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Online learning and MOOCs have become increasingly popular in recent years, and the trend will continue, given the technology boom. There is a dire need to observe learners' behavior in these online courses, similar to what instructors do…
Continual learning of a stream of tasks is an active area in deep neural networks. The main challenge investigated has been the phenomenon of catastrophic forgetting or interference of newly acquired knowledge with knowledge from previous…
A key capability of an intelligent system is deciding when events from past experience must be remembered and when they can be forgotten. Towards this goal, we develop a predictive model of human visual event memory and how those memories…
Language models often struggle with handling factual knowledge, exhibiting factual hallucination issue. This makes it vital to evaluate the models' ability to recall its parametric knowledge about facts. In this study, we introduce a…
Large-Language Models (LLMs) are changing the way learners acquire knowledge outside the classroom setting. Previous studies have shown that LLMs seem effective in generating to short and simple questions in introductory CS courses using…
Performance of text classification models tends to drop over time due to changes in data, which limits the lifetime of a pretrained model. Therefore an ability to predict a model's ability to persist over time can help design models that…
Machine unlearning techniques aim to mitigate unintended memorization in large language models (LLMs). However, existing approaches predominantly focus on the explicit removal of isolated facts, often overlooking latent inferential…
Change impact analysis consists in predicting the impact of a code change in a software application. In this paper, we take a learning perspective on change impact analysis and consider the problem formulated as follows. The artifacts that…
In category learning, a growing body of literature has increasingly focused on exploring the impacts of interleaving in contrast to blocking. The sequential attention hypothesis posits that interleaving draws attention to the differences…
Context: Motivation is known to improve performance. In software development in particular, there has been considerable interest in the motivation of contributors to open source. Objective: We identify 11 motivators from the literature…
In this paper, we investigate the effect of TDD, as compared to a non-TDD approach, as well as its retainment (or retention) over a time span of (about) six months. To pursue these objectives, we conducted a (quantitative) longitudinal…
Annotations have been formally introduced into Java since Java 5. Since then, annotations have been widely used by the Java community for different purposes, such as compiler guidance and runtime processing. Despite the ever-growing use,…
Despite exceptional capabilities in knowledge-intensive tasks, Large Language Models (LLMs) face a critical gap in understanding how they internalize new knowledge, particularly how to structurally embed acquired knowledge in their neural…
Massive open online courses (MOOCs), which offer open access and widespread interactive participation through the internet, are quickly becoming the preferred method for online and remote learning. Several MOOC platforms offer the service…
Software developers use metrics to evaluate code quality and productivity, but these practices are still rare in programming education. This project bridges the gap by collecting real-time learning analytics from individual student and…
In continual learning, knowledge must be preserved and re-used between tasks, maintaining good transfer to future tasks and minimizing forgetting of previously learned ones. While several practical algorithms have been devised for this…
This paper addresses a key challenge in MOOC dropout prediction, namely to build meaningful representations from clickstream data. While a variety of feature extraction techniques have been explored extensively for such purposes, to our…
One of the main motivations of studying continual learning is that the problem setting allows a model to accrue knowledge from past tasks to learn new tasks more efficiently. However, recent studies suggest that the key metric that…
Providing consistent summative assessment to students is important, as the grades they are awarded affect their progression through university and future career prospects. While small cohorts are typically assessed by a single assessor,…
The use of Multimedia applications in Learning provides useful concepts for Instructional Content Design. This study aimed to investigate the effect of design electronic curriculum and multimedia applications on acquiring e-content design…