|Ph.D Student||Lapidot Tamar|
|Subject||Computer Science Teachers' Learning during their Everyday|
|Department||Department of Education in Science and Technology||Supervisor||Professor Emeritus Uri Leron|
This dissertation describes a field study carried out in high-school computer science classrooms. The main research goal has been to uncover the mechanism behind teachers' learning processes during their daily teaching, with an emphasis on computer science learning. In this research, learning has been regarded as a process of constructing personal meanings through the social interaction of the teachers with their students.
The fieldwork was carried out according to principles of ethnographic research, including analyses that enable the formation of field-grounded theory. The data was collected in high-school computer science classrooms over a four year period. The research population included a sample of 15 teachers and student-teachers. From this group, two experienced teachers and five student-teachers were selected for a deeper analysis.
Based on the research findings, a content reasoning model has been constructed, with the aim of explicating the learning processes of high-school computer science teachers. The model is based on the pedagogical reasoning model of Shulman and offers an explanatory framework for the content learning of these teachers. According to the content reasoning model, there are four stages that differ in their learning characteristics: the comprehension stage (content-oriented learning), the transformation stage (pedagogical-oriented learning), the teaching stage (non-directed content learning), and the reflection stage (pedagogical reflection that leads to a content reflection). The content learning of teachers is influenced by three types of factors: cognitive factors (externalization, awareness, and understanding performances), social factors (mainly classroom interaction), and affective factors (fostered by professional responsibility).