Research · 3 min read
Activation Prompts in Business Education - Identifying Instructional Patterns
Dr. Claudia Kopf's dissertation on prior knowledge activation in business education using quantitative video analysis with Mangold INTERACT
Prior knowledge is a significant factor influencing learning success. Numerous empirical studies demonstrate positive effects of prior knowledge on learning. However, the mere presence of prior knowledge is not sufficient to achieve good learning outcomes. Essential is the activation and use of prior knowledge.
To beneficially activate prior knowledge relevant to new learning content, learners need specific support. According to previous research, automatic activation of prior knowledge cannot be assumed. Rather, it depends on the instructions of the teacher.
The following two research questions are the focus:
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Which activation prompts are used in business education classroom research?
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How are activation prompts embedded in business education teaching practice during topic introductions?
To address this, the current state of research on activation prompts and their instructional embedding is discussed. Within the framework of a pilot study, the research design is first specified. Based on the results, a category system is developed and business education classes at vocational schools in Baden-Württemberg are recorded and evaluated. These evaluations include both quantitative, software-supported analysis methods as well as qualitative analysis methods in the form of sequence analysis.
The result of the analyses are four dimensions whose characteristics (subdimensions) describe different activation prompts. The role of the teacher, the materials used, the type of prior knowledge, and the learning content represent the subdimensions from which activation prompts are composed. Furthermore, five patterns of embedding activation prompts in topic introductions can be distinguished. The results represent a first approximation to the highly inferential construct of ‘prior knowledge activation’. On this basis, the patterns can be validated and specified, and the effectiveness of activation prompts occurring in business education teaching practice can be investigated.
Analysis Method: Quantitative Video Analysis
This work pursues both a qualitative and quantitative research approach to investigate the occurrence of activation prompts in business education teaching practice from different perspectives. First, the procedure for the quantitative research part is described.
The coding of video data was carried out by three coders. The observers received prior observer training including simulations with examples from the teaching videos of the pilot study and an introduction to the coding manual to ensure objectivity. The 50 videos were divided among the three coders. Coders 2 and 3 coded the lessons for which consent from the teachers was available that the material could be shown confidentially to third parties. Coder 1 coded 20 percent of the codings of the teaching videos from coders 2 and 3 for validation purposes. Event samples (‘event-sampling’) were chosen as the analysis unit for coding, meaning the teaching unit is divided into a series of differently sized time segments, each with its own starting and ending point for each occurrence of the criterion.
Using the video analysis software Interact , graphical evaluations – such as frequency and time diagrams – were made and the corresponding statistics were collected. Both evaluations per video and analyses across the total data were performed. The highest and lowest value of a category or subcategory was determined with software support, and the respective differences were divided into four color categories to identify outliers and represent the distribution of codings (‘Visual Data Exploration’). In addition, so-called ‘State-Space-Grids’ were created. This evaluation routine was developed by Hollenstein (2011, 2013) and is a special method for evaluating synchronized event sequences and thus identifying possible patterns of co-occurrence of certain events.
To determine all categories that overlap within a time period in a specific behavior, overlapping codings were filtered and combined (‘Co-Occurrence-Filter’).
We thank Dr. Kopf very much for providing the research study on the occasion of her inaugural dissertation at the University of Mannheim.
The complete study is available for download here
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