THE USE OF THE EARLY WARNING INDICATOR REPORT TO IMPACT NINTH GRADE PROMOTION RATES IN A LARGE URBAN SCHOOL DISTRICT

Abstract The purpose of this study was to examine how four high schools used an Early Warning Indicator Report (EWIR) to improve ninth grade promotion rates. Ninth grade on-time promotion is an early predictor of a student’s likelihood to graduate (Bornsheuer, Polonyi, Andrews, Fore, & Onwuegbuzie, 2011; Leckrone & Griffith, 2006; Roderick, Kelley-Kemple, Johnson, & Beechum, 2014; Zvoch, 2006). The analysis revealed both similarities and differences in the ways that the four schools used the EWIR. The research took place in a large urban school district in the Mid-Atlantic. Sixteen participants from four high schools and the district’s central office voluntarily participated in face-to-face interviews. The researcher utilized a qualitative case study method to examine the implementation of the EWIR system in Wyatt School District. The interview data was transcribed and analyzed, along with district documents, to identify categories in this cross case analysis. Three primary themes emerged from the data: (1) targeted school structures for EWIR implementation, (2) the EWIR identified necessary supports for students, and (3) the central office support for school staff. The findings revealed the various ways that the target schools implemented the EWIR in their buildings and the level of support that they received from the central office that aided them in using the EWIR to improve ninth grade promotion rates. Based on the findings of this study, the researcher provided a number of key recommendations: (1) Districts should provide professional development to schools to ensure that schools have the support they need to implement the EWIR successfully; (2) There should be increased accountability from the central office for schools using the EWIR to identify impactful interventions for ninth graders; and (3) The district needs to assign dedicated central office staff to support the implementation of the EWIR in high schools across the district. As schools continue to face the challenge of improving ninth grade promotion rates, effective use of an Early Warning Indicator Report is recommended to provide school and district staff with data needed to impact overall student performance.

Warning Against Faking: Boon or Bane? Effects on Test Score Validity

Previous research found personality test scores to be inflated on average among individuals who were motivated to present themselves in a desirable fashion in high stakes situations, such as during the employee selection process. One apparently effective way to reduce the undesirable test score inflation in such situations was to warn participants against faking. This research set out to investigate whether warning against faking would indeed affect personality test scores in the theoretically expected fashion. Contrary to expectations, the results did not support the hypothesized causal chain. Results across three studies show that while a warning may lower test scores in participants motivated to respond desirably (i.e., to fake), the effect of warning on test scores was not fully mediated by: a reduction in motivation to do well and self-reports of exaggerated responses in the personality test. Theoretical and practical implications are discussed.

Computational Foundations for Safe and Efficient Human-Robot Collaboration in Assembly Cells

Human and robots have complementary strengths in performing assembly operations. Humans are very good at perception tasks in unstructured environments. They are able to recognize and locate a part from a box of miscellaneous parts. They are also very good at complex manipulation in tight spaces. The sensory characteristics of the humans, motor abilities, knowledge and skills give the humans the ability to react to unexpected situations and resolve problems quickly. In contrast, robots are very good at pick and place operations and highly repeatable in placement tasks. Robots can perform tasks at high speeds and still maintain precision in their operations. Robots can also operate for long periods of times. Robots are also very good at applying high forces and torques. Typically, robots are used in mass production. Small batch and custom production operations predominantly use manual labor. The high labor cost is making it difficult for small and medium manufacturers to remain cost competitive in high wage markets. These manufactures are mainly involved in small batch and custom production. They need to find a way to reduce the labor cost in assembly operations. Purely robotic cells will not be able to provide them the necessary flexibility. Creating hybrid cells where humans and robots can collaborate in close physical proximities is a potential solution. The underlying idea behind such cells is to decompose assembly operations into tasks such that humans and robots can collaborate by performing sub-tasks that are suitable for them. Realizing hybrid cells that enable effective human and robot collaboration is challenging. This dissertation addresses the following three computational issues involved in developing and utilizing hybrid assembly cells: - We should be able to automatically generate plans to operate hybrid assembly cells to ensure efficient cell operation. This requires generating feasible assembly sequences and instructions for robots and human operators, respectively. Automated planning poses the following two challenges. First, generating operation plans for complex assemblies is challenging. The complexity can come due to the combinatorial explosion caused by the size of the assembly or the complex paths needed to perform the assembly. Second, generating feasible plans requires accounting for robot and human motion constraints. The first objective of the dissertation is to develop the underlying computational foundations for automatically generating plans for the operation of hybrid cells. It addresses both assembly complexity and motion constraints issues. - The collaboration between humans and robots in the assembly cell will only be practical if human safety can be ensured during the assembly tasks that require collaboration between humans and robots. The second objective of the dissertation is to evaluate different options for real-time monitoring of the state of human operator with respect to the robot and develop strategies for taking appropriate measures to ensure human safety when the planned move by the robot may compromise the safety of the human operator. In order to be competitive in the market, the developed solution will have to include considerations about cost without significantly compromising quality. - In the envisioned hybrid cell, we will be relying on human operators to bring the part into the cell. If the human operator makes an error in selecting the part or fails to place it correctly, the robot will be unable to correctly perform the task assigned to it. If the error goes undetected, it can lead to a defective product and inefficiencies in the cell operation. The reason for human error can be either confusion due to poor quality instructions or human operator not paying adequate attention to the instructions. In order to ensure smooth and error-free operation of the cell, we will need to monitor the state of the assembly operations in the cell. The third objective of the dissertation is to identify and track parts in the cell and automatically generate instructions for taking corrective actions if a human operator deviates from the selected plan. Potential corrective actions may involve re-planning if it is possible to continue assembly from the current state. Corrective actions may also involve issuing warning and generating instructions to undo the current task.