Research on the Influencing Factors of Problem-Driven Children's Deep Learning.

Deep learning is widely used in the fields of information technology and education innovation but there are few studies for young children in the preschool stage. Therefore, we aimed to explore factors that affect children's learning ability through collecting relevant information from teachers in the kindergarten. Literature review, interview, and questionnaire survey methods were used to determine the influencing factors of deep learning. There were five dimensions for these factors: the level of difficulty of academic, communication skills, level of active collaboration, level of in-depth processing, and reflection level evaluation. Reliability and validity tests were used to analyze the data from questionnaires. In total, 100 valid questionnaires were collected. The Cronbach coefficients for academic challenge, communication, active cooperation, deep processing, and reflective evaluation were 0.801, 0.689, 0.770, 0.758, and 0.665, respectively. Principal component analysis revealed that there were three main factors that affect children's learning depth: the level of deep processing (maximum KMO: 0.908), the level of reflective evaluation (maximum KMO: 0.542), and the active level of collaboration (maximum KMO: 0.410). In conclusion, there were several factors affecting deep learning in children and further studies are warranted to promote the development of this field.