Comprehensible Input is the central hypothesis of Second Language Acquisition (SLA) proposed by linguist Stephen Krashen (1982). It posits that humans acquire language in only one way: by understanding messages. The hypothesis states that acquisition occurs when a learner is exposed to input that is slightly above their current level of competence.

If a learner’s current level is $i$, the optimal input level is $i+1$.

• $i+0$ (Too Easy): If the content contains only words and structures the learner already knows, no acquisition takes place.
• $i+10$ (Too Hard): If the content is incomprehensible, it becomes "noise." This triggers the Affective Filter (anxiety), which blocks processing.

According to our internal analysis, the success of Comprehensible Input is mediated by the Affective Filter. High anxiety acts as a cognitive impedance, consuming Working Memory Capacity and preventing the input from reaching the language acquisition device. Therefore, input must be both understandable ($i+1$) and low-stress to be effective.

Our The Immersion Engine is built to solve the "$i+1$ problem." The internet is typically $i+10$ (too hard) for learners.

• Adaptive Rewriting: Our AI plugin analyzes web content and rewrites it to match your specific competency profile ($i+1$).
• Contextual Injection: We inject vocabulary words you are currently learning into this comprehensible text, ensuring you encounter them in a meaningful context rather than in isolation.

1. Krashen, S. D. (1982). Principles and Practice in Second Language Acquisition. Pergamon Press.

2. Sweller, J. (1994). Cognitive Load Theory, learning difficulty, and instructional design. Learning and Instruction, 4(4), 295-312. (Supporting the necessity of reducing load to allow input processing).