This work analyzes the effectiveness of an artificial intelligence (AI) community- building workshop designed for high school teachers and it focuses on contemporary issues related to AI concepts and applications. A group of high school teachers from local education districts attended a one-day AI hands-on workshop at our university. The workshop included several AI-related topics and hands-on examples and exercises aiming to introduce AI concepts and tools relevant to pre-college education. The participating teachers were expected to become a part of a collaborative network created to design, develop, and implement novel AI learning modules for high school students. Initial and a post-training surveys have been used to measure the impact of this training and to obtain a better understanding of teachers’/students’ readiness for additional hands-on AI experiences and further training. The surveys showed that the teachers gained valuable AI knowledge, AI tools, and attitudes that could help them when introducing AI concepts, applications, and AI ethics to their students. The teachers also explored various AI-based teaching tools that they could use to improve learning outcomes for their students. Based on the positive results of this work, one of the authors developed and implemented a three-credit graduate elective course ED 537 AI in K-12 Education at the School of Education at our university. This is an updated and improved version of the ASEE conference paper titled “Engaging High School Teachers in Artificial Intelligence Concepts and Applications.”
ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data
... Show MoreABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel
... Show MoreIt is an established fact that substantial amounts of oil usually remain in a reservoir after primary and secondary processes. Therefore; there is an ongoing effort to sweep that remaining oil. Field optimization includes many techniques. Horizontal wells are one of the most motivating factors for field optimization. The selection of new horizontal wells must be accompanied with the right selection of the well locations. However, modeling horizontal well locations by a trial and error method is a time consuming method. Therefore; a method of Artificial Neural Network (ANN) has been employed which helps to predict the optimum performance via proposed new wells locations by incorporatin
Abstract
This study aims at investigating the effectiveness of the cooperative inquiry strategy in developing the achievement and development of mathematical communication skills of elementary school students. To achieve this aim, the experimental method was utilized. The study sample consisted of an experimental group (n = 34) and a control group (n = 31), which were randomly selected from primary schools. A Teacher's Guide for teaching a unit entitled "Statistics and Graphic Representations" for the sixth elementary graders in the first semester were devised. A (30) multiple-choice item achievement test distributed at the levels of (recall, comprehension, and application), as well as an (18) item mathematical c
... Show MoreBackground: Insufficient sleep due to excessive media use is linked to decrease physical activity, poor nutrition, obesity, and decreased overall health-related quality of life.
Objectives: To assess the effect of using the internet and social media on the sleep of 4th-stage secondary school students.
Subjects and Methods: Cross-sectional study with the analytic element; for 500 secondary school students, obtained by choosing two schools randomly from each of the six educational directorates, by using a structured questionnaire.
Result: Secondary scho
... Show MoreWriting in English is one of the essential factors for successful EFL learning .Iraqi students at the preparatory schools encounter problems when using their background knowledge in handling subskills of writing(Burhan,2013:164).Therefore, this study aims to investigate the 4thyear preparatory school students’ problems in English composition writing, and find solutions to these pro
... Show MoreThe Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The develope
... Show MoreThe majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value <0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe
Background: White spot lesion is the first visible sign of dental caries that is characterized by demineralized lesion underneath an intact surface. Several studies demonstrated that they could be treated using noninvasive techniques like the use of fluoride or casein phospho-peptide and amorphous calcium phosphate. Improvement in aesthetic outcomes by covering the demineralized enamel is one of the advantages of the use of resin infiltration and opal-ustre microabrasion, which are two new techniques that had been used for treatment of white spot lesion. The purpose of this study was to evaluate the impact of resin infiltration and microabrasion in the microhardness of the artificial white spot lesions at various depths. Material and method
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