Related papers: Computer-Supported Collaborative Learning in Softw…
In the last decade, Single-Board Computers (SBCs) have been employed more frequently in engineering and computer science both to technical and educational levels. Several factors such as the versatility, the low-cost, and the possibility to…
Context: The software development industry is rapidly adopting machine learning for transitioning modern day software systems towards highly intelligent and self-learning systems. However, the full potential of machine learning for…
Security engineering in the software lifecycle aims at protecting information and systems to guarantee confidentiality, integrity, and availability. As security engineering matures and the number of research papers grows, there is an…
Improving artificial intelligence (AI) literacy has become an important consideration for academia and industry with the widespread adoption of AI technologies. Collaborative learning (CL) approaches have proven effective for information…
In this paper, we introduce the concept of collective learning (CL) which exploits the notion of collective intelligence in the field of distributed semi-supervised learning. The proposed framework draws inspiration from the learning…
As belief around the potential of computational social science grows, fuelled by recent advances in machine learning, data scientists are ostensibly becoming the new experts in education. Scholars engaged in critical studies of education…
Given the increasing demands in computer programming education and the rapid advancement of large language models (LLMs), LLMs play a critical role in programming education. This study provides a systematic review of selected empirical…
Computer Science education has been evolving over the years to reflect applied realities. Until about a decade ago, theory of computation, algorithm design and system software dominated the curricula. Most courses were considered core and…
Curriculum learning (CL) is a training strategy that trains a machine learning model from easier data to harder data, which imitates the meaningful learning order in human curricula. As an easy-to-use plug-in, the CL strategy has…
Computer science education is a dynamic field with many aspects that influence the learner's path. While these aspects are usually studied in depth separately, it is also important to carry out broader large-scale studies that touch on many…
The article describes the advisable ways of the cloud-based systems use to support students collaboration in the process of math disciplines learning. The SageMathCloud-based component that aggregates electronic resources for several math…
Background: Philosophers of science including Collins, Feyerabend, Kuhn and Latour have all emphasized the importance of consensus within scientific communities of practice. Consensus is important for maintaining legitimacy with outsiders,…
Developing effective predictive models becomes challenging in dynamic environments that continuously produce data and constantly change. Continual Learning (CL) and Streaming Machine Learning (SML) are two research areas that tackle this…
Continual learning requires incremental compatibility with a sequence of tasks. However, the design of model architecture remains an open question: In general, learning all tasks with a shared set of parameters suffers from severe…
Education for sustainable development has evolved to include more constructive approaches and a better understanding of what is needed to align education with the cultural, societal, and pedagogical changes required to avoid the risks posed…
Randomized A/B comparisons of alternative pedagogical strategies or other course improvements could provide useful empirical evidence for instructor decision-making. However, traditional experiments do not provide a straightforward pathway…
Context: Advancements in machine learning (ML) lead to a shift from the traditional view of software development, where algorithms are hard-coded by humans, to ML systems materialized through learning from data. Therefore, we need to…
The modern engineering landscape increasingly requires a range of skills to successfully integrate complex systems. Project-based learning is used to help students build professional skills. However, it is typically applied to small teams…
One of the objectives of software engineering education is to make students to learn essential teamwork skills. This is done by having the students work in groups for course assignments. Student team composition plays a vital role in this,…
This study examines the integration of digital collaborative tools and structured peer evaluation in the Machine Learning for Health master's program, through the redesign of a Biomedical Image Processing course over two academic years. The…