Inputgetrieben

Inputgetrieben is an adjective used in German to describe processes, models, or systems whose behavior is determined primarily by external input signals or data. The term is a calque from the English “input-driven” and is common in fields such as information science, control theory, economics, and education. An inputgetrieben approach emphasizes the role of observable inputs in shaping outcomes, as opposed to reliance on internal states, predefined objectives, or generated outputs alone.

In practice, inputgetrieben systems react to or are guided by input data. In data science and machine learning, they rely on the available inputs to determine predictions or actions, often prioritizing real-world signals over theory-driven assumptions. In control and automation, inputgetriebene controllers adjust behavior based on sensor readings or user commands. In language learning and education, inputgetriebenes Lernen describes learning that is primarily shaped by exposure to input (spoken, written, or multimedia) rather than explicit instruction or internal goals.

In economics, inputgetriebenes Wachstum refers to growth driven largely by the accumulation of inputs such as capital, labor, or natural resources, rather than by advances in total factor productivity. This usage highlights policy implications focused on input expansion and resource allocation, rather than solely on efficiency improvements.

The term is used across domains with varying specifics, and its exact meaning should be clarified in context. See also: data-driven, input-driven control, input-driven learning.