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March 2003 | Volume 6 | Number 6
Using Data to Improve Student Achievement
On a warm day late last summer, Lincoln High School's halls were quiet—the bells were silent, no lockers slammed. But there was a “buzz” coming from the Library Media Center, where the entire faculty was meeting to define its departmental SMART goals—goals that are Strategic and Specific, Measurable, Attainable, Results-based, and Timebound.
Brian Jones and the rest of the social studies department team were working in the library that day as part of the school's ongoing continuous improvement process. The previous year, the team—along with the rest of the faculty—had engaged in an intensive, comprehensive needs assessment process during which they had examined achievement, climate, behavioral, and programmatic data for their entire school.
That examination process revealed a clear student learning priority: all students in all grades needed to improve their writing skills. Achievement tests and other performance measurements indicated still more weak skill areas, and the faculty had committed to looking at their subject-area curricula to improve these results. But they also knew that they needed to focus on one area in order to see a significant improvement in student achievement (Reeves, 1999; Calhoun, 1999; Cawelti, 1999; Barth, Haycock, & Jackson, 1999). (See Figure 1.)
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Teachers collaboratively decided that Lincoln High School's schoolwide student learning goal would be to improve the writing skills of all students across all curricular areas. Last year, the faculty went even further and set this SMART goal: By spring 2003, the number of students at each grade level who score 4 or better on the schoolwide writing sample will increase by five percent. Teachers had done the tough work of aligning a local assessment—a rubric-based writing prompt—with the standards, so they knew that if students did well on this assessment, they would also do well on the state tests. In addition, they looked at their baseline data on the local assessment and decided that their goal was attainable.
Brian and his department team, along with all the other departmental teams, listened intently as a small group of teachers that had researched best practices in writing over the summer shared their findings. They identified seven factors that contribute to improved writing:
Based on this information, Brian and his team, along with the entire faculty, created six schoolwide strategies. Teachers would
Each department also decided to develop classroom-based measures they would use in common to track progress toward the SMART schoolwide goal. They then scheduled collaborative time to come together periodically throughout the year, using the “30+ Minute Meeting” process [see sidebar], to share results and strategies, and make adjustments to their strategies as needed (Schmoker, 1998).
In spring 2003, six weeks before 10th graders would be taking the state achievement tests, the history department met to share results from each of their classrooms. Brian reported that during the first quarter, he gave students only six writing assignments. The feedback they received came only from him, and most of it was in writing. During this last quarter, however, Brian gave his students eleven assignments, four of which he responded to in writing and three verbally. Brian also arranged for students and other staff to give feedback on two of the writing assignments.
Brian noted that he tracked the class's percentage of correct answers on the vocabulary lists. The average percent correct had risen from 50 to 80 during that first quarter (see Figure 2). He also reported that more students were making their own writing selections. More were choosing tougher AP-style writing assignments, choosing cross-curricular subjects, and choosing to write about history subjects they were interested in (see Figure 3).
After congratulating Brian on his efforts and results, the other teachers shared their classroom results, and a similar pattern emerged. The teachers then reviewed the results on the agreed-upon writing prompt (see Figure 4). The team was delighted—but not surprised—to see the increase in the number of students achieving a score of 4 or higher on the six-point writing rubric. In the first quarter, no student scored a 6 and the most frequent score was a 3 (below proficient), while in the 4th quarter, many scored a 6, and the most frequent scores were 4 and 5.
Still, the teachers realized that their work was not yet done—there were too many students continuing to score below 4. They decided as a team to focus in on those remaining students, find out what specific writing skills they were having trouble with, and spend extra time coaching them on those skills. When the May state testing time arrived, nearly all of the students were ready and very few scored a 3 or below.
Skillful teachers know how to balance the science and the art of their teaching. On the one hand we need to ask, “How can we use data (our science) to validate what our intuition and professional knowledge and experience tell us?” But we also need to ask, “How can we bring our professional knowledge and wisdom (our art) to the process in a way that helps us understand and critically question the data?” This interplay between the science and art of teaching is what elevates compassion to professionalism.
When applied with knowledge and integrity, using data heightens our ability to make informed and reasoned decisions about our work; it is what distinguishes the professional practitioner from the technician. In other professions—such as medicine, law, athletics, and the arts—shared learning, research, public scrutiny, feedback on performance, and peer review are characteristic of professional practice. Why wouldn't we expect the same level of professional rigor from ourselves as educators? Teaching is not just about methods and textbooks. Teaching is about learning and being able to demonstrate through the performance of the learners that real teaching and learning have occurred.
Brian and his departmental team were unafraid of data and eager to collaborate on ways to improve their teaching. They were focused on continuous improvement of student learning through SMART goals, and they used a process—30+ Minute Meetings—to get improved results. When departmental and grade-level teams of teachers come together around shared goals, using a good process and meaningful assessments, and when they link this work to the school's larger vision for improvement, there is no limit to the results that can be achieved.
These meetings can be conducted by the entire staff, by grade level teams, or by departments.
5 min. Question: What are the student learningissues we are struggling with the most?
10 min. Brainstorm responses.
5 min. Identify top three priorities.
10 min. Question: What more do we need to know? How can we find out?
Between meetings, gather student data and information on priority areas.
10 min. Present graphs of student performance in areas of concern. (Focus on skill areas or proficiency or performance levels.)
10 min. Brainstorm results-oriented goals for priority areas.
5 min. Select one results-oriented goal for each priority area.
10 min. Make the goals SMART: Individuals write indicators, measures, and targets for one goal.
(Consider indicators by skill, competence, or performance expectations aligned to standards; consider both standardized and classroom-based measures; consider student data when writing targets.)
5 min. Share SMART goals in round-robin style, one at a time.
15 min. Select “best” indicators, measures, and targets to write group SMART goals.
10 min. Question: What do we need to know in order to affect student learning for these SMART goals?
Between meetings, do literature, research, and best-practice review.
10 min. Share information gathered between meetings.
10 min. Develop matrix: What are we already doing that supports best practice in this area? What more would we like to learn about?
10 min. Identify instructional strategies we want to do more of, start doing, and/or stop doing.
Between meetings, research ways to develop professional knowledge to learn best practices.
10 min. Share information about various staff development methods.
10 min. Study the matrix: Individuals select preferred strategy for learning about best practices and identify areas they are willing to coach in or teach others about.
15 min. Discuss implementation: How will we implement staff development for best practices? What support do we need? How will we measure progress on the SMART goals?
Between meetings, implement staff development and integration of best practices, then gather data to measure against baseline.
10 min. Present graphs of new data.
15 min. Discuss what worked, what didn't, and why.
15 min. If the instructional strategy worked well, discuss how to “hold the gains.”
If the strategy did not work well, decide next steps: Start doing the strategy differently, stop doing the strategy altogether, or start a new strategy.
Start the cycle over again.
Schmoker, M. (1998). Results: The key to continuous school improvement (2nd ed.). Alexandria, VA: Association for Supervision and Curriculum Development.
Barth, P., Haycock, K., & Jackson, H. (Eds.). (1999). Dispelling the myth: High-poverty schools exceeding expectations. (Report No. SR9901). Washington, DC: Education Trust. (ERIC Document Reproduction Service No. ED 445 140)
Cawelti, G. (1999). Portraits of six benchmark schools: Diverse approaches to improving student achievement. Arlington, VA: Educational Research Service.
O'Neill, J. SMART Goals, SMART Schools. (2000, February). Educational Leadership, 57(5), 46–50.
Jan O'Neill(firstname.lastname@example.org) is cofounder, with Anne Conzemius, of Quality Leadership by Design, LLC (QLD) (www.qldlearning.com). She and Anne have cowritten two books, Building Shared Responsibility for Student Learning (ASCD, 2001) and The Handbook for SMART School Teams (NES, 2002).
Copyright © 2003 by Association for Supervision and Curriculum Development
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