Predictive student models are increasingly used in learning environments due to their ability to enhance educational outcomes and support stakeholders in making informed decisions. However, predictive models can be biased and produce unfair outcomes, leading to potential discrimination against some students and possible harmful long-term…

Previous research and experiences have indicated the potential that games have in educational settings. One of the possible uses of games in education is as game-based assessments (GBA), using game tasks to generate evidence about skills and content knowledge that can be valuable. There are different approaches in the literature to implement the…

Misinformation is a global pandemic, fueled by the sophistication of the human intellect, algorithmic systems among other factors. Enhanced by the proliferation of algorithms optimized for engagement and reactions on social media, misinformation has ignited or hampered sociopolitical participation and movements and dissuaded citizens from being…

Social scientists increasingly use video data, but large-scale analysis of its content is often constrained by scarce manual coding resources. Upscaling may be possible with the application of automated coding procedures, which are being developed in the field of computer vision. Here, we introduce computer vision to social scientists, review the…

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…

Social media have established a new way of communicating and understanding social relationships. At the same time, there are downsides, especially, their use of algorithms that have been built and developed under their umbrella and their potential to alter public opinion. This paper tries to analyse the YouTube recommendation system from the…

This conceptual study uses dynamic systems theory (DST) and phenomenology as lenses to examine data privacy implications surrounding wearable devices that incorporate stakeholder, contextual and technical factors. Wearable devices can impact people's behaviour and sense of self, and DST and phenomenology provide complementary approaches for…

In recent years, smart learning environments have become central to modern education and support students and instructors through tools based on prediction and recommendation models. These methods often use learning material metadata, such as the knowledge contained in an exercise which is usually labeled by domain experts and is costly and…

To provide intelligent learning guidance for students in e-learning systems, it is necessary to accurately predict their performance in future exams by analyzing score data in past exams. However, existing research has not addressed the uncertain and dynamic features of students' cognitive status, whereas these features are essential for improving…

Procrastination, the irrational delay of tasks, is a common occurrence in online learning. Potential negative consequences include a higher risk of drop-outs, increased stress, and reduced mood. Due to the rise of learning management systems (LMS) and learning analytics (LA), indicators of such behavior can be detected, enabling predictions of…

This paper reviews algorithmic or artificial intelligence (AI) bias in education technology, especially through the lenses of speculative fiction, speculative and liberatory design. It discusses the causes of the bias and reviews literature on various ways that algorithmic/AI bias manifests in education and in communities that are underrepresented…

In the context of a rapid digital transformation, digital competence is now regarded as a fourth cultural skill complementing reading, writing, and arithmetic. We argue that a well-structured and sound competence model is needed as a shared foundation for learning, teaching, pedagogical diagnostics and evaluative schemes in the school system.…

The aim of this study is to classify the subjects and skills of middle school mathematics course in the context of MATH Taxonomy and to determine their relations. For this purpose, the questions and answers related to the mathematics subtest of a national exam were analyzed over the answers of 20154 students. The study continued with the analysis…

Educational Robotics is increasingly used in elementary-school classrooms to develop students' algorithmic thinking and programming skills. However, most research appears descriptive and lacks experimental evidence on the effects of teaching interventions using robotics to develop algorithmic thinking. Using the robots Dash and Dot, this study…

The Jeong (2020) study found that greater use of backward and depth-first processing was associated with higher scores on students' argument maps and that analysis of only the first five nodes students placed in their maps predicted map scores. This study utilized the jMAP tool and algorithms developed in the Jeong (2020) study to determine if the…