Improving Generative cognitive processing through Germane Cognitive Load: A Qualitative Research

One of the main challenges students in learning environments is learners' mastery of educational content and the application of new knowledge in real life. Generative learning involves actively making sense of to-be-learned information by mentally reorganizing and integrating it with one’s prior knowledge, thereby enabling learners to apply what they have learned to new situations. Due to the novelty of the concept of generative processing, there is a need for additional research on methods to enhance this type of learning.Therefore, the present study tried to identify and explain the strategies for strengthening generative prossesing (GL) through germane cognitive load (GCL). The research method was qualitative, conducted using thematic analysis method. The study area was all written and digital Persian and English on GCL. Thirty two papers were selected and analyzed as the sample according to the professors using content analysis and purposive approach and selecting texts and the key experts in the field of GL and cognitive load and considering theoretical saturation in the last ten years. The results were categorized as basic themes (codes and key points of the text), organizational themes (themes obtained from the composition and summarizing the basic themes) and inclusive themes (excellent themes containing the principles governing the text as a whole) and the network of themes was plotted. After data analysis, five main themes including multimedia application, personalization, feedback, thought and guided learning, and 53 sub-themes emerged to strengthen optimal generative processing and cognitive load.