This exploratory study investigates the convergence of marketing communications and AI-powered technology in higher education, adopting a perspective on student interactions with generative AI tools. Through a comprehensive content analysis of learners' responses, we employed a blend of manual scrutiny, Python-generated Word Cloud, and Latent…

Higher education systems exhibit varying degrees of heterogeneity in approaches to undergraduate degree classification -- specifically for this Point of Departure: the wide variety of 'Degree Classification Algorithms' (DCAs) used to calculate students' final awards. To date, the impact of DCA variation remains an under-researched 'black box', and…

This study aims to examine the views of fourth-grade primary school students on coding education given through the Scratch program by determining the students' skills in using the program and algorithmic thinking skills. The study was conducted as a one-group study with an embedded mixed design. The study group consisted of 32 students attending…

Nowadays, e-learning is a significant learning option, especially in light of the COVID-19 pandemic. However, it is a very challenging task because, in online courses, tutors have no direct interaction with students, which causes most of them to lose interest and ultimately drop out of their studies. In regular classes, teachers can see how each…

Algorithmic decision-making systems such as Learning Analytics (LA) are widely used in an educational setting ranging from kindergarten to university. Most research focuses on how LA is used and adopted by teachers. However, the perspective of students and parents who experience the (in)direct consequences of these systems is underexplored. This…

Intelligent Voice Assistants (IVAs) have become integral to many users' daily lives, using advanced algorithms to automate various tasks. Nevertheless, many users do not understand the underlying algorithms and how they work, posing potential risks to the competent and self-determined use of IVAs. This work develops three online training modules…

Algorithmic systems such as Learning Analytics (LA) are driving the datafication and algorithmization of education. In this research, we focus on the appropriateness of LA systems from the perspective of parents and students in secondary education. Anchored in the contextual integrity framework (Nissenbaum, "Washington Law Review, 79,"…

Negative attitudes and perceptions on programming impair the effectiveness of learning programming skills. In this study the attitude related to programming, problem solving, and self-views on importance of IT/programming knowledge were assessed by pre- and post-test completed at the beginning and at the end of a software development course. The…

Whereas 'Web 2.0 technology' has pushed the learning agenda towards connectivity and boundary crossing, in the current 'new new media ontology' the fear that algorithms might block our avenues to knowledge and connections prevails. In response to this, media scholars have argued that knowledge based on the algorithmic experiences of users is key…

Computer Science (CS) Unplugged activities are designed to engage students with CS concepts. It is an active learning approach combining physical interaction with visual representation. This research article investigates the impact of CS Unplugged on students' understanding of the bubble sort algorithm. Algorithm visualization, traditionally…

Social media platforms rely on algorithms to filter and select content, thereby personalizing every individual's social media experience. Many use social media without awareness of this personalization and its impact, pointing to a need to both understand and improve literacy among active social media users. This qualitative study addresses…

The field of Data Science has seen rapid growth over the past two decades, with a high demand for people with skills in data analytics, programming, statistics, and ability to visualize, predict from, and otherwise make sense of data. Alongside the rise of various artificial intelligence (AI) and machine learning (ML) applications, we have also…

The study focuses on the identification of relationships and/or rules between computational thinking (CT) concepts among the undergraduate students of Applied Informatics due to their attitudes towards mathematics. We analyze three CT concepts -- decomposition, pattern recognition, and algorithmic thinking. We assume that students who have a…

Computational modelling is widely used in biological science. Therefore, biology students need to learn computational modelling. However, there is a lack of evidence about how to teach computational modelling in biology and what the effects are on student learning. The purpose of this intervention-control study was to investigate how knowledge in…

Computational thinking (CT) skills of pre-service teachers have been explored extensively, but the effectiveness of CT training has yielded mixed results in previous studies. Thus, it is necessary to identify patterns in the relationships between predictors of CT and CT skills to further support CT development. This study developed an online CT…