EFL paraphrasing skills with QuillBot: Unveiling students' enthusiasm and insights

EFL students' attitudes are crucial for the development of writing abilities, which in the age of cutting-edge technology depend extensively on artificial intelligence -mediated tools, and paraphrasing draws no exception. Therefore, this study aims to identify English as a foreign language student’s enthusiasm and insights about utilizing QuillBot to improve their paraphrasing skills. To achieve the study objectives, the quasi-experimental design was employed. Thirty-one preparatory year students were recruited to answer a questionnaire and semi-structured interview having verified the validity and reliability of the instruments. The sample of the test demonstrated that students improved their performance in synonyms, sentence structure, and word choice. The respondents hold high enthusiasm and insights toward utilizing QuillBot to improve their paraphrasing skills. In addition, students had positive feelings about utilizing QuillBot to improve their paraphrasing skills. In light of the findings, the researchers recommended employing QuillBot in a writing class while learning paraphrasing skills

Development of an Energy Efficient and Cost Effective Autonomous Vehicle Research Platform

Commercialization of autonomous vehicle technology is a major goal of the automotive industry, thus research in this space is rapidly expanding across the world. However, despite this high level of research activity, literature detailing a straightforward and cost-effective approach to the development of an AV research platform is sparse. To address this need, we present the methodology and results regarding the AV instrumentation and controls of a 2019 Kia Niro which was developed for a local AV pilot program. This platform includes a drive-by-wire actuation kit, Aptiv electronically scanning radar, stereo camera, MobilEye computer vision system, LiDAR, inertial measurement unit, two global positioning system receivers to provide heading information, and an in-vehicle computer for driving environment perception and path planning. Robotic Operating System software is used as the system middleware between the instruments and the autonomous application algorithms. After selection, installation, and integration of these components, our results show successful utilization of all sensors, drive-by-wire functionality, a total additional power* consumption of 242.8 Watts (*Typical), and an overall cost of $118,189 USD, which is a significant saving compared to other commercially available systems with similar functionality. This vehicle continues to serve as our primary AV research and development platform