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Brain–computer interfaces (BCIs) are a form of technology that read a user’s neural signals to perform a task, often with the aim of inferring user intention. They demonstrate potential in a wide range of clinical, commercial, and personal applications. But BCIs are not always simple to operate, and even with training some BCI users do not operate their systems as intended. Many researchers have described this phenomenon as “BCI illiteracy,” and a body of research has emerged aiming to characterize, predict, and solve this perceived problem. However, BCI illiteracy is an inadequate concept for explaining difficulty that users face in operating BCI systems. BCI illiteracy is a methodologically weak concept; furthermore, it relies on the flawed assumption that BCI users possess physiological or functional traits that prevent proficient performance during BCI use. Alternative concepts to BCI illiteracy may offer better outcomes for prospective users and may avoid the conceptual pitfalls that BCI illiteracy brings to the BCI research process.

For all the current enthusiasm for AI-based teaching and learning, the evidence base for their transformative effects on education remains thin (Holmes et al., 2022). [...]of writing, the biggest stories about AI in education concern automated natural language generating technologies. What we currently call AI is an historical accumulation of statistics, algorithm design, data storage and computing power, and new automated data science discovery methods of machine learning, neural networks and deep learning (McQuillan, 2022). AIED is not just a bundle of technologies but is the socially and historically specific result of an accumulation of technical developments, scientific practices, institutional applications, and power struggles - including struggles between supporters and their critics. Regarding the economic or market factors, education technology (edtech) is now a massive multibillion dollar global industry, powered by private venture capital investors.

In this paper, I argue that the fields of artificial intelligence (AI) and education have been deeply intertwined since the early days of AI. Specifically, I show that many of the early pioneers of AI were cognitive scientists who also made pioneering and impactful contributions to the field of education. These researchers saw AI as a tool for thinking about human learning and used their understanding of how people learn to further AI. Furthermore, I trace two distinct approaches to thinking about cognition and learning that pervade the early histories of AI and education. Despite their differences, researchers from both strands were united in their quest to simultaneously understand and improve human and machine cognition. Today, this perspective is neither prevalent in AI nor the learning sciences. I conclude with some thoughts on how the artificial intelligence in education and learning sciences communities might reinvigorate this lost perspective.

PurposeThe PICCH research project contributes to opening a dialogue between cultural heritage archives and users. Hence, the users are identified and their information needs, the search strategies they apply and the search challenges they experience are uncovered.Design/methodology/approachA combination of questionnaires and interviews is used for collection of data. Questionnaire data were collected from users of three different audiovisual archives. Semi-structured interviews were conducted with two user groups: (1) scholars searching information for research projects and (2) archivists who perform their own scholarly work and search information on behalf of others.FindingsThe questionnaire results show that the archive users mainly have an academic background. Hence, scholars and archivists constitute the target group for in-depth interviews. The interviews reveal that their information needs are multi-faceted and match the information need typology by Ingwersen. The scholars mainly apply collection-specific search strategies but have in common primarily doing keyword searching, which they typically plan in advance. The archivists do less planning owing to their knowledge of the collections. All interviewees demonstrate domain knowledge, archival intelligence and artefactual literacy in their use and mastering of the archives. The search challenges they experience can be characterised as search system complexity challenges, material challenges and metadata challenges.Originality/valueThe paper provides a rare insight into the complexity of the search situation of cultural heritage archives, and the users’ multi-facetted information needs and hence contributes to the dialogue between the archives and the users.

Immersive Virtual Reality (IVR) consists of artificial computer-generated environments allowing a user to perceive the sensation of being present and interact in an ambience that convincingly replaces the physical world. When travel is restricted, such visualization power can be shared globally as an essential remote teaching tool for educational institutions through the Internet. The current advancements in IVR technology and their ubiquitous availability at affordable costs present a conducive environment for teaching and learning in both in-person and remote settings. The research presented in this paper explores the use of IVR technologies for teaching architectural history and presents tangible student learning outcomes. Specifically, the Pantheon in Rome was used as a representative test case for evaluating the effectiveness of IVR as a medium for remote teaching. Unlike Augmented Reality (AR), where virtual information is overlaid on physical real-world objects, this research focuses on IVR implementation and its effectiveness as a history teaching medium from exploring: (1) the nature of VR, (2) how IVR can be used online for teaching history, (3) the representation of IVR for presenting history, and (4) issues of learning outcomes. Two assessments with 57 and 68 students were separately conducted and five independent variables of: (1) learning about architecture, (2) history, (3) sense of presence in VR, (4) structural realism, and (5) comparison to in-class learning were evaluated using scores. Studies revealed that the intricate architectural details combined with high-resolution imagery and audio narrations for objects of historical interest in coordination with the user’s viewpoint within the IVR environment provided an excellent learning experience. The true past and the reality of history can be implemented in IVR through seeing objects and hearing historical data. Further, the use of IVR afforded the opportunity for students to accurately gauge, recognize, and appreciate the 3D aspects, size, and proportion of virtual spaces. The preparation of the Pantheon model, the development of an interactive IVR application, the design of the studies, the measurement of learning outcomes, and technological challenges are presented in this paper. Future exploration of new technologies to improve the representation of history by execution speed, which is the determining factor impacting realism of model and viewing experience, are also explained.

In this paper we present a new method for automatic transliteration and segmentation of Unicode cuneiform glyphs using Natural Language Processing (NLP) techniques. Cuneiform is one of the earliest known writing system in the world, which documents millennia of human civilizations in the ancient Near East. Hundreds of thousands of cuneiform texts were found in the nineteenth and twentieth centuries CE, most of which are written in Akkadian. However, there are still tens of thousands of texts to be published. We use models based on machine learning algorithms such as recurrent neural networks (RNN) with an accuracy reaching up to 97% for automatically transliterating and segmenting standard Unicode cuneiform glyphs into words. Therefore, our method and results form a major step towards creating a human-machine interface for creating digitized editions. Our code, Akkademia, is made publicly available for use via a web application, a python package, and a github repository.

Digital badges provide new affordances for online educational activities and experiences. When used with points and leaderboards, a badge can become a gamification element allowing learners to compete with themselves or others, and to know how close they are to accomplishing a goal and acquiring its accompanying reputation. In this role, badges motivate continued engagement, which increases time on task and supports skill acquisition through performance. Learning outcomes signified by badges can also be displayed in an e-portfolio or on web sites and are highly transportable to social media sites. In this role they summarize achievement and signal accomplishment. With these characteristics, digital badges have the potential to become an alternative credentialing system, providing visible recognition in digital symbols that link directly via metadata to validating evidence of educational achievements in public displays. This paper will trace the brief history of digital badges, define what they are, give examples of their use, and discuss their educational affordances.

Social media has substantially changed how people confront health issues. However, a comprehensive understanding of how social media has altered the foci and methods in public health research remains lacking. This study aims to examine research themes, the role of social media, and research methods in social media-based public health research published from 2000 to 2018. A dataset of 3419 valid studies was developed by searching a list of relevant keywords in the Web of Science and PubMed databases. In addition, this study employs an unsupervised text-mining technique and topic modeling to extract research themes of the published studies. Moreover, the role of social media and research methods adopted in those studies were analyzed. This study identifies 25 research themes, covering different diseases, various population groups, physical and mental health, and other significant issues. Social media assumes two major roles in public health research: produce substantial research interest for public health research and furnish a research context for public health research. Social media provides substantial research interest for public health research when used for health intervention, human-computer interaction, as a platform of social influence, and for disease surveillance, risk assessment, or prevention. Social media acts as a research context for public health research when it is mere reference, used as a platform to recruit participants, and as a platform for data collection. While both qualitative and quantitative methods are frequently used in this emerging area, cutting edge computational methods play a marginal role. Social media enables scholars to study new phenomena and propose new research questions in public health research. Meanwhile, the methodological potential of social media in public health research needs to be further explored.

Educational technologies have captured the attention of researchers, policy makers, and parents. Each year, considerable effort and money are invested into new technologies, hoping to find the next effective learning tool. However, technology changes rapidly and little attention is paid to the changes after they occur. This paper provides an overall picture of the changing trends in educational technology by analyzing the Horizon Reports’ predictions of the most influential educational technologies from 2011 to 2021, identifying larger trends across these yearly predictions, and by using bibliometric analysis to evaluate the accuracy of the identified trends. The results suggest that mobile and analytics technologies trended consistently across the period, there was a trend towards maker technologies and games in the early part of the decade, and emerging technologies (e.g., VR, AI) are predicted to trend in the future. Overall, the specific technologies focused on by the HRs’ predictions and by educational researchers’ publications seem to coincide with the availability of consumer grade technologies, suggesting that the marketplace and technology industry is driving trends (cf., pedagogy or theory).