The dream of intelligent assistants to enhance programmer productivity has now become a concrete reality, with rapid advances in artificial intelligence. Large language models (LLMs) have demonstrated impressive capabilities in various domains based on the vast amount of data used to train them. However, tasks which require structured reasoning or…

This paper systematically explores how Large Language Models (LLMs) generate explanations of code examples of the type used in intro-to-programming courses. As we show, the nature of code explanations generated by LLMs varies considerably based on the wording of the prompt, the target code examples being explained, the programming language, the…

In the last two decades, computational thinking has gained wide relevance in international educational systems. The inclusion of this new type of thinking poses educational challenges with some underlying research questions that need to be answered to meet these challenges with quality. Thus, this study focuses on analyzing the difficulties that…

Large language models (LLMs), such as Codex, hold great promise in enhancing programming education by automatically generating feedback for students. We investigate using LLMs to generate feedback for fixing syntax errors in Python programs, a key scenario in introductory programming. More concretely, given a student's buggy program, our goal is…

Aim/Purpose: This paper is part of a multi-case study that aims to test whether generative AI makes an effective coding assistant. Particularly, this work evaluates the ability of two AI chatbots (ChatGPT and Bing Chat) to generate concise computer code, considers ethical issues related to generative AI, and offers suggestions for how to improve…

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,…

This research is part of the Artificial Intelligence Virtual Trainer (AI-VT) project which aims to create a system that can identify the user's skills from a text by means of machine learning. AI-VT is a case-based reasoning learning support system can generate customized exercise lists that are specially adapted to user needs. To attain this…

Constructing a consensus problem space from extensive qualitative data for an ill-structured real-life problem and expressing the result to a broader audience is challenging. To effectively communicate a complex problem space, visualization of that problem space must elucidate inter-causal relationships among the problem variables. In this…

In order to improve the accessibility and user friendliness of an accurately pretrained stacking ensemble machine learning regressor used to predict sulfate levels (mg/L) in Acid Mine Drainage (AMD), a Graphical User Interface (GUI) was developed using Python by combining human input with ChatGPT and deployed in the Jupyter Notebook environment.…

ChatGPT has received considerable attention in education, particularly in programming education because of its capabilities in automated code generation and program repairing and scoring. However, few empirical studies have investigated the use of ChatGPT to customize a learning system for scaffolding students' computational thinking. Therefore,…

Structured Query Language (SQL) is still the de facto database query language widely used in industry and taught in almost all university level database courses. The role of SQL is further strengthened by the emergence of NewSQL systems which use SQL as their query language as well as some NoSQL systems, e.g., Cassandra and DynamoDB, which base…

As students learn how to program, both their programming code and their understanding of it evolves over time. In this work, we present a general data-driven approach, named "Temporal-ASTNN" for modeling student learning progression in open-ended programming domains. Temporal-ASTNN combines a novel neural network model based on abstract…

A posttest-only control group experimental design compared novice Arduino programmers who developed their own programs (self-programming group, n = 17) with novice Arduino programmers who used ChatGPT 3.5 to write their programs (ChatGPT-programming group, n = 16) on the dependent variables of programming scores, interest in Arduino programming,…

DEVS (Discrete Event System Specification) is a formalism that was introduced in the mid-1970s by Bernard Zeigler, for modeling and analysis of discrete event systems. DEVS is essentially a formal mathematical language for specifying complex systems through models that can be simulated and has been executed in object-oriented software, DEVSJava…

Aim/Purpose: This study aims to investigate the perceptions of programming instructors among the Information Technology faculty members at AL al-Bayt University regarding the effectiveness of ChatGPT in supporting the programming instructional process. This study also aims to explore their experiences concerning the potential benefits and adverse…