In order to support query-based learning, this research focuses on the applications of an AI tool named *** in the instruction of computerscience and engineering students in Structured Query Language (SQL). As the fo...
详细信息
ISBN:
(数字)9798331517953
ISBN:
(纸本)9798331517960
In order to support query-based learning, this research focuses on the applications of an AI tool named *** in the instruction of computerscience and engineering students in Structured Query Language (SQL). As the foundation for obtaining data from databases and manipulating vast volumes of data in a variety of vocations, SQL is essential to the field of data management. For computerscience students, database knowledge and skills—especially SQL—are essential because they provide them with insights into the querying, altering, and analyzing of data—a crucial component of software engineering, data administration, and database management. Appropriate and effective techniques, including tutoring, which provide the student with individualised support, are particularly beneficial for learning SQL. It was noted that both situations allowed for the temporary usage of ***, as well as feedback to encourage selfdirected product immersion. In an effort to provide *** in a learning environment, this article reports on variations in student performance, practical SQL skills, and engagement levels. The article compares the efficacy of ***'s case studies and effectiveness studies to other traditional tutoring methods, describing how the platform encouraged students to practise SQL outside of the classroom. The findings demonstrate that nearly all students made progress in both writing and composing SQL queries.
A career is a crucial aspect for any person to fulfill their desires through hard work. During their studies, students cannot find the best career suggestions unless they receive meaningful guidance tailored to their ...
详细信息
Artificial Intelligence (AI), with ChatGPT as a prominent example, has recently taken center stage in various domains including higher education, particularly in computerscience and engineering (CSE). The AI revoluti...
详细信息
ISBN:
(数字)9798350394023
ISBN:
(纸本)9798350394030
Artificial Intelligence (AI), with ChatGPT as a prominent example, has recently taken center stage in various domains including higher education, particularly in computerscience and engineering (CSE). The AI revolution brings both convenience and controversy, offering substantial benefits while lacking formal guidance on their application. The primary objective of this work is to comprehensively analyze the pedagogical potential of ChatGPT in CSE education, understanding its strengths and limitations from the perspectives of educators and learners. We employ a systematic approach, creating a diverse range of educational practice problems within CSE field, focusing on various subjects such as data science, programming, AI, machine learning, networks, and more. According to our examinations, certain question types, like conceptual knowledge queries, typically do not pose significant challenges to ChatGPT, and thus, are excluded from our analysis. Alternatively, we focus our efforts on developing more in-depth and personalized questions and project-based tasks. These questions are presented to ChatGPT, followed by interactions to assess its effectiveness in delivering complete and meaningful responses. To this end, we propose a comprehensive five-factor reliability analysis framework to evaluate the responses. This assessment aims to identify when ChatGPT excels and when it faces challenges. Our study concludes with a correlation analysis, delving into the relationships among subjects, task types, and limiting factors. This analysis offers valuable insights to enhance ChatGPT's utility in CSE education, providing guidance to educators and students regarding its reliability and efficacy.
This innovative practice full paper presents an empirical study aimed at evaluating the potential of ChatGPT, an advanced AI-driven chatbot, as a supplementary educational tool in undergraduate computerscience and So...
详细信息
ISBN:
(数字)9798350351507
ISBN:
(纸本)9798350363067
This innovative practice full paper presents an empirical study aimed at evaluating the potential of ChatGPT, an advanced AI-driven chatbot, as a supplementary educational tool in undergraduate computerscience and Software engineering (CSSE) courses. The study, initiated in the summer of 2023, focused on assessing ChatGPT's capabilities in generating accurate and complete computer code, identifying and rectifying code defects (bugs), and its scalability in handling larger programs. To achieve this, we conducted a series of experiments with ChatGPT. In one experiment, we introduced bugs into small programs from introductory CSSE courses. ChatGPT was tasked with detecting these defects and providing recommendations for fixing them. We evaluated ChatGPT's effectiveness in bug detection, the quality of its recommendations, and the completeness of the proposed solutions. We sought answers to questions such as whether ChatGPT found all injected defects, provided appropriate recommendations, and delivered high-quality solutions based on criteria like code completeness, size, complexity, and readability. In another experiment, ChatGPT was asked to generate code for assignments from previous CSSE courses, including Intro to computerscience and Programming in C++, Intro to Python Programming, and Object-Oriented Programming and Data Structures using Java. We assessed the generated code's correctness and quality in comparison to student-written code. Similarly, in a third experiment, we evaluated ChatGPT's ability to generate larger programs using requirement specifications from an upper-division CSSE course on Agile Software engineering. Analyzing both qualitative and quantitative data from these experiments during the summer, we determined that ChatGPT showed promise as an educational tool. Consequently, we developed a plan to integrate ChatGPT into select CSSE courses for the fall semester of 2023. Specifically, ChatGPT was integrated into two of our introductory CSSE cou
Facial recognition systems on learning platforms like Moodle enable fast and efficient evaluation, automating the detection of impersonation in online exams. This project implements a Moodle plugin that performs facia...
Facial recognition systems on learning platforms like Moodle enable fast and efficient evaluation, automating the detection of impersonation in online exams. This project implements a Moodle plugin that performs facial recognition on the student attempting to take a quiz. It consists of two parts for authentication through a webcam: the first part occurs before accessing the quiz, and the second part involves surveillance through a camera during the quiz. The plugin was developed using the PHP and JavaScript programming languages, as well as Face-api. The JavaScript API detects and recognizes faces in the web browser using Tiny Yolo v2 and FaceRecognizerNet. It compares a student’s photo or image with the image from their webcam while they are taking the quiz. The Moodle plugin achieved an average error probability of 39.39% for face detection similarity distance.
Clausius was the first to coin the term 'entropy' roughly 160 years ago. Since then, many scholars from several scientific fields have continued to enhance, develop, and interpret the data. This study describe...
详细信息
Research has demonstrated the positive influence of Undergraduate Research Experience (URE) programs in science, Technology, engineering, and Mathematics (STEM) on students' educational journey and their developme...
Research has demonstrated the positive influence of Undergraduate Research Experience (URE) programs in science, Technology, engineering, and Mathematics (STEM) on students' educational journey and their development as scientists, ultimately aiding them in making informed career choices. However, traditionally, URE programs have primarily targeted junior and senior students who already possess disciplinary knowledge and exhibit a strong inclination to persist in STEM fields. This study aims to examine the effects of involving freshmen in the Industry-Research Inclusion in STEM Education (I-RISE) program, specifically in the disciplines of electrical engineering (EE) and computerscience (CS), on student retention. The I-RISE program integrated research opportunities for undergraduate students with mentorship activities, facilitating the acquisition of relevant skills in applied computing and engineering techniques, research methodologies, and the attainment of internships. Analyzing the retention rates of three distinct cohorts of I-RISE participants over a span of three years revealed significantly higher retention rates compared to students who did not partake in the I-RISE program.
Generative AI assistants are AI-powered applications that can provide personalized responses to user queries or prompts. A variety of AI assistants have recently been released, and among the most popular is OpenAI'...
Generative AI assistants are AI-powered applications that can provide personalized responses to user queries or prompts. A variety of AI assistants have recently been released, and among the most popular is OpenAI's ChatGPT. In this work-in-progress in innovative practice, we explore evidence-based learning strategies and the integration of Generative AI for computerscience and engineering education. We expect this research will lead to innovative pedagogical approaches to enhance undergraduate computerscience and engineering education. In particular, we describe how ChatGPT was used in two computing-based courses: a Junior-level course in database systems and a Senior-level class in mobile application development. We identify four evidence-based learning strategies: well-defined learning goals, authentic learning experiences, structured learning progression, and strategic assessment. We align these strategies with the two aforementioned courses and evaluate the usefulness of ChatGPT specifically in achieving the learning goals. Combining Generative AI with evidence-based learning has the potential to transform modern education into a more personalized learning experience.
This Work-in-Progress research paper evaluates the validity of Large Language Models (LLMs) as conversational AI tutors for computerscience learning. While current engineering education literature has predominantly e...
详细信息
ISBN:
(数字)9798350351507
ISBN:
(纸本)9798350363067
This Work-in-Progress research paper evaluates the validity of Large Language Models (LLMs) as conversational AI tutors for computerscience learning. While current engineering education literature has predominantly emphasized the rapid evolution of LLMs as conversational AI tutors for programming languages, the exploration into their effectiveness within general STEM topics remains comparatively scarce. This WIP study thus centers on evaluating the potential of LLMs to facilitate understanding of core hardware design concepts critical to computerscience and engineering (CSE) education. By cross-checking the responses from generative AI chatbots to an openended CSE-based question, we aimed to uncover how LLMs, such as ChatGPT-3.5, Claude, Gemini, and Meta AI, can contribute to teaching and learning of general CSE courses instead of a specifically coding-based one. Our method involved simulating a student query on the popular debate between CISC vs. RISC related to computer architecture and analyzing the chatbots' responses. This initial collection of data served as the foundation for a continual comparative analysis aimed at determining the inherent instructional value of each LLM and its validity and reliability. To systematically assess the responses, we introduced an evaluation framework focusing on metrics, such as response accuracy, persuasiveness, and depth of explanation. The current work anticipates not only enriching our understanding of how these advanced LLMs can support general CSE education but also identifying areas where further development is needed for a more holistic integration of LLM-based chatbots in assisting student comprehension in the overarching engineering education.
ChatGPT has become the most popular regenerative AI application, used for obtaining responses for queries in different domains. Some responses of ChatGPT reported in the internet are accurate, others are funny, and so...
详细信息
暂无评论