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In practical laboratory classes students traditionally receive data by reading from a measurement device (ruler, clock, voltmeter, etc.) or digitally as files in exchange formats such as CSV (comma separated value). In many cases these data have to be processed later using non-linear regression, here referred to as curve fitting. Therefore, analog data first have to be digitalised and imported to a data analysis and visualisation program, which is often commercial and requires installation. In this paper we present an alternative concept fusing open-source community tools into a single page web application facilitating data acquisition, visualisation, analysis via non-linear regression and further post processing usable for error calculations. We demonstrate the e-learning potential of this web application accessible at curvefit.tu-chemnitz.de in the context of acquired data as typically obtained in physical laboratory classes from undergraduate studies. A prototype workflow for the topic 'specific electric resistance determination' is presented along with a technical description of the basic web technology used behind. Restrictions, such as limited portability or cumbersome ways to share results electronically between student and supervisor as occurring in traditional software applications are overcome by enabling export via URL. The discussion is complemented by thorough comparison of curve fitting web applications with focus on their capability to be adaptable to user-specific models (equations) as faced by (undergraduate) students in the context of their education in laboratory classes in natural and life sciences, such as physics, biology and chemistry.

In practical laboratory classes students traditionally receive data by reading from a measurement device (ruler, clock, voltmeter, etc.) or digitally as files in exchange formats such as CSV (comma separated value). In many cases these data have to be processed later using non-linear regression, here referred to as curve fitting. Therefore, analog data first have to be digitalised and imported to a data analysis and visualisation program, which is often commercial and requires installation. In this paper we present an alternative concept fusing open-source community tools into a single page web application facilitating data acquisition, visualisation, analysis via non-linear regression and further post processing usable for error calculations. We demonstrate the e-learning potential of this web application accessible at curvefit.tu-chemnitz.de in the context of acquired data as typically obtained in physical laboratory classes from undergraduate studies. A prototype workflow for the topic 'specific electric resistance determination' is presented along with a technical description of the basic web technology used behind. Restrictions, such as limited portability or cumbersome ways to share results electronically between student and supervisor as occurring in traditional software applications are overcome by enabling export via URL. The discussion is complemented by thorough comparison of curve fitting web applications with focus on their capability to be adaptable to user-specific models (equations) as faced by (undergraduate) students in the context of their education in laboratory classes in natural and life sciences, such as physics, biology and chemistry.