Active Learning And Creative Thinking
HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023
In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A
... Show MoreThe aim of this paper is to find out the effects of the strategy of productive thinking upon the student’s achievement for the subject of research methodology in the College of Islamic Sciences. Achieving this objective, the researchers set the null hypotheses: (1) No difference is noticed to be statistically significant at the level of significance (0.05) among the student’s mean scores in the experimental group who were taught by the strategy of productive thinking, and the student’s mean scores in the control group who studied by the traditional method in the achievement test. (2) At level of sig. (0.05), there is no statistically significant difference in the mean of scores of the pre-tests and post ones in the achievement test of
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
The research aims to identify the effect of jigsaw strategy in learning achievement and engaging for the third grade intermediate students in chemistry. The research sample consisted of (61) students distributed in two experimental and control groups. The research tools consisted in the achievement test and the measure of engaging learning. The results showed that there are statistically significant differences at the level of (α = 0.05) between the experimental group and the control group in both the achievement test and the measure of learning involvement for the benefit of the experimental group. In this light, the researcher recommended the use of jigsaw strategy for teaching the subject matter. Lamia because of its impact in raising
... Show More