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Our ongoing program of research works with teachers to help them become more autonomy supportive during instruction and hence more able to promote students’ classroom motivation and engagement.

We have published five experimentally based, longitudinally designed, teacher-focused intervention studies that have tested the effectiveness and educational benefits of an autonomy-supportive intervention program (ASIP).

Findings show that (1) teachers can learn how to become more autonomy supportive and less controlling toward students, (2) students of the teachers who participate in ASIP report greater psychological need satisfaction and lesser need frustration, (3) these same students report and behaviorally display a wide range of important educational benefits, such as greater classroom engagement, (4) teachers benefit as much from giving autonomy support as their students do from receiving it as teachers show large postintervention gains in outcomes such as teaching efficacy and job satisfaction, and (5) these ASIP-induced benefits are long lasting as teachers use the ASIP experience as a professional developmental opportunity to upgrade the quality of their motivating style.

Our ASIP helps teachers learn how to better support their students’ autonomy during instruction. The value of this teaching skill can be seen in teachers’ and students’ enhanced classroom experience and functioning.

The purpose of this paper is to obtain values that stabilize the lateral and longitudinal flight of the quadrotor for which the morphing amount and the best Proportional-Integral-Derivative (PID) coefficients are determined by using the simultaneous perturbation stochastic approximation (SPSA) optimization algorithm.

Quadrotor consists of body and arms; there are propellers at the ends of the arms to take off and rotors that rotate them. By reducing the angle between mechanism 1 and the rotors with the horizontal plane, the angle between mechanism 2 and the arms, the rotors rise and different configurations are obtained. Conventional multi-rotor aircraft has a fixed fuselage and does not need a tail rotor to change course as helicopters do. The translational and rotational movements are provided by the rotation of the rotors of the aircraft at different speeds by creating moments about the geometric center in 6-degree-of-freedom (DOF) space. These commands sent from the ground are provided by the flight control board in the aircraft. The longitudinal and lateral flight stability and properties of different configurations evaluated by dynamic analysis and simulations in 6 DOF spaces are investigated. An algorithm and PID controller are being developed using SPSA to achieve in-flight position and attitude control of an active deformable aircraft. The results are compared with the results of the literature review and the results of the previous article.

With SPSA, the best PID coefficients were obtained in case of morphing.

The effects of quadrotor arm height and hub angle changes affect flight stability. With the SPSA optimization method presented in this study, the attitude is quickly stabilized.

With the optimization method, the most suitable PID coefficients and angle values for the lateral and longitudinal flight stability of the quadrotor are obtained.

The transition rate and PID coefficients are determined by using the optimization method, which is advantageous in terms of cost and practicality.

With the proposed method, the aircraft can change shape to adapt to different environments, and the parameters required for more stable flight for each situation will be calculated, and this will be obtained more quickly and safely with the SPSA optimization method.

The purpose of this paper is to conduct the design, development and testing of a controller for an autonomous small‐scale helicopter.

The hardware in the loop simulation (HILS) platform is developed based on the nonlinear model of JR Voyager G‐260 small‐scale helicopter. Autonomous controllers are verified using the HILS environment prior to flight experiments.

The gains of the multi‐loop cascaded control architecture can be effectively optimized within the HILS environment. Various autonomous flight operations are achieved and it is demonstrated that the prediction from the simulations is in a good agreement with the result from the flight test.

The synthesized controller is effective for the particular test‐bed. For other small‐scale helicopters (with different size and engine specifications), the controller gains must be tuned again.

This work represents a practical control design and testing procedures for an autonomous small‐scale helicopter flight control. The autonomous helicopter can be used for various missions ranging from film making, agriculture and volcanic surveillance to power line inspection.

The research addresses the need for systematic design, development and testing of controller for a small‐scale autonomous helicopter by utilizing HILS environment.

The purpose of this paper is to improve autonomous flight performance of a fixed-wing unmanned aerial vehicle (UAV) via simultaneous morphing wingtip and control system design conducted with optimization, computational fluid dynamics (CFD) and machine learning approaches.

The main wing of the UAV is redesigned with morphing wingtips capable of dihedral angle alteration by means of folding. Aircraft dynamic model is derived as equations depending only on wingtip dihedral angle via Nonlinear Least Squares regression machine learning algorithm. Data for the regression analyses are obtained by numerical (i.e. CFD) and analytical approaches. Simultaneous perturbation stochastic approximation (SPSA) is incorporated into the design process to determine the optimal wingtip dihedral angle and proportional-integral-derivative (PID) coefficients of the control system that maximizes autonomous flight performance. The performance is defined in terms of trajectory tracking quality parameters of rise time, settling time and overshoot. Obtained optimal design parameters are applied in flight simulations to test both longitudinal and lateral reference trajectory tracking.

Longitudinal and lateral autonomous flight performances of the UAV are improved by redesigning the main wing with morphing wingtips and simultaneous estimation of PID coefficients and wingtip dihedral angle with SPSA optimization.

This paper originally discusses the simultaneous design of innovative morphing wingtip and UAV flight control system for autonomous flight performance improvement. The proposed simultaneous design idea is conducted with the SPSA optimization and a machine learning algorithm as a novel approach.

The purpose of this paper is to design a quadrotor with collective morphing using the simultaneous perturbation stochastic approximation (SPSA) optimization algorithm.

Quadrotor design is made by using Solidworks drawing program and some mathematical performance relations. Modelling and simulation are performed in Matlab/Simulink program by using the state space model approaches with the parameters mostly taken from Solidworks. Proportional integral derivative (PID) approach is used as control technique. Morphing amount and the best PID coefficients are determined by using SPSA algorithm.

By using SPSA algorithm, the amount of morphing and the best PID coefficients are determined, and the quadrotor longitudinal and lateral flights are made most stable via morphing.

It takes quite a long time to model the quadrotor in Solidworks and Matlab/Simulink with the state space model and using the SPSA algorithm. However, this situation is overcome with the proposed model.

Optimization with SPSA is very useful in determining the amount of morphing and PID coefficients for quadrotors.

SPSA optimization method is useful in terms of cost, time and practicality.

It is released to improve performance with morphing, to determine morphing rate with SPSA algorithm and to determine PID coefficients accordingly.

Elementary schools have been confronted with large-scale educational reforms as strategies to improve the educational quality. While building school-wide capacity for improvement is considered critical for changing teachers’ classroom practices, there is still little empirical evidence for link between enhanced school capacity for improvement and instructional change. In this study, the authors examined the impact of school improvement capacity on changes in teachers’ classroom practices over a period of time. Leadership practices, school organizational conditions, teacher motivation and teacher learning were used to measure school-wide capacity for improvement. The paper aims to discuss these issues.

Mixed-model analysis of longitudinal data over a four years (2005-2008) period of time from 862 teachers of 32 Dutch elementary schools were used to test the impact of school improvement capacity on changing teachers’ instructional practices.

The results showed that organizational-level conditions and teacher-level conditions play an important, but different role in changing teachers’ classroom practices. Whereas teacher factors mainly affect changes in teachers’ classroom practices, organizational factors are of significant importance to enhance teacher motivation and teacher learning.

More longitudinal research is needed to gain better insight into the opportunities and limits of building school-wide capacity to stimulate instructional change.

By encouraging teachers to question their own beliefs, facilitating opportunities for teachers to work together to solve problems, and through the promotion of shared decision making, school leaders can reinforce the personal and social identification of teachers with the organization. As a consequence, teachers will feel increasingly committed and are more willing to change their classroom practices. Additionally, school leaders can use the findings from this study and the related instrument as a tool for school self-evaluation.

This paper contributes to a deeper understanding of the nature of changes in conditions for school improvement and its influence on changes in teachers’ instructional practices over a period of time.

This study aims to simultaneously and stochastically maximize autonomous flight performance of a variable wing incidence angle having an unmanned aerial vehicle (UAV) and its flight control system (FCS) design.

A small UAV is produced in Iskenderun Technical University Drone Laboratory. Its wing incidence angle is able to change before UAV flight. FCS parameters and wing incidence angle are simultaneously and stochastically designed to maximize autonomous flight performance using an optimization method named simultaneous perturbation stochastic approximation. Obtained results are also benefitted during UAV flight simulations.

Applying simultaneous and stochastic design approach for a UAV having passively morphing wing incidence angle and its flight control system, autonomous flight performance is maximized.

Permission of the Directorate General of Civil Aviation in Turkish Republic is necessary for real-time flights.

Simultaneous stochastic variable wing incidence angle having UAV and its flight control system design approach is so useful for maximizing UAV autonomous flight performance.

Simultaneous stochastic variable wing incidence angle having UAV and its flight control system design methodology succeeds confidence, excellent autonomous performance index and practical service interests of UAV users.

Creating an innovative method to recover autonomous flight performance of a UAV and generating an innovative procedure carrying out simultaneous stochastic variable wing incidence angle having UAV and its flight control system design idea.

This study presents a longitudinal analysis of patterns of investment in advanced manufacturing technologies (AMT) and financial performance. Investments in AMT from fifty manufacturing plants in the metalworking industries are examined. Data was collected via mail surveys administered to fifty manufacturing plants at three separate data collection times: 1994, 1996, and 1998. This study seeks to fill a void in the area of technology management, which is comprised primarily of cross‐sectional studies that do not address the dynamic nature of investments in technology. The results suggest differences in the evolutionary profile of several technologies, including e‐mail, bar coding, robotics, and computer aided design. Further tests indicate that there is a positive relationship between many of these technologies and plant financial performance. Finally, the longitudinal data suggest that there is approximately a two‐year time lag between investment in technology and performance improvements.

Numerous studies have shown that community service during adolescence is associated with positive youth outcomes and future civic engagement (Reinders and Youniss, 2006; Yates and Youniss, 1996). However, less is known about the ways in which students participate in and perceive intermittent, noncurricular community service. The purpose of this study is to examine seventh and eighth grade students' (N = 22) experiences during a common school-wide community service event: the canned food drive.

Data include students' journal responses to questions about the food drive including their feelings about the event, learning that took place, positive parts of the drive and challenges. An inductive qualitative analysis was used.

Analysis of students' responses revealed that most students perceived themselves and their classmates as being very helpful to the community and described feeling happiness and pride from the event, even when participation was minimal or nonexistent. While some students reported awareness of poverty and inequality after the food drive, many of their comments about those receiving the donations included deficit-oriented terminology and cognitive distancing by positioning those experiencing food insecurity as “the other” and different from themselves.

Findings highlight the benefits and shortcomings of community service, as class biases and surface-level ideas about helping may be unintentionally reinforced. Recommendations to address these issues are discussed.

Given the prevalence of community service in schools, qualitative research is needed to understand firsthand how students experience these events.

In acknowledging the reality of climate change, large firms have set internal and external (supplier oriented) targets to reduce their greenhouse gas emissions. This study aims to explore the complex processes behind the evolution and diffusion of carbon reduction strategies in supply networks.

The research uses complex adaptive systems (CASs) as a theoretical framework and presents a single case study of a focal buying firm and its supply network in the food sector. A longitudinal and multilevel analysis is used to discuss the dynamics between the focal firm, the supply network and external environment.

Rather than being a linear and controlled process of adoption implementation outcomes, the transition to reduce carbon in a supply network is much more dynamic, emerging as a result of a number of factors at the individual, organisational, supply network and environmental levels.

The research considers the emergence of a carbon reduction strategy in the food sector, driven by a dominant buying firm. Future research should seek to investigate the diffusion of environmental strategies more broadly and in other contexts.

Findings from the research reveal the limits of the control that a buying firm can exert over behaviours in its network and show the positive influence of consortia initiatives on transitioning to sustainability in supply networks.

CAS is a fairly novel theoretical lens for researching environmental supply network dynamics. The paper offers fresh multilevel insights into the emergent and systemic nature of the diffusion of environmental practices in supply networks.