The nature of educational data can range widely from quantitative data, which is highly structured, and is collected through closed tools such as scales, to unstructured information, such as textual data obtained with the use of open questions. It is possible to adopt an approach involving deductive/confirmatory or exploratory/inductive analysis in the case of structured as well as unstructured data.
Examples of these approaches include Structural Equation Modelling (SEM), exploratory factor analysis (EFA) for quantitative data, as well as content analysis and statistical analysis of textual data. Moreover, mixed approaches are also possible, which may include the statistical analysis of texts and the integration of structured and unstructured information.
There are some open issues regarding research questions: when analyzing educational data, it should always be clear at what level of interest the questions are asked (i.e. at individual or group level), and whether any interaction between these levels is expected. Moreover, with regard to textual data, it is important to consider that, depending on the research questions, they can be analyzed both to test hypotheses and to explore an area of interest. The decision of whether or not to integrate quantitative data with textual data also depends on the research questions.
We are particularly interested in receiving original research that addresses the themes mentioned above, and that presents the criteria underlying the methodological decisions made.
This original research can deal with (without being limited to) the following themes:
• Empirical studies conducted in educational contexts and based on structured data (e.g. structural equation modeling, multilevel modeling, confirmatory factor analysis, longitudinal studies, exploratory factor analysis, and exploratory structural equation modeling).
• Empirical studies conducted in educational contexts and based on unstructured data (e.g. statistical analysis of textual data, and bottom-up and top-down content analysis).
• Studies that integrate the use of structured and unstructured data.
The main criterion for inclusion is that the original research should indicate the link between the research questions, constructs, and variables used and the choice of which method of analysis to use.
The nature of educational data can range widely from quantitative data, which is highly structured, and is collected through closed tools such as scales, to unstructured information, such as textual data obtained with the use of open questions. It is possible to adopt an approach involving deductive/confirmatory or exploratory/inductive analysis in the case of structured as well as unstructured data.
Examples of these approaches include Structural Equation Modelling (SEM), exploratory factor analysis (EFA) for quantitative data, as well as content analysis and statistical analysis of textual data. Moreover, mixed approaches are also possible, which may include the statistical analysis of texts and the integration of structured and unstructured information.
There are some open issues regarding research questions: when analyzing educational data, it should always be clear at what level of interest the questions are asked (i.e. at individual or group level), and whether any interaction between these levels is expected. Moreover, with regard to textual data, it is important to consider that, depending on the research questions, they can be analyzed both to test hypotheses and to explore an area of interest. The decision of whether or not to integrate quantitative data with textual data also depends on the research questions.
We are particularly interested in receiving original research that addresses the themes mentioned above, and that presents the criteria underlying the methodological decisions made.
This original research can deal with (without being limited to) the following themes:
• Empirical studies conducted in educational contexts and based on structured data (e.g. structural equation modeling, multilevel modeling, confirmatory factor analysis, longitudinal studies, exploratory factor analysis, and exploratory structural equation modeling).
• Empirical studies conducted in educational contexts and based on unstructured data (e.g. statistical analysis of textual data, and bottom-up and top-down content analysis).
• Studies that integrate the use of structured and unstructured data.
The main criterion for inclusion is that the original research should indicate the link between the research questions, constructs, and variables used and the choice of which method of analysis to use.
