This study investigated the effect of using brainstorming as a teaching technique on the students’ performance in writing different kinds of essays and self regulation among the secondary students. The total population of this study, consisted of (51) female students of the 5th Secondary grade in Al –kawarzmi School in Erbil during the academic year 2015-2016. The chosen sample consisted of 40 female students, has been divided into two groups. Each one consists of (20) students to represent the experimental group and the control one. Brainstorming technique is used to teach the experimental group, and the conventional method is used to teach the control group. The study instruments used for collecting the data are an essay writing test and Academic Self-regulated Learning Scale. The performance on an essay writing task and Academic Self-regulated Learning Scale has been taken into account as the pretest and posttest in both groups. The validity and reliability of the study instruments are acceptable. T-test formula is used to analyze the data collected. The analysis results show that the experimental group's performance and self- regulation are significantly higher than the performance and self regulation of the control group at (0.05) level of significance. Therefore, the brainstorming teaching technique significantly affects the students’ performance in writing essays and self- regulation.
The Effect of Using Brainstorming Technique on the Essay Writing and Self- regulation Learning of the Iraqi Secondary Students
Brainstorming Technique
Self- regulation
Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Tuning PID Controller by Neural Network for Robot Manipulator Trajectory Tracking
PID controller
Neural Network
Self tuning controller
Robot manipulator
Trajectory tracking
Ziegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of PID controller. This tuning method is simple and gives fixed values for the coefficients which make PID controller have weak adaptabilities for the model parameters variation and changing in operating conditions. In order to achieve adaptive controller, the Neural Network (NN) self-tuning PID control is proposed in this paper which combines conventional PID controller and Neural Network learning capabilities. The proportional, integral and derivative (KP, KI, KD) gains are self tuned on-line by the NN output which is obtained due to the error value on the desired output of the system under control. The conventio
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