Related papers: AutoGrad: Automated Grading Software for Mobile Ga…

We address the problem of group fairness in classification, where the objective is to learn models that do not unjustly discriminate against subgroups of the population. Most existing approaches are limited to simple binary tasks or involve…

The use of new technologies in higher education has surprisingly emphasized students' tendency to adopt a passive behavior in class. Participation and interaction of students are essential to improve academic results. This paper describes…

We present AutoGLM, a new series in the ChatGLM family, designed to serve as foundation agents for autonomous control of digital devices through Graphical User Interfaces (GUIs). While foundation models excel at acquiring human knowledge,…

Student's academic performance prediction empowers educational technologies including academic trajectory and degree planning, course recommender systems, early warning and advising systems. Given a student's past data (such as grades in…

This experience report explores the effects of ungraded assignments on the learning experience of students in an introductory computing course. Our study examines the impact of ungraded assignments on student engagement, understanding, and…

Artificial intelligence (AI) retrieval-augmented generation (RAG) tools now enable educators to transform course materials into diverse multimedia at scale. However, it remains unclear whether such AI-generated content functions as a…

The demand for quality in mobile applications has increased greatly given users' high reliance on them for daily tasks. Developers work tirelessly to ensure that their applications are both functional and user-friendly. In pursuit of this,…

With recent advancements in artificial intelligence (AI), there has been growing interest in using state of the art (SOTA) AI solutions to provide assistance in grading handwritten answer sheets. While a few commercial products exist, the…

The increasing prevalence of mobile apps has led to a proliferation of resource usage scenarios in which they are deployed. This motivates the need to specialize mobile apps based on diverse and varying preferences of users. We propose a…

Proof Blocks is a software tool which enables students to write proofs by dragging and dropping prewritten proof lines into the correct order. These proofs can be graded completely automatically, enabling students to receive rapid feedback…

In this paper, we discuss our experience in designing and teaching a course on Software Engineering Project Management, where the focus is on Agile/Scrum development and Requirement Engineering activities. The course has undergone…

Modern code review is a process in which an incremental code contribution made by a code author is reviewed by one or more peers before it is committed to the version control system. An important element of modern code review is verifying…

Modern software systems require various capabilities to meet architectural and operational demands, such as the ability to scale automatically and recover from sudden failures. Self-adaptive software systems have emerged as a critical focus…

Due to the competitive environment, mobile apps are usually produced under pressure with lots of complicated functionality and UI pages. Therefore, it is challenging for various roles to design, understand, test, and maintain these apps.…

As more and more academic papers are being submitted to conferences and journals, evaluating all these papers by professionals is time-consuming and can cause inequality due to the personal factors of the reviewers. In this paper, in order…

Developing mobile applications remains difficult, time consuming, and error-prone, in spite of the number of existing platforms and tools. In this paper, we define MoDroid, a high-level modeling language to ease the development of Android…

The use of automatic grading tools has become nearly ubiquitous in large undergraduate programming courses, and recent work has focused on improving the quality of automatically generated feedback. However, there is a relative lack of data…

Grading handwritten, open-ended responses remains a major bottleneck in large university STEM courses. We introduce Pensieve (https://www.pensieve.co), an AI-assisted grading platform that leverages large language models (LLMs) to…

The classical AdaGrad method adapts the learning rate by dividing by the square root of a sum of squared gradients. Because this sum on the denominator is increasing, the method can only decrease step sizes over time, and requires a…

The advent of large language models (LLMs) in the education sector has provided impetus to automate grading short answer questions. LLMs make evaluating short answers very efficient, thus addressing issues like staff shortage. However, in…