The use of artificial intelligence and machine learning techniques across all disciplines has exploded in the past few years, with the ever-growing size of data and the changing needs of higher education, such as digital education. Similarly, online educational information systems have a huge amount of data related to students in digital education. This educational data can be used with artificial intelligence and machine learning techniques to improve digital education. This study makes two main contributions. First, the study follows a repeatable and objective process of exploring the literature. Second, the study outlines and explains the literature’s themes related to the use of AI-based algorithms in digital education. The study findings present six themes related to the use of machines in digital education. The synthesized evidence in this study suggests that machine learning and deep learning algorithms are used in several themes of digital learning. These themes include using intelligent tutors, dropout predictions, performance predictions, adaptive and predictive learning and learning styles, analytics and group-based learning, and automation. artificial neural network and support vector machine algorithms appear to be utilized among all the identified themes, followed by random forest, decision tree, naive Bayes, and logistic regression algorithms.

Web accessibility is becoming a relevant topic with an increased number of people with disabilities and the elderly using the web. Numerous legislations are being passed that require the web to be universally accessible to all people, regardless of their abilities and age. Despite this trend, university curricula still teach traditional web development without addressing accessibility as a topic. To investigate this matter closely, we studied the syllabi of web development courses at one university to evaluate whether the topic of accessibility was taught there. Additionally, we conducted a survey with nineteen students who were enrolled in a web development course, and we interviewed three lecturers from the same university. Our findings suggest that the topic of accessibility is not covered in web development courses, although both students and lecturers think that it should. This generates lack of competence in accessibility. The findings also confirm the finding of previous studies that, among web developers, there is a low familiarity with accessibility guidelines and policies. An interesting finding we uncovered was that gender affects the motivation to learn about accessibility. Females were driven by personal reasons, which we attribute to females having an increased sense of empathy. Finally, our participants were divided in their opinions whether accessibility contributes to usability.

Today, the Internet of Things (IoT) is mainly associated with vertically integrated systems that often are closed and fragmented in their applicability. To build a better IoT ecosystem, the open IoT platform has become a popular term in the recent years. However, this term is usually used in an intuitive way without clarifying the openness aspects of the platforms. The goal of this paper is to characterize the openness types of IoT platforms and investigate what makes them open. We conducted a systematic mapping study by retrieving data from 718 papers. As a result of applying the inclusion and exclusion criteria, 221 papers were selected for review. We discovered 46 IoT platforms that have been characterized as open, whereas 25 platforms are referred as open by some studies rather than the platforms themselves. We found that the most widely accepted and used open IoT platforms are NodeMCU and ThingSpeak that together hold a share of more than 70% of the declared open IoT platforms in the selected papers. The openness of an IoT platform is interpreted into different openness types. Our study results show that the most common openness type encountered in open IoT platforms is open-source, but also open standards, open APIs, open data and open layers are used in the literature. Finally, we propose a new perspective on how to define openness in the context of IoT platforms by providing several insights from the different stakeholder viewpoints.

Guided by design-based research and the notion of seamless learning, we have designed a learning activity in mathematics where mobile and web technologies support transitions between outdoor and indoor learning contexts. The students' initiatives during the self-regulated outdoor part of the activity are scaffolded by the use of mobile technologies and activity prompts which provide means and demands for on-the-spot oral and visual recordings of the groups' experiences and strategies. We argue that the high quality of mathematical content in the recordings is due to several contributing factors: the choice of appropriate technological support, the informal settings, the availability of relevant physical references, and the immediate recording based on fresh experiences. Our data suggests that the rich nature of the recordings contributes to the effective transition and communication of the outdoor experiences to the classroom's learning context where these experiences are shared and discussed with peers. Finally, we discuss design issues related to the role of the teacher, as well as the structure of the entire activity and the implications for future design iterations.

Designing MMLA systems is a complex task requiring a wide range of considerations. In this paper, we identify key considerations that are essential for designing MMLA systems. These considerations include data management, human factors, sensors and modalities, learning scenarios, privacy and ethics, interpretation and feedback, and data collection. The implications of these considerations are twofold: 1) The need for flexibility in MMLA systems to adapt to different learning contexts and scales, and 2) The need for a researcher-centered approach to designing MMLA systems. Unfortunately, the sheer number of considerations can lead to a state of "analysis paralysis," where deciding where to begin and how to proceed becomes overwhelming. This synthesis paper asks researchers to rethink the design of MMLA systems and aims to provide guidance for developers and practitioners in the field of MMLA.