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Table 1 Suggested methods for analysis based on trace data temporal resolution

From: The relational, co-temporal, contemporaneous, and longitudinal dynamics of self-regulation for academic writing

Trace data Dimension of analysis Methods
Logs, videos, Multimodal data, individual traces or activities Sequences Sequence mining
Transitions and flow Process mining or sequence mining
Relations and interactions Network analysis
Covariation and relations Psychological networks
Evolution Temporal networks
Commonalities or grouping Clustering
Trends Time series
Aggregation and frequencies Frequency and visualizations
Co-temporal data Co-occurrence Epistemic network analysis
Covariation and relations Network analysis
Contemporaneous data Sessions of events Process mining or sequence mining
Covariation or correlation Psychological networks
Longitudinal data Longitudinal evolution Temporal networks
  Sequence or trajectory Sequence mining or hidden Markov models
  Modelling Group-based trajectory modelling, Longitudinal clustering or latent class analysis
Covariation, temporal evolution and relations (interdependence) Temporal networks of time series data