**2.2. Methodology**

that teachers' knowledge in this context can be addressed using the terms: "knowledge of elements of thinking and/or metacognition" and "pedagogical knowledge in the context of teaching HOT and/or metacognition." These terms highlight the fact that teachers' knowledge in this field has unique characteristics and is both domain general and domain specific (for a

A precondition for teachers' metacognitive knowledge in this area is their familiarity with thinking strategies and processes on the cognitive level, that is, with **knowledge of elements of thinking**. In addition, previous researchers noted that in order to use metacognition successfully when teaching HOT, teachers need robust knowledge of **elements of metacognition**, that is, of the pertinent **metacognitive knowledge and skills** related to HOT [19, 20]. Moreover, the domain-specific aspects of **metastrategic knowledge (MSK)** suggest that teachers may need diverse types of MSK for the diverse thinking strategies they would address in class. Teachers obviously also need to be proficient with the **metastrategic skills (MS)** that are relevant for planning, monitoring, evaluating, and regulating thinking processes in the area of HOT. Such complex knowledge of metacognition is a precondition for sound **pedagogical knowledge** in this area. Zohar and Barzilai [15] further elaborated the component of the pedagogical knowledge noted earlier, describing several pedagogical principles, two of which are particularly significant for the present chapter: (1) deliberate attention to general thinking structures and skills, and (2) fostering explicit awareness of

Despite researchers' agreement about the value of teachers' knowledge about metacognition, studies show that in effect, the knowledge of most teachers in this area is slim [1, 20–27]. Teacher education programs may cultivate that knowledge using multiple means. For example, while small groups of student-teachers engage in problem-solving, one member of the group is asked to record the thinking strategies her peers have been using during that process. At a later stage of the lesson, this member of the group shares the data she recorded, thereby making the thinking strategies explicit and an object of discussion and evaluation. Other examples may consist of watching and analyzing a video of a lesson in which the teacher applied metacognitive teaching or of a task presenting a thinking-rich lesson plan, and then

**1.** How do educators who lead wide-scale programs aimed at the development of students' higher order thinking (HOT) view teachers' knowledge in the area of metacognition?

**2.** How do they view the impact of teachers' knowledge on the implementation of

asking student-teacher to add metacognitive components to the lesson.

The present study aims to answer the following research questions:

more detailed explanation, see [15, 18]).

90 Contemporary Pedagogies in Teacher Education and Development

metacognition in the classroom.

**2. Method**

**2.1. Research questions**

metacognition?

This is a qualitative study based on in-depth, semi-structured interviews with 18 instructional leaders who had prominent roles in large-scale implementation programs designed to teach HOT. Data analysis applies a pragmatic qualitative research approach that is particularly suitable for professional fields because it provides the descriptive information that can inform professional practices [28]. The research conducted within this approach is just what the name implies: research that draws upon the most sensible and practical methods available in order to answer a given research question. It aims for description of experiences and events as interpreted by the researchers, and therefore marks the meeting point of description and interpretation, in which description involves presentation of facts, feelings, and experiences in the everyday language of participants, as interpreted by the researcher. Analysis typically consists of qualitative content analysis using modifiable coding systems that correspond to the data collected. Interpretation stays close to the data [28].
