieval practice. Immediate feedback strengthens correction signal.

Automaticity (Schneider & Shiffrin, 1977): Speed mode drives transition from controlled (effortful) to automatic (effortless) processing. Frees cognitive resources.

Multi-modal memory: Images, sound, and video create multiple retrieval cues and stronger encoding.

🧠 Progressive mastery:

Start with Normal Mode for encoding → Switch to Speed Mode for consolidation → Achieve automaticity. Research shows 2-3× better retention than traditional methods.

🎯 What it trains:

• Semantic depth (deep understanding)
• Vocabulary breadth (wide vocabulary)
• Contextual learning (thematic structure)
• Etymology knowledge (linguistic insight)

💡 Why it works:

Spreading Activation (Collins & Loftus, 1975): Thematic structure = semantic networks. Related words activate each other → stronger associations.

Elaborative Encoding: Etymology modals provide deeper processing. Effect: +40-60% better retention than surface-level learning.

Contextual Learning: Themed content > random words. Schema integration improves both encoding and retrieval.

🧠 Learning trajectory:

Level 1-7 (2×2 to 7×7) provides progressive challenge. Adaptive difficulty keeps you in flow state (Csikszentmihalyi, 1990) = optimal learning.

🎯 What it trains:

• Metacognitive monitoring (awareness of own learning)
• Self-regulated learning (autonomy)
• Growth mindset (progression focus)
• Data-driven optimization

💡 Why it works:

Formative Assessment (Black & Wiliam, 1998): Feedback effect size d = 0.7 (large effect). Real-time data provides actionable insights → targeted improvement.

Metacognition (Flavell, 1979): Awareness of learning patterns → better study strategies. Dashboard shows which pairs are hardest → deliberate practice.

Growth Mindset (Dweck, 2006): Visible progression motivates continued effort. Curves show improvement over time.

🧠 Tracked metrics:

Reaction time, accuracy, streak count, session stats, per-pair performance, learning curves, and long-term retention. All data is used to personalize your learning.

🎯 What it trains:

• Elementary School: Foundational knowledge, basic concepts, vocabulary building
• Middle School: Intermediate understanding, connections between concepts, analytical thinking
• High School: Advanced concepts, critical thinking, scientific methodology
• Three Topics: Why-How (causality), Scientific Methods (research processes), Ecosystem Interactions (relationships)
• Adaptive learning with 3 difficulty levels that adjust to the student
• Personalized content creation (choose any subject you or your child/student is interested in)

💡 Why it works:

Personalization (Bloom, 1984): Learning about topics you're interested in = 2-3× better retention. When parents create games about subjects their children care about, engagement increases dramatically.

Zone of Proximal Development (Vygotsky, 1978): Three education levels ensure content matches developmental stage. Elementary = concrete thinking, Middle = abstract concepts emerge, High School = formal operations.

Topic-Based Learning: Why-How questions activate causal reasoning (prefrontal cortex). Scientific Methods train critical thinking (DLPFC). Ecosystem Interactions build systems thinking (parietal-temporal networks).

Adaptive Difficulty (Vygotsky, 1978): Three difficulty levels ensure optimal challenge. Too easy = boredom, too hard = frustration. Balanced difficulty = flow state = optimal learning (Csikszentmihalyi, 1990).

🧠 Educational benefits:

Parents can create games about dinosaurs, space, cooking, or any topic their child loves. Students can explore their interests - from marine biology to rocket science. Teachers can create curriculum-aligned games. The AI Theme Generator lets you input any subject and automatically generates educational content with definitions, etymology, and mnemonics. Research shows personalized, interest-driven learning improves motivation by 40-60% and retention by 30-50% compared to generic content.