Background | Implementation | Student Performance | Reflections | Comments

Implementation

In Fall 2004 (Pilot 1), the students participated in six peer-teaching labs.  After four selected labs, they received either peer-generated feedback or a visual record of their teaching.  Peer-generated feedback data came in two forms:  a checklist that reported the teaching behaviors observed, or a coding sheet that provided a count of the preservice teacher’s feedback statements, as well as their content, mode, and direction.  The visual record was a DVD recording of the students’ teaching.  I assigned optional reflective exercises after the four peer-teaching labs.  Students were asked to respond to two open-ended questions or prompts.  The purpose of the first prompt was to jumpstart the reflective process with a general query.  The second prompt asked them to think about their teaching skills and reflect on what they might do to improve them.  For the first lab, half of the class received peer-generated feedback, and the other half received a visual record of their performance only.  At the next lab, each group received the other type of feedback.  By the end of the semester, most of the students had received equal amounts of both feedback types.  I received two reflections under both conditions from five out of ten students.  I examined them and attempted to determine whether reflections based upon visual record were more meaningful than those inspired by peer-generated feedback.

When I taught the course subsequently in Spring 2005 (Pilot 2), the students once again participated in six peer-teaching labs.  Procedures in the first two labs were similar to Pilot 1, but later I found that modifications were necessary.  Since there were only five students enrolled, it became inconvenient to pull one student out to serve as an observer, so I dropped that component of the project.  Furthermore, the return rate for the reflective exercises was poor.  In an effort to boost the return, I asked all of the students to use the checklist and the coding sheet to analyze their videos from the third and fourth labs.  Due to the small class size, a 75-minute period often provided sufficient time for me to offer comments and lead a short discussion after each student completed a teaching episode.  Unlike the previous semester, when students received a completed checklist and brief comments or a visual record, these students also experienced an instructor-led discussion of their teaching skills.  I received one reflective response under both conditions from three out of five students.

After the pilot studies, I modified the procedures for my next project (Spring, 2006).  First, I gave all of the students two sheets after each peer-teaching lab—the reflective prompts and the feedback checklist or coding sheet.  Some students were observed by a peer; therefore, their checklist or coding sheet contained data and comments from an observer.  Other students received a blank checklist or coding sheet, and they were free to use it to analyze their own performance while they watched their DVD.  This provided all of the students the opportunity to use the checklist and coding sheet as prompts for reflection.  Second, during the labs, I made no specific comments about anyone’s teaching performance.  As the instructor of this course, I certainly believe I should provide feedback on the students’ performance.  But after Pilot 2, I feared that the individual feedback I gave after each student’s teaching episode might have become the subject of the students’ reflection.  In essence, they might have been substituting my reflections for their own.  Therefore, in the current reflective study, I held all comments until all of the teaching episodes were complete, and then I blanketed the students with thoughts and concepts related to the lab.  It was my hope that they would consider all of my comments, then choose and reflect upon those that related to their performance.

I also modified procedures for data analysis in the current study.  In the pilots, my analysis was primarily observational.  Although I did compare the length of statements under both feedback conditions, for the most part, I merely took note of the types of reflective statements made by the students.  For the current reflective study, data analysis was largely evaluative.  I designed a rubric (PDF) (HTML) to enable me to assess the quality of the reflective statements.  The data were used to categorize individual reflections into one of three hierarchical reflective groups--advanced, intermediate, and novice.  Responses were analyzed for length, breadth, accuracy, and depth.  Length was included as a general descriptor.  Breadth scored the number of topics to which the students referred in their reflection.  Accuracy indicated whether or not a teaching concept was referenced correctly.  Both breadth and accuracy were weighted more heavily than length, because they are both indicators of the students’ knowledge and understanding of the theory they should have learned in this course.  The most heavily weighted category was depth, because it indicated whether students penetrated beyond vague conceptual statements to make real connections between learned theory and their performance.  After evaluating all of the students’ statements, I determined which type of feedback generated more advanced and intermediate reflections.  Furthermore, I gave each student an overall rating of their reflective skills.  As a final assessment, I asked the students to tell me which type of feedback inspired them to reflect more deeply about
their teaching.

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