Journal of Engineering and Applied Computing

Within The Context of An Online TBLL Environment, Enhancing the Negotiation of Meaning Through Task Familiarity Through the Utilization of Subtitled Videos

2024-05-10T21:14:26+03:00

Through the utilization of subtitled films, this study investigates the influence that task familiarity has on the process of meaning negotiation within the context of an online task-based language learning (TBLL) environment. The purpose of this research is to investigate the extent to which non-native speakers (NNSs) negotiate meaning in an effort to hasten the process of learning a second language and improve the ability to comprehend input. By utilizing a chat capability in WebCT-Vista and an online TBLL environment that was designed specifically for this research, ten NNS-NNS dyads worked together to complete four communicative tasks. There were five pairs of students who were shown videos with subtitles before they were required to complete the activity. The remaining five pairs of students completed the tasks without watching the videos. The level of meaning negotiation was determined by Smith (2003) by employing a variant of Gass and Varonis's (1985) negotiation of meaning sequences model for online communication. This model was specifically designed for online communication. The information that was collected from the transcripts of the conversations revealed that non-native speakers (NNSs) who had a greater level of familiarity with the tasks engaged in more extensive meaning negotiation in comparison to those who did not have such familiarity about the tasks.

The Effects of Distinct Learning Models and Techniques on The Online Education of Adults

2024-05-10T21:32:00+03:00

The purpose of this study was to investigate the ways in which the degree of computer skills, preferred learning styles, and prior experience with online courses influenced the acquisition of knowledge among adult learners who were participating in an online special education course. There were a total of forty-six adult students that participated in the research project and registered for a special education course that was offered online. Based on the findings of the study, it was discovered that the learning styles and preferences of adult students have a substantial impact on their knowledge acquisition. Additionally, the study discovered that computer proficiency has a moderately positive link with academic achievement. During the course of the research, it was discovered that there was no substantial connection between previous involvement in online courses and achievement in web-based courses.

Keywords: Web-based learning, learning styles, computer skills, adult learners

Creating a Learning Taxonomy Particular to Computer Science

2024-05-11T10:50:19+03:00

A growing number of classes are incorporating Bloom's taxonomy of the cognitive domain as well as the SOLO taxonomy into their course design and evaluation processes. On the other hand, their applicability in the field of computer science is restricted in some ways. The purpose of this study is to investigate the existing state of knowledge concerning the implementation of educational taxonomies in the field of computer science education. It is advocated that a new taxonomy be developed, and the difficulties that arise in this particular contextual setting are emphasized. In addition to this, it analyzes the potential applications of this taxonomy in applied courses, particularly those that are focused on the industry of programming.

Keywords: Computer science education, taxonomies of learning, curricula, assessment, credit transfer, benchmarking

Innovations in Autonomous Vehicles: Engineering Challenges and Solutions for Safe Transportation

2024-05-13T14:08:50+03:00

Autonomous vehicles (AVs) represent a paradigm shift in transportation, promising increased safety, efficiency, and accessibility. However, the widespread adoption of AVs is hindered by various engineering challenges. This paper explores the current innovations in AV technology, highlighting key engineering hurdles and proposing solutions to ensure safe transportation in the autonomous era.

Emerging Trends in Cybersecurity for Applied Computing: Securing Digital Infrastructures

2024-05-13T14:05:21+03:00

This paper explores the dynamic landscape of cybersecurity within the domain of applied computing, focusing on the imperative of securing digital infrastructures. As technological innovations continue to redefine industries and societies, the proliferation of interconnected systems presents unprecedented challenges in safeguarding sensitive data and critical assets. Through an analysis of emerging trends, including the evolving threat landscape, cryptographic solutions, AI-driven security mechanisms, and governance frameworks, this study delineates strategies to fortify digital infrastructures against cyber threats. By elucidating key challenges and proposing innovative solutions, this research contributes to the advancement of cybersecurity practices in applied computing, thereby enhancing the resilience of organizations in the face of evolving cyber risks.

Machine Learning Applications in Biomedical Engineering: Revolutionizing Healthcare

2024-05-13T14:12:18+03:00

Machine learning (ML) has emerged as a powerful tool in biomedical engineering, transforming healthcare delivery and patient outcomes. This article explores the diverse applications of ML in biomedical engineering, ranging from medical imaging and diagnostics to personalized treatment strategies. By leveraging large datasets and sophisticated algorithms, ML algorithms have enabled the extraction of valuable insights from complex biomedical data, leading to enhanced disease detection, prognostication, and treatment optimization. This paper provides a comprehensive overview of the current state-of-the-art ML techniques in biomedical engineering and discusses their potential impact on revolutionizing healthcare.