June 11, 2015


Effective Teacher Pedagogy

Various data collection tools focusing on research-based teaching strategies have been developed in order to assist principals and peers in collecting data for teacher reflection and joint analysis. This tool, based on the research of Dr. John Hattie (2009), was designed at the School University Research Network (SURN) at the College of William and Mary for use in their Principals’ Academy. Focusing on both principal performance standards and research-based, high-yield strategies, Dr. Jan Rozelle (2012) and her colleagues developed several teacher observation and feedback tools to give principals the opportunity to assess the variety of research-based teacher behaviors exhibited during an observation, as well as make anecdotal comments. An analysis of these data with the teacher provides an opportunity to assess the range of behaviors being employed to help students achieve. Each of the ten observation “look-fors” on this form has an effect size of .40 or greater. Many schools simply choose to focus on several of the observation “look-fors” during a given school year in order for staff to become experts in select high-yield strategies by year’s end. (See “Materials” under the “Resources” tab for a crosswalk document that provides greater detail on examples and non-examples of each “look-for”.)

High-Yield Teacher Behaviors

This data collection tool was also created for the SURN Principal’s Academy at the College of William and Mary. This tool contains an additional 11 high-yield “look-fors” identified in Dr. Hattie’s (2009) meta analyses, all with an effect size of .40 or greater. In addition, this tool gives the observer the opportunity to record occurrences of both high- and low-yield practices by the teacher. Similar to the use of the Effective Teacher Pedagogy form, often school leadership team members will reach consensus on which select observation “look-fors” will be focus areas for a given school year. These specific strategies are then addressed through the school improvement planning process and often become an integral component to the school’s plan for professional learning. (See “Materials” under the “Resources” tab for a crosswalk document that provides greater detail on examples and non-examples of each “look-for”.)

Student Indicators of Engagement

Another tool was designed by Dr. Rozzelle (2012) and her colleagues to collect data on how students are engaging with content of the lesson. Principals and other observers use this tool to collect data on student participation in both high-yield and low-yield practices. Reflection and joint analysis enable both the teacher and principal in assessing the quality of student interaction with instructional activities and whether a discrepancy exists between the desired and actual outcomes. A primary difference between this SURN tool and the first two tools is that observers focus on student behaviors vs. teacher behaviors. For example, the first observation “look-for” is “Engages in setting learning goals”. In this case, the observer is looking for evidence that students are actively involved in setting their own learning goals as opposed to the teacher stating the learning objectives for a given class period. (See “Materials” under the “Resources” tab for a crosswalk document that provides greater detail on examples and non-examples of each “look-for”.)

Teacher/Student Behavior Observation

This tool was created to permit an observer to collect data on teacher and student behaviors simultaneously. Designed to focus on the high yield strategies identified by Marzano (2003), observers use this form to collect data using three keys – teacher behavior, student behavior, and teaching strategies. A rich data set for reflection and analysis results by focusing on the three key elements simultaneously. These data provide an opportunity to examine student reactions to the teacher’s behaviors. Observers and teachers engage in conversations with questions such as, “Are the students’ reactions congruent with the teacher’s reactions? Do they conform to student behaviors anticipated based on teacher’s behaviors? Are the behaviors focused on learning? Do the teacher’s behaviors reflect research-based instructional strategies that affect student achievement?”

Cognitive Levels of Questions and Wait Time

Good questioning is a critical component of effective teaching. Research has established a direct link between student achievement and the effective use of questioning at different difficulty and cognitive levels (Craig, Sullins, Witherspoon, & Gholson, 2006; Hattie, 2009). This tool is used by the observer to collect data for the cognitive level of each question the teacher poses during a lesson. Note that the observer also records the wait time in seconds next to the cognitive level of each question. The number of questions asked at each cognitive level is also summarized. Joint analysis by the teacher and observer may reveal patterns or the fact that most questions are at one cognitive level (e.g., recall), for example. It is important for the observer and the teacher to be familiar with the cognitive hierarchy and questions stems that cue to specific cognitive levels. (See “Materials” under the “Resources” tab for handouts on this topic.)

Student Engagement Data Collection

Simply making more time for learning will not automatically lead to achievement. A key to enhancing learning is to increase productive time – engaged learning time or time on task. The greater the academic demands on students and more they feel challenged, the more the students are engaged with instruction and the less prone they are to distractions. The frequency of different learning opportunities is much more important than spending more time on task (Hattie, 2009). Using this tool, the observer records the behavior of the teacher at short intervals. In reviewing this record of what the teacher was doing throughout the class period, teacher and observer can accurately determine how much academically focused time there was and also identify trends of teacher behavior that interfere with or distract from academic focus. A benefit of this form is that the observer also records how students spend their time in class. Often a description of teacher behavior alone is misleading, particularly when the teacher works with small groups. There are also a variety of uses for this form. For example, the observer could track the engagement of students by gender, name, or proximity. A code legend is provided to represent on- and off-task behaviors observed.

Teacher/Student Interactions

Interaction refers to verbal behaviors that keep the learning activity directed, focused, and organized by the teacher. Providing information, questioning, answering, clarifying, praising, giving directions, and redirecting skills and techniques are of particular interest. This tool is used for analysis and reflection about the kind and frequency of interactions with each student in the class. Observers simply indicate an interaction from the teacher to a student by placing an arrow pointed down in one of the boxes when teacher directs an interaction to a student and an arrow pointed up when the student directs an interaction to the teacher. The observer also places the appropriate code from the legend for the kind of verbal interaction. An analysis of this data can indicate behavioral patterns relevant to a teacher’s direction of activity. Data may reveal, for example, that the teacher interacts with only a limited number of students in a certain manner while others are virtually ignored. By using the code in the legend, the kind of interactions with individual students can also be determined and patterns revealed.

Engagement Data Collection

This tool is similar to the Student Engagement Data Collection form and is ideal for use with novice teachers to engage in conversations about classroom management strategies and time on task. In addition to collecting data about teacher behaviors during each activity of the lesson, this tool permits the observer to capture the exact number of students who are either on task or off task for each activity. (There is no emphasis placed on identifying specific students with the use of this form.) The code legend is also used to record the specific on-task and/or off-task behaviors for both groups of students. When the data reveal that one or more activities during the lesson has a higher than desired percentage of students demonstrating off-task behaviors, the conversation during the post-observation conference focuses on the teacher behavior(s) logged on the tool for that particular activity during the lesson.