Using Gap Analysis to Improve Student Achievement - 2009 Thematic Dissertation Group
This 2009 thematic dissertation group focuses on using gap analysis and evidence-based methods to help schools increase the achievement of underperforming students. The group is designed for those who intend to work in K-12 settings as consultants, administrators or researchers, as well as students who hope to become college instructors in schools of education. To be eligible, students should have completed the four core courses (EDUC 522, 523, 524, 525), Inquiry I & II, plus at least two of the Ed Psych advanced courses (Research in learning, Motivation, Lifespan Development).
The group will use gap analysis and the latest evidence-based teaching methods and motivational strategies to help a school district increase the achievement of underperforming students. We will draw on recent studies of the cognitive processes that occur when teachers and school administrators decide what and how to teach, when students attempt to learn from instruction and when the performance of teachers and students is assessed. The complexity of these processes increases in situations where teachers attempt to maximize the learning of all students in diverse classrooms that include many students with special needs. The students in this dissertation group will conduct collaborative, individual studies that attempt to identify and close different types of gaps between school and classroom goals on the one hand, and current progress towards achieving those goals on the other hand.
Our collective goal will be to work together to implement a large scale gap analysis that examines the objectives of interest to the school, individual doctoral students and faculty advisors. In this way, students will have the opportunity to directly experience the development of not only their own analysis but those of other students. In addition, doctoral students will have the opportunity of examining some of the more recent evidence-based models of teaching and learning from a cognitive, dual process, direct instruction framework. Recent advances in psychology provide opportunities to identify and influence the cognitive mechanisms that drive motivation and learning. For example, applying the principles of cognitive load theory to classroom dynamics reveals new methods for identifying, assessing, and managing the pedagogical content and instructional design necessary for optimal learning by diverse students with very different backgrounds. Recent reviews of research on the limits of popular teaching methods suggest some innovative ways to achieve common classroom goals for different students.
The school will select the gaps it wants closed. Students will have the opportunity to choose among those gaps to select problems that interest them. We are giving a service to the district and so not free to dictate the gaps we will analyze. Each student's dissertation will essentially describe how they closed the gap they selected from the range of problems offered by the school district. Gaps typically involve reading, writing, mathematics performance and other curriculum (and high stakes testing) issues.
Participation in this group will contribute to your professional work as practitioners. Educational psychology forms one of the key foundations for educational policy, assessment and instructional practice. Learning to diagnose, analyze, and validate the cause of performance gaps and selecting appropriate evidence-based interventions to close those gaps in urban school settings is a critical skill for all professional educators with a doctorate. One of the School Districts in Los Angeles has invited our thematic dissertation group to help them solve underperformance problems. Provided that students are willing to invest the effort required to conduct intense and demanding action research in a real setting, the learning benefit to doctoral students will be significant and the service we will provide to k-12 students, families and the school district will make the effort worthwhile.
Students will be required to use the Gap Analysis framework as their primary research methodology. The framework encompasses six steps: (a) identifying key organizational goals; (b) identifying individual performance goals; (c) determining performance gaps; (d) analyzing performance gaps to determine their causes; (e) identifying and implementing solutions; and (f) evaluating results. Performance gaps can be diagnosed based on three factors: (a) the knowledge and skills that are applied to achieve individual performance goals; (b) the motivation to achieve individual performance goals; and (c) the organizational culture, resources, equipment, and work processes that influence the achievement of performance goals. Solutions for bridging performance gaps must be analyzed based on social science and educational research, to identify their "active ingredients" and to determine if they are appropriate to close the performance gap in question. As a final step, the results must be evaluated to determine whether, in fact, the performance problem has been solved.
In addition, both quantitative and qualitative analytical methods will be used in all aspects of this thematic group. All students who participate will be required to use "blended" methods. Integrating a common methodological approach and compatible research tools in thematic dissertations provides for an examination of different issues from a variety of perspectives, the results of which can be merged into a more accurate and comprehensive view of the causes and solutions of gaps and opportunities.
Automated Knowledge Research Group
The Center for Cognitive Technology supports an ongoing collaboration between a number of faculty and student researchers who share an interest in the development and modification of automated or implicit knowledge.
The goal of the ”Automated Knowledge Research Group” is to understand how to modify automated and unconscious knowledge with a specific focus on automated racial and ethnic stereotypes. We are also interested in our personal awareness of automated process such as the investment of mental effort during learning, self monitoring and self awareness of decisions.
In the past five years, approximately 10 doctoral students and faculty have met on a regular schedule to review, design and conduct experiments. In the past three years, a number of students in the group have developed and implemented research projects that led to dissertations including Sarah Firestone (PhD, 2003), Andy Dean (PhD, 2004) Fredric Maupin (EdD, 2004), Ipek Yildir (EdD, 2004), David Feldon (PhD, 2004), Sunhee Choi (PhD 2005), Keith Howard (PhD 2005), and Kenneth Yates (EdD, 2007).
Firestone, Maupin and Feldon’s dissertations were all selected as finalists for the dissertation award in the year they finished. Fredric Maupin’s dissertation was recently ranked as among the top three dissertations in the country by the American Society for Training and Development. Keith Howard’s research on stereotype threat is groundbreaking and we fully expect that his dissertation will receive wide recognition. And Kenneth Yates' dissertation revealed novel interactions among cognitive task analysis methods and knowledge types. As students graduate from the group and move on, others are taking their place.
The research group is a major focus of our creative efforts and an ongoing collaborative program. A sample of the current activities in the research group includes: