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Hsiao-Ping Hsu – TechTrends: Linking Research and Practice to Improve Learning, 2025
The advancement of large language model-based generative artificial intelligence (LLM-based GenAI) has sparked significant interest in its potential to address challenges in computational thinking (CT) education. CT, a critical problem-solving approach in the digital age, encompasses elements such as abstraction, iteration, and generalisation.…
Descriptors: Programming, Prompting, Computation, Thinking Skills
Oscar Karnalim; Hapnes Toba; Meliana Christianti Johan – Education and Information Technologies, 2024
Artificial Intelligence (AI) can foster education but can also be misused to breach academic integrity. Large language models like ChatGPT are able to generate solutions for individual assessments that are expected to be completed independently. There are a number of automated detectors for AI assisted work. However, most of them are not dedicated…
Descriptors: Artificial Intelligence, Academic Achievement, Integrity, Introductory Courses
Damien S. K. Samways; Lara Yousef; Scott A. Sheffield – Advances in Physiology Education, 2025
Although interactive software has long been employed to complement traditional lecture and laboratory classes, instructors have typically been limited to premade programs produced by others with significant programming experience. Furthermore, many existing programs have limited platform cross-compatibility, with few compatible with the most…
Descriptors: Physiology, Pharmacology, Programming, Technology Uses in Education
Babak Mahjour; Andrew McGrath; Andrew Outlaw; Ruheng Zhao; Charles Zhang; Tim Cernak – Journal of Chemical Education, 2023
Data science is becoming a mainstay in research. Despite this, very few STEM graduates matriculate with basic formal training in programming. The current lesson plan was developed to introduce undergraduates studying chemistry or biology to chemoinformatics and data science in medicinal chemistry. The objective of this lesson plan is to introduce…
Descriptors: Undergraduate Students, Chemistry, Biology, Information Science
Venigalla, Akhila Sri Manasa; Chimalakonda, Sridhar – Smart Learning Environments, 2023
E-textbooks are one of the commonly used sources to learn programming, in the domain of computer science and engineering. Programming related textbooks provide examples related to syntax, but the number of examples are often limited. Thus, beginners who use e-textbooks often visit other sources on the internet for examples and other information.…
Descriptors: Electronic Publishing, Textbooks, Documentation, Programming
Venkatasubramanian, Venkat – Chemical Engineering Education, 2022
The motivation, philosophy, and organization of a course on artificial intelligence in chemical engineering is presented. The purpose is to teach undergraduate and graduate students how to build AI-based models that incorporate a first principles-based understanding of our products, processes, and systems. This is achieved by combining…
Descriptors: Artificial Intelligence, Chemical Engineering, College Students, Teaching Methods
Sharma, Priynka; Harkishan, Mayuri – Education and Information Technologies, 2022
Intelligent Tutoring Systems (ITSs) are educational systems that reflect knowledge using artificial intelligence implements. In this paper, we give an outline of the Programming-Tutor architectural design with the core implements on user interaction. This pilot proposal is for designing a model domain of a subset in the computer programming…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Programming, Online Courses
Lafuente, Deborah; Cohen, Brenda; Fiorini, Guillermo; Garci´a, Agusti´n Alejo; Bringas, Mauro; Morzan, Ezequiel; Onna, Diego – Journal of Chemical Education, 2021
Machine learning, a subdomain of artificial intelligence, is a widespread technology that is molding how chemists interact with data. Therefore, it is a relevant skill to incorporate into the toolbox of any chemistry student. This work presents a workshop that introduces machine learning for chemistry students based on a set of Python notebooks…
Descriptors: Undergraduate Students, Chemistry, Electronic Learning, Artificial Intelligence
Robins, Anthony V. – ACM Transactions on Computing Education, 2022
This paper explores a major theoretical framework from psychology, Dual Process Theory (DPT), which has received surprisingly little attention in the computing education literature. DPT postulates the existence of two qualitatively different kinds of cognitive systems, a fast, intuitive "System 1" and a slow, reflective "System…
Descriptors: Learning Theories, Cognitive Processes, Intelligence, Long Term Memory
Pang, Bo; Nijkamp, Erik; Wu, Ying Nian – Journal of Educational and Behavioral Statistics, 2020
This review covers the core concepts and design decisions of TensorFlow. TensorFlow, originally created by researchers at Google, is the most popular one among the plethora of deep learning libraries. In the field of deep learning, neural networks have achieved tremendous success and gained wide popularity in various areas. This family of models…
Descriptors: Artificial Intelligence, Regression (Statistics), Models, Classification
Kahn, Ken; Winters, Niall – British Journal of Educational Technology, 2021
Constructionism, long before it had a name, was intimately tied to the field of Artificial Intelligence. Soon after the birth of Logo at BBN, Seymour Papert set up the Logo Group as part of the MIT AI Lab. Logo was based upon Lisp, the first prominent AI programming language. Many early Logo activities involved natural language processing,…
Descriptors: Artificial Intelligence, Man Machine Systems, Programming Languages, Programming
Baosen Zhang; Ariana Frkonja-Kuczin; Zhong-Hui Duan; Aliaksei Boika – Journal of Chemical Education, 2023
Computer vision (CV) is a subfield of artificial intelligence (AI) that trains computers to understand our visual world based on digital images. There are many successful applications of CV including face and hand gesture detection, weather recording, smart farming, and self-driving cars. Recent advances in computer vision with machine learning…
Descriptors: Classification, Laboratory Equipment, Visual Aids, Optics
Cai, Zhiqiang; Hu, Xiangen; Graesser, Arthur C. – Grantee Submission, 2019
Conversational Intelligent Tutoring Systems (ITSs) are expensive to develop. While simple online courseware could be easily authored by teachers, the authoring of conversational ITSs usually involves a team of experts with different expertise, including domain experts, linguists, instruction designers, programmers, artists, computer scientists,…
Descriptors: Programming, Intelligent Tutoring Systems, Courseware, Educational Technology
Quille, Keith; Bergin, Susan – Computer Science Education, 2019
Background and Context: Computer Science attrition rates (in the western world) are very concerning, with a large number of students failing to progress each year. It is well acknowledged that a significant factor of this attrition, is the students' difficulty to master the introductory programming module, often referred to as CS1. Objective: The…
Descriptors: Computer Science Education, Introductory Courses, Programming, Student Attrition
Devedzic, Vladan – International Journal of Artificial Intelligence in Education, 2016
If you ask me "Will Semantic Web 'ever' happen, in general, and specifically in education?", the best answer I can give you is "I don't know," but I know that today we are still far away from the hopes that I had when I wrote my paper "Education and The Semantic Web" (Devedzic 2004) more than 10 years ago. Much of the…
Descriptors: Web 2.0 Technologies, Semantics, Web Based Instruction, Visual Aids

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