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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