This symposium focuses on an innovative field of educational research: the analysis of processes from the perspective of sequences. By this, the overall temporality of acting is taken into account and becomes the explicit object of research. In general, the focus on processes (and not in first place on results) is crucial for educational sciences as an activity-oriented and practical science.

It is argued that in current media-pedagogical research, the analysis of process-data lags behind existing methodological options. This is especially true for quantitative research: Although there are several methods, which focus on processes (e.g. event history analysis, time series analysis, cohort analysis, sequence), these are hardly used in practice of research. Furthermore, the need for innovative approaches is obvious in the field of internet-research and especially in the field of analysis of logdata as process-generated data.

Therefore, this symposium focusses on the innovative and creative method of sequence analysis by means of optimal-matching. The optimal-matching algorithm is well known in applied and natural sciences (i.e. molecular biology) but is hardly used in social sciences. Optimal-matching (see Kruskal 1999) starts with a pairwise comparison of every sequence (process) of the dataset. According to Erzberger (2001) the exploratory-heuristic sequence analysis by means of optimal matching can be characterized as an exploratory and heuristic, quantitative and case-oriented, inductive approach that allows the identification of typical patterns in empirical sequences, without using theoretical models or reference sequences. This method of sequence analysis is supposed to be one of the most effective ways to analyse sequences in a quantitative way (Baur 2005).

In contrast, in the field of linguistics, processes were used since the 1920ies to be analysed by the methodological concept of markov-chains: markov-chains analyse the probability of the transition from one step to the following. As a result, sequences of probabilities are calculated as a statement about the whole process. In this analysis, the single sequence and its structure of process is hidden behind mathematical artefacts. In addition, markov-chain analysis produces aggregated data describing the sequences in a very generalised way. In this symposion the concepts of markov-chains and sequence analysis will not only be discussed as competitive methods of research, but as two methods which can be combined creatively.

This symposium discusses the innovative and creative application as well as theoretical background of the method of sequence analysis by means of optimal-matching from several perspectives:

• The first presentation focusses on philosophical aspects of analysing sequence according to the process-theory of A. N. Whitehead.

• The second presentationfocusses on the theoretical and methodological background of the method of sequence analsis by means of optimal-matching.

• The third presentation focusses on the application of this method within the EU-Project Lancelot (Leonardo Da Vinci), analysing intercultural differences in designing instruction (teaching styles)

• This fourth presentation puts the method of sequence analysis by optimal-matching into a broader context by focussing on differences of analysing (learning) paths by markov-chains.