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The aim of the present study was to explore the relationship between testing mode (taking a test on computer versus paper) and two other factors: (1) cognitive load and (2) scratch paper use in an undergraduate general chemistry class setting. Cognitive load was measured with two self-report questions (perceived mental effort and level of difficulty) and scratch paper use was analyzed manually. All 221 students completed three assessments administered either on computer or paper. The assessments included a variety of chemistry topics with an equal number of three question types (algorithmic, conceptual, and definition). There was no significant difference in the cognitive load imposed by computer or paper-based tests at the overall test level or by question type. Students utilized scratch paper more on paper-based than online tests, especially when the questions were conceptual, and they used scratch paper the most for algorithmic questions. Altogether, these results provide further support that online testing can be implemented in educational settings without imposing additional cognitive load on students. [ABSTRACT FROM AUTHOR]

Abstract Exposing learners to cognitive computing concepts involves new learning strategies. Because cognitive computing is probabilistic, using massive sets of data is fundamental in understanding these concepts. One data set is the release of the Offshore Panama Papers Leaks Database (LeaksDB) in May 2016, in which researchers were able to access this graph database as part of the International Consortium of Investigative Journalists (ICIJ) Offshore Leaks investigation and to draw conclusions about companies, trusts, foundations, and funds incorporated in 21 tax havens. For the purpose of this research, GraphDB Server was installed and configured by faculty members from a mid-western university. In addition, DBPedia and GeoNames repositories were linked to LeaksDB, leading to the discovery of interesting patterns about these Geo facade relationships between Officers (persons or companies) and Countries. Highlights • Using massive data sets is fundamental to teaching cognitive computing concepts. • Repositories linked to Panama Papers LeaksDB uncovered patterns of relationships. • Top 20 countries are related to 80% of entities listed in the LeaksDB database. [ABSTRACT FROM AUTHOR]

The present study examined two common mechanisms that are used to explain why reading on an electronic screen versus paper result in different reading outcomes: The Cognitive Map Mechanism and the Medium Materiality Mechanism. A laboratory experiment (N = 45), was conducted using a three-group comparison design (paper book vs. digital equivalent vs. digital disrupted view). Our hypotheses that were based on the cognitive map mechanism were largely supported. On the other hand, our hypotheses following the medium materiality mechanism were not sufficiently evidenced. Specifically, our results showed that the paper book was similar to its digital equivalent, and both were better than the digital disrupted view in terms of reading comprehension, feelings of fatigue, and psychological immersion. The findings implied that it is not the materiality of the presentation medium that influences reading outcomes, rather it is the extent to which the text presentation facilitates, or impedes, the reader's ability to construct a cognitive map that influences the reading process. Implications for future research and practice are discussed. [ABSTRACT FROM AUTHOR]

Abstract In this paper we explore the interrelationship between the sociotechnical-pedagogical culture of e-learning, the emerging disciplines of Web science, Social Sensing and that of Cognitive Computation–as an emerging paradigm of computation. We comment in particular on the importance of this relation for the development of learning-analytics discourse. Moreover, we present an initial relational framework between these disciplines and suggest how these relations can be exploited to solve problems in each area. This paper argues for (a) the particular importance of the abstract class of 'learning machines' for Web science, (b) understanding cognitive computation as a necessary practical framework for the increasingly dominating, situated informal learning context, and (c) the potential benefit of Web science frameworks for investigating both, contemporary research questions in e-learning and the development of theories for informal ubiquitous learning. Finally, we argue that exploring links between these disciplines is necessary for improving practical research, for the purpose of developing learning-analytics methodology for evaluating the growing types of modern e-learning contexts such as the informal situated learning context. Highlights • Web Science, Cognitive Computing, E-learning and Social Sensing are connected. • Informal situated-learning is becoming the most prevalent form of e-learning. • Situated learning argued to be significant form of social machine (from Web Science). • Progress in learning-analytics depends on exploiting relations with these disciplines. [ABSTRACT FROM AUTHOR]

Web personalization has been widely adopted in the mobile shopping context to improve shopping experience and consumer loyalty. Timing is a crucial issue of the implementation of web personalization, a topic not yet adequately investigated in the extant literature. Web personalization could classify into two forms, namely Before-search Web Personalization (BSWP) and After-search Web Personalization (ASWP), in the mobile shopping context. Besides, motivations are the critical factors in mobile shopping, and seldom research has studied the effects of motivation on consumer's use of web personalization in the mobile shopping context. To advance understanding of the timing issue of web personalization, this paper employs the Uses and Gratifications method to investigate how mobile shopping motivations influence consumers' use of BSWP and ASWP, respectively. Furthermore, this paper also investigates the role of an important personal disposition (i.e. need for cognition). Empirical results indicate that shopping motivations could have significant effects on web personalization use; furthermore, BSWP use and ASWP use are predicted by different shopping motivations. Besides, need for cognition is found to positively moderate some effects of mobile shopping motivations on web personalization use. Theoretical and practical implications are also discussed. [ABSTRACT FROM AUTHOR]

Modeling reading comprehension processes is a critical task for Learning Analytics, as accurate models of the reading process can be used to match students to texts, identify appropriate interventions, and predict learning outcomes. This paper introduces an improved version of the Automated Model of Comprehension, namely version 4.0. AMoC has its roots in two theoretical models of the comprehension process (i.e., the Construction-Integration model and the Landscape model), and the new version leverages state-of-the-art Large Language models, more specifically ChatGPT, to have a better contextualization of the text and a simplified construction of the underlying graph model. Besides showcasing the usage of the model, the study introduces three in-depth psychological validations that argue for the model's adequacy in modeling reading comprehension. In these studies, we demonstrated that AMoC is in line with the theoretical background proposed by the Construction-Integration and Landscape models, and it is better at replicating results from previous human psychological experiments than its predecessor. Thus, AMoC v4.0 can be further used as an educational tool to, for example, help teachers design better learning materials personalized for student profiles. Additionally, we release the code from AMoC v4.0 as open source in a Google Collab Notebook and a GitHub repository. • Introduce the Automated Model of Comprehension version 4.0 that integrates state-of-the-art Large Language models - ChatGPT. • Perform 3 in-depth psychological validation studies to support the model's adequacy in modeling reading comprehension. • AMoC v4.0 aligns with theoretical frameworks, namely Construction-Integration and Landscape models. • The model outperforms its predecessor and replicates results from human psychological experiments. • AMoC v4.0 can serve as an educational tool for designing personalized learning materials. [ABSTRACT FROM AUTHOR]

Every day we trust other individuals as we engage in social interactions in which various desirable outcomes depend on others acting the way we hope, or they have indicated. Trust extends beyond specific individuals, however, as we might trust unknown others – individuals, institutions, corporations, and governments. Some also say that we trust various artifacts, such as machines. But what is the basis of trust, and can we really trust technology? Trust is intimately connected to the notion ethos from the study of rhetoric and human persuasion, which is often used to describe various characteristics of the speaker, the audience, the relationship between the speaker and the audience, and the wider context in which communication and interaction occurs. In this article I explore to what degree machines can be considered to have ethos, and consequently whether ethos is a useful concept for understanding persuasive and credibility-related situations in HMI and by extension key aspects of human-machine trust. This allows us to draw on a long lineage of research from, for example, rhetoric, communication studies, and cognitive and social psychology to better understand the usefulness – or not – of using the notion of trust to describe our relationship with machines. • Trust in machines partly parallels trust in humans, institutions, and artifacts. • Ethos, from rhetoric, relates to credibility and trust in human-machine interaction. • This paper explores if machines can have ethos, and how this relates to trust. • Machine ethos is about perceived credibility and not the machine's ethics. • Examining ethos enriches understanding of trust and design in HMI. [ABSTRACT FROM AUTHOR]

This paper investigates the interplay among human cognitive processing differences (field dependence vs . field independence), alternative interaction device types (desktop vs . touch) and user authentication schemes (textual vs . graphical) towards task completion efficiency and effectiveness. A four-month user study ( N = 164) was performed under the light of the field dependence-independence theory which underpins human cognitive differences in visual perceptiveness as well as differences in handling contextual information in a holistic or analytic manner. Quantitative and qualitative analysis of results revealed that field independent (FI) users outperformed field dependent users (FD) in graphical authentication, FIs authenticated similarly well on desktop computers as on touch devices, while touch devices negatively affected textual password entry performance of FDs. Users' feedback from a post-study survey further showed that FD users had memorability issues with graphical authentication and perceived the added difficulty when interacting with textual passwords on touch devices, in contrast to FI users that did not have significant usability and memorability issues on both authentication and interaction device types. Findings highlight the necessity to improve current approaches of knowledge-based user authentication research by incorporating human cognitive factors in both design and run-time. Such an approach is also proposed in this paper. [ABSTRACT FROM AUTHOR]

Learning sciences are embracing the significant role technologies can play to better detect, diagnose, and act upon self-regulated learning (SRL). The field of SRL is challenged with the measurement of SRL processes to advance our understanding of how multimodal data can unobtrusively capture learners' cognitive, metacognitive, affective, and motivational states over time, tasks, domains, and contexts. This paper introduces a self-regulated learning processes, multimodal data, and analysis (SMA) grid and maps joint and individual research of the authors (63 papers) over the last five years onto the grid. This shows how multimodal data streams were used to investigate SRL processes. The two-dimensional space on the SMA grid is helpful for visualizing the relations and possible combinations between the data streams and how the measurement of SRL processes. This overview serves as an analytical introduction to the current special issue "Advancing SRL Research with Artificial Intelligence (AI)" and we encourage to position new research and unexplored frontiers. We emphasize the need for intensive and strategic collaboration to accelerate progress using new interdisciplinary methods to develop accurate measurement of SRL in educational technologies. • Self-regulated learning (SRL) field started using one data stream to analyse a certain SRL process with simple statistics. • We diversified our research towards the horizontal approach analysing multiple SRL processes with one data stream using more advanced statistical techniques. • As well as to the vertical approach, investigating one SRL process using multiple data streams. • Novel is an integrated approach aligning multimodal data investigating multiple SRL processes with advanced AI techniques. [ABSTRACT FROM AUTHOR]

Technological development has influenced the ways in which learning and reading takes place, and a variety of technological tools now supplement and partly replace paper books. Previous studies have suggested that digital study media impair metacognitive monitoring and regulation (Ackerman & Goldsmith, 2011; Ackerman & Lauterman, 2012; Lauterman & Ackerman 2014 ). The aim of the current study was to explore the relationship between metacognitive experiences and learning for digital versus non-digital texts in a test situation where metacognitive experiences were assessed more broadly compared to previous studies, and where a larger number of potentially confounding factors were controlled for. Experiment 1 ( N = 100) addressed the extent to which metacognitive monitoring accuracy for 4 factual texts was influenced by whether texts were presented on a paper sheet, a PC, an iPad, or a Kindle. Metacognitive experiences were measured by Predictions of Performance (PoP), Judgements of Learning (JoL), and Confidence Ratings (CR), and learning outcome was measured by recognition performance. Experiment 2 ( N = 50) applied the same basic procedure, comparing a paper condition with a PC condition with the opportunity to take notes and highlight text. In both experiments, study media had no consistent effect on metacognitive calibration or resolution. The results give little support to previous claims that digital learning impairs metacognitive regulation. [ABSTRACT FROM AUTHOR]

Making is a playful exploration of tools and materials to design personally meaningful artifacts, providing a particularly impactful entry point for traditionally underrepresented youth in science, technology, engineering, and mathematics (STEM) fields. However, it remains unclear how these constructionist explorations translate to eventual professional and educational STEM opportunities, especially for women. This paper tracks an exemplary case in a makerspace to theorize, describe, and analyze the behavioral patterns of young women as they engage in making and move toward expertise in STEM. Building on a material-based and constructionist notion of making, we use mediated discourse analysis to examine how recognition (materialized in artifacts as displaying, legitimizing, and circulating emergent STEM expertise) leads to transformational development over time. We introduce the notion of tinkering with development , which conceptualizes playful project design, spatial project placements, and emergent online project sharing as drivers of human developmental trajectories. Implications of this work include a set of design principles to support makerspaces and other constructionist learning environments to foster participation in STEM. Further, implications for constructionist theory and STEM gender representation are discussed. Image 1 • Recognition plays a vital role in STEM learning and pathway development. • Honoring women's STEM expertise can counteract their turning away from STEM. • Constructionism has underspecified how sharing can cultivate recognition. • Displaying, legitimizing, and circulating expertise can foster recognition. • Personally meaningful artifacts produce and display growing expertise. [ABSTRACT FROM AUTHOR]

Over the last few years, the integration of coding activities for children in K-12 education has flourished. In addition, novel technological tools and programming environments have offered new opportunities and increased the need to design effective learning experiences. This paper presents a design-based research (DBR) approach conducted over two years, based on constructionism-based coding experiences for children, following the four stages of DBR. Three iterations (cycles) were designed and examined in total, with participants aged 8–17 years old, using mixed methods. Over the two years, we conducted workshops in which students used a block-based programming environment (i.e., Scratch) and collaboratively created a socially meaningful artifact (i.e., a game). The study identifies nine design principles that can help us to achieve higher engagement during the coding activity. Moreover, positive attitudes and high motivation were found to result in the better management of cognitive load. Our contribution lies in the theoretical grounding of the results in constructionism and the emerging design principles. In this way, we provide both theoretical and practical evidence of the value of constructionism-based coding activities. • Design-based research approach to investigate constructionism-based coding activities for children. • Identify elements of children's engagement in constructionism-based coding activities. • Theoretical grounding of the findings on constructionism theory. • Instructional design principles to facilitate constructionism-based coding activities for children. [ABSTRACT FROM AUTHOR]

It is known that well-designed immersive Virtual Reality (VR) environments can positively impact on user experiences, with results evidencing that a considered approach to hue design can trigger positive cognitive performance and intellectual abilities. However, limited research has been conducted to study the design potential of chroma and brightness colour attributes of immersive VR environments. This study investigates the impacts of colour attributes on cognitive performance and intellectual abilities in immersive Virtual Reality (VR) Environments. The paper included the results of two psychological experiments that evaluate people's cognitive performance to different chroma and brightness, respectively. The experiments further studied effects of colour attributes on participants' logical and lateral thinking abilities, as well as their attention to details. Participants' response time and error rate when completing each psychometric test were recorded with different hue, chroma, and brightness backgrounds in immersive virtual environments. The data collected from participants reveal the differential impacts of colour attributes on people's cognitive performance and intellectual abilities in immersive VR environments. The findings of our study provide new insights to metaverse areas of research suggests that effective use of colour design in the immersive digital context can positively trigger people's cognitive performance and intellectual abilities at an unconscious level. • Colours in different levels of chroma and brightness can significantly influence people's arousal and impulsiveness in immersive VR environments. • A considered approach to immersive colour design can have a positive impact on cognitive performance in immersive VR environments. • New insights to metaverse areas of research suggests that effective use of colour design in the immersive digital context can positively trigger people's cognitive performance and intellectual abilities at an unconscious level. [ABSTRACT FROM AUTHOR]

User engagement has become a much-cited construct in human-computer interaction (HCI) design and evaluation research and practice. Constructed as a positive and desirable outcome of users' interactions, more frequent and longer interactions are considered evidence of engagement. Disengagement, when discussed, is considered a best avoided outcome of technology use or a solution to problematic technology use. In the case of the former, disengagement may signal usability issues or user disinterest, while the latter emphasizes that some engaging interactions can result in negative consequences (e.g., addiction) for end-users. In this paper, we draw upon examples from HCI research and digital tools to present a more nuanced understanding of the symbiotic relationship between engagement and disengagement in order to propose a new definition and novel ways to model disengagement. Further, we challenge generalizations that dichotomize engagement (positive, continuous, accompanied by high interactivity and beneficial to end-users) and disengagement (negative, stopping use or detrimental use) and invite readers to interpret engagement in the context of desirability with respect to users' goals and perceived agency. We concluded with implications that invite the reader to make space for disengagement and move beyond usage data in the evaluation of engagement. This paper is a call to step away from the practice of engagement-for-engagement's sake, and to reflect on whether and when engagement is meaningful and desirable for end users. • User engagement is a desired outcome in human-computer interaction (HCI) research. • Less attention is paid to disengagement, though it is often perceived negatively. • We challenge prevalent fallacies of (dis)engagement in HCI design and evaluation. • We propose a definition of disengagement that takes into account user agency. • We model disengagement as a necessary part of the engagement cycle. [ABSTRACT FROM AUTHOR]

Highlights: [•] The paper defines cognitive democracies as democracies that are based on the cognitive processes of human beings. [•] This is addressed by the democratisation of knowledge (arguments that justify positions). [•] The paper describes a further step in the extraction of policy-making arguments. [•] A new e-learning tool for extraction of knowledge from a discussion forum is also presented. [•] Using opinion analysis techniques, the tool identifies the arguments that support opinions. [Copyright &y& Elsevier]

Abstract: In this paper, we explore how visual representations of information in 3D virtual environments (3DVEs) supports both individual and shared understanding, and consequently contribute to group decision making in tasks with a strong visual component. We integrate insights from cognitive fit theory and cognitive load theory in order to formulate hypotheses about how 3DVEs can contribute to individual understanding, shared understanding, and group decision making. We discuss the results of an experiment in which 192 participants, in 3-person teams, were asked to select an apartment. As proposed by cognitive fit theory, our results indicate that 3DVEs are indeed more effective in supporting individual understanding than 2D information presentations. Next, in line with cognitive load theory, the static presentation of 3D information turns out to be more effective in supporting shared understanding and group decision making than an immersive 3DVE. Our results suggest that although the 3DVE capabilities of realism, immersion and interactivity contribute to individual understanding, these capabilities combined with the interaction and negotiation processes required for reaching a shared understanding (and group decision), increases cognitive load and makes group processes inefficient. The implications of this paper for research and practice are discussed. [Copyright &y& Elsevier]

Abstract: The Cognitive Mediation Networks Theory (CMNT) is a novel approach to human intelligence that, among other things, attempts to understand the cognitive changes associated to the emergence and dissemination of information and communication technologies throughout the last few decades. The present paper aims to investigate a central claim of the model, which is that the greater interaction of individuals with the changes emanating from the Digital Revolution and its implications (Hyperculture) tends to, in and of itself, produce psychological changes that lead to enhanced Cognitive Performance. For that purpose, a total of 1291 Brazilian adults and adolescents were investigated by means of an especially prepared form and cognitive tests. The results obtained indicated that a greater degree of Hyperculture is positively associated to Cognitive Performance and Sociability, regardless of sex, age, income, and level of education. These findings, taken together with those from other studies, strongly support the predictions of the CMNT, which emerges in this paper as a valid model of human cognition, at least when applied to the impacts of the Digital Revolution. [Copyright &y& Elsevier]

Video-based self-reflection and annotation is receiving increasing attention within the education literature. The importance of such technologies in education relate, in part, to the interactive nature and functionality these tools bring to aid learning engagement. In particular, these tools are well aligned with the need to promote and develop student meta-cognitive skills through the use of self-reflection activities. However, in the context of video-based learning environments, the nature of a students' self-reflective process is not well understood. We attempt to address this gap in the literature in two main ways. First, we developed a coding instrument to assess the depth of a students' self-reflection captured through the use of a video annotation tool. We then explored the linguistic and discourse properties of the student self-reflections using Coh-Metrix, a theoretically grounded computational linguistics facility. The adopted approach applies comprehensive analysis of language and discourse features associated with the specificity of students' internal self-feedback , which is externalized as self-reflections in video annotations. The results suggest that levels of self-reflection have characteristically different linguistic properties, and these differences align with the underlying cognitive mechanisms associated with distinct reflective activities. The paper provides a detailed discussion of the findings in the context of the theoretical, methodological, and practical implications associated with video-based self-reflection and video annotation. • Self-reflection and annotation are important strategies in video-based learning. • We develop a coding instrument to assess the depth of a students' self-reflection. • We explore the linguistic and discourse properties of the student self-reflections. • The levels of self-reflection have consistently different linguistic properties. • The findings also highlight the importance of effective learning design. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we propose a novel approach to the analysis of collaborative learning. The approach posits that different dimensions of collaborative learning emerging from social ties and content analysis of discourse can be modeled as networks. As such, the combination of social network analysis (SNA) and epistemic network analysis (ENA) analysis can detect information about a learner's enactment of what the literature on collaborative learning has described as a role: an ensemble of cognitive and social dimensions that is marked by interacting with the appropriate people about appropriate content. The proposed approach is named social epistemic network signature (SENS) and is defined as a combination of these two complementary network analytic techniques. The proposed SENS approach is examined on data produced in collaborative activities performed in a massive open online course (MOOC) delivered via a major MOOC platform. The results of a study conducted on a data set collected in a MOOC suggest SNA and ENA produce complementary results which can i) explain collaboration processes that shaped the creation of social ties and that were associated with different network roles; ii) describe differences between low and high performing groups of learners; and iii) show how combined properties derived from SNA and ENA predict academic performance. Highlights • A network analytics approach for collaborative learning is proposed. • The approach combines social network analysis and epistemic network analysis. • The approach is validated with a dataset from a massive open online course. • Prediction of the structure of social ties and network roles with discourse is shown. • Prediction of performance (groups) with discourse is demonstrated. [ABSTRACT FROM AUTHOR]

Abstract The paper deals with assessment of the influence of adaptive e-learning as a part of learning analytics on learning effectiveness of primary school pupils. E-learning exercises containing implemented adaptive elements were created in accordance with the Bloom's Taxonomy. Within the pilot study the authors detected high percentage success rate during e-learning exercise completion. This leads to formulation of the question „Can any e-learning exercise of lower cognitive levels of Bloom's taxonomy be skipped without affecting the cognitive thinking for solution of the e-learning exercises on upper cognitive levels of Bloom's taxonomy?" To answer the question, the algorithm of adaptive e-learning was defined and hypotheses were established. The research was carried out as pedagogical experiment comparing the results of both experimental and control groups of pupils. The research hypotheses were confirmed by statistical analysis of the research data. The results confirm that adaptive features of e-learning can be implemented in the primary education. The research results confirm the fact that educational objectives can be achieved with some pupils more effectively. Consequently, the implementation of adaptive elements into e-learning at the primary school supports an individual approach when completing e-learning exercises according to the principle of cognitive computing. Highlights • Adaptive e-learning (AE) application in primary school education were studied. • Algorithm for primary AE based on concept of learning analytics was proposed. • Adaptive algorithm of primary AE meets the typical features of cognitive computing. • Learning effectiveness (LE) was clearly and exactly defined. • It was confirmed that the LE of primary e-learning increases by utilization of AE. [ABSTRACT FROM AUTHOR]

Abstract The advanced learning analytics research of the last years converges with the industry demand to enhance famous learning management systems with learning analytics capabilities promoting the efficiency of higher education. The exploitation of big volume learning data, is a critical challenge for the design of personalized curricula and learning experiences. The purpose of this research paper is to communicate a framework for Learning Analytics aiming to support the integrated management of end-to-end learning data. We present the research foundations of a research prototype for the integration of a Learning Analytics Dashboard: The AMBA Prototype with famous Learning Management Systems. Finally, we present the main findings of an empirical study that proves the capacity of learning analytics to enhance the learners' ecosystem with value adding learning services. The proposed framework exploits cognitive computing for the enhancement of decision making in education by proving the capacity of Learning Analytics to reveal hidden patterns of learners' behaviour and attitude. Highlights • New "Course-adapted student learning analytics framework" is proposed. • Proposed framework is partially implemented in the form of AMBA tool. • Impact of AMBA tool is extensively evaluated for student's engagement. [ABSTRACT FROM AUTHOR]

Abstract Moving towards the next generation of personalized learning environments requires intelligent approaches powered by analytics for advanced learning contexts with enriched digital content. Micro-Learning through Massive Open Online Courses is riding the wave of popularity as a novel paradigm for delivering short educational videos in small pre-organized chunks over time, so that learners can get knowledge in a manageable way. However, with the ever-increasing number of videos, it has become challenging to arrange and search them according to specific categories. In this paper, we get around the problem by bridging Learning Analytics and Cognitive Computing to analyze the content of large video collections, going over traditional term-based methods. We propose an efficient and effective approach to automatically classify a collection of educational videos on pre-existing categories which uses (i) a Speech-to-Text tool to get video transcripts, (ii) Natural Language Processing and Cognitive Computing methods to extract semantic concepts and keywords from video transcripts for their representation, and (iii) Apache Spark as Big Data technology for scalability. Several classifiers are trained on the feature vectors extracted by Cognitive Computing tools. Then, we compared our approach with other combinations of state-of-the-art feature types and classifiers over a large-scale dataset we collected from Coursera. Considering the experimental results, we expect our approach can facilitate the development of Learning Analytics tools powered by Cognitive Computing to support content managers on micro-learning video management while improving how learners search videos. Highlights • An efficient and effective approach to classify micro-learning videos is proposed. • Cognitive Computing is leveraged to extract features from micro-learning videos. • Using concepts and keywords as features improves overall classification performance. [ABSTRACT FROM AUTHOR]

Abstract Engagement with social networking sites is influenced by the cognitive and learning processes which in turn is influenced by culture. This paper aims at unbundling the effect of culture on the use of social network sites and thus contributes to our understanding on the way cognitive and learning processes influence the engagement with social networks. The study of over 600 social networking users addresses how professional and leisure use of social networks differs across cultures, gender and other demographics. Firstly, by utilising ANOVA techniques we associate users' behaviour with nationality and furthermore through the use of an ordered logistics regression we delineate clusters of users by the purpose of social networking adoption and their cultural characteristics. Our study helps bridge the gap in literature on identifying how cultural traits, nationality and gender affect both business and leisure use of social networking. The implications of differences in user behaviour driven by nationality and gender warrant further need for applying learning analytics in social platforms to enhance user experience. Future directions of research on social networking in relation to cognition and culture are offered for discussion. Highlights • We unbundle the cognitive and learning processes that influence engagement with SNS. • We investigate how cultural traits, nationality and gender affect the use of SNS. • Utilising ANOVA techniques we associate individual behaviour based on a study of over 600 users. • Application of learning analytics in social platforms is needed to enhance experience. • Future directions of research in relation to cognition and culture are offered for discussion. [ABSTRACT FROM AUTHOR]

Abstract Science, Technology, Engineering and Mathematics (STEM) education is recognized as a top school education priority worldwide and Inquiry-based teaching and learning is identified as a promising approach. To effectively engage students in Inquiry tasks, appropriate guidance should be provided, usually by combining digital tools such online labs and modeling tools. This is a cumbersome task for teachers, since it involves manually assessing the type/level of tool-supported guidance to be provided and potentially refining these to meet guidance needs of individual students. In our research we target to investigate how to support this systematic reflection process with educational data analytics methods and tools from both the design and the delivery of Inquiry-based educational designs (IED). The contribution of this paper is to propose a novel "Teaching and Learning" Analytics method and research prototype tool, extending the scope of purely learning analytics methods, to analyze IED in terms of the tool-supported guidance they offer and relate these analyses to students' educational data that are already being collected by existing learning analytics systems, increasing teachers' awareness. A two-layer evaluation methodology positively assessed the capacity of our method to analyze IED and provided initial evidence that the insights generated offer statistically significant indicators that impact students' activity during the delivery of these IED. The insights of this work aim to contribute in the field of cognitive data analytics for teaching and learning, by investigating new ways to combine analyses of the educational design and students' activity, and inform teachers' reflection from a holistic perspective. Highlights • Tool-supported Guidance is essential for effective Inquiry-based education. • Teaching and Learning Analytics (TLA) can support teachers provide appropriate Guidance. • The TLA method and supporting tool provides analyses of the level of Guidance in Inquiry-based scenarios. • Analyses of the design can be investigated against customizable learners' data and profiles. • Insights from these combined analyses could help teachers improve their teaching designs. [ABSTRACT FROM AUTHOR]

Abstract In contemporary education, students often need to use the Internet to find information for solving a problem and completing a learning task. Teachers assume that students are sufficiently skilled to do so, but research shows the skills necessary for effective information problem solving (IPS) are more often than not underdeveloped. This paper presents a study on embedded IPS training consisting of whole IPS tasks integrated in a 20-week course on vocabulary development, and its effects on student teachers' IPS skills. Skill measurements show that student teachers receiving the training search and select information more systematically in the short term, but their search queries, sources, and solutions are not of significantly higher quality than those of student teachers who received the regular course without IPS training. In addition, the improvements were no longer visible after five weeks. The training therefore succeeded in developing cognitive strategies for approaching an information problem, but did not create lasting improvements in all aspects of the IPS skill. Methodological and practical implications are discussed. Highlights • Students received an embedded, whole-task information problem solving training. • Trained students improved their approach to searching and selecting information. • No improvements were found on quality of queries, selected sources and solutions. • Improvements were no longer visible on a test five weeks after training stopped. [ABSTRACT FROM AUTHOR]

Mobile phones have become an integral part of life, drawing researchers' attention to their behavioral consequences. Yet, we know little about the psychological associations of mobile phones. It has been proposed that due to their role in maintaining social relationships, the mobile phone, as an object, has become the representation of a person's social network. This paper empirically investigates this idea. A sample of 154 university students participated in an experiment that tested the cognitive consequences of activating the concept of a mobile phone. We primed the concept of a mobile phone and measured the accessibility of thoughts related to social relationships with a word fragment completion task. People reminded of their mobile phones (vs. neutral personal objects) found significantly more words related to social networks, demonstrating the association between social relationships and the idea of mobile phones. Additionally, priming people with their mobile phones was associated with lower need to belong. [ABSTRACT FROM AUTHOR]

Organizations are increasingly flooded with large amounts of data on which they base their business decisions. It is thus crucial to visualize relevant data efficiently so that employees are able to extract relevant information most accurately and quickly. However, at present, information visualization research lacks a coherent and evidence based theoretical framework providing clear guidelines on how to design efficient visualizations. When it comes to the use of redundant elements in charts like commonly used data labels, cognitive fit theory and cognitive load theory make different predictions. Whereas the latter assumes that redundant labels generally reduce visualizations’ efficiency due to increased cognitive load, cognitive fit theory predicts increased efficiency for some task types that shall be solved by means of the visualization. In the online experiment presented in this paper, we investigated the effect of data labels in line and bar charts on users’ accuracy and speed in solving chart-related business tasks dependent on different task types. Our results reveal that users perceive charts with redundant labels as significantly more efficient and answer related questions significantly more accurate and faster, which we explain by the help of cognitive fit theory. We provide valuable insights into cognitive processing of charts and encourage graph designers to consider redundant elements as a possible means to increase efficiency under particular circumstances. [ABSTRACT FROM AUTHOR]

Abstract: Different learners have different needs; they differ, for example, in their learning goals, their prior knowledge, their learning styles, and their cognitive abilities. Adaptive web-based educational systems aim to cater individual learners by customizing courses to suit their needs. In this paper, we investigate the benefits of incorporating learning styles and cognitive traits in web-based educational systems. Adaptivity aspects based on cognitive traits and learning styles enrich each other, enabling systems to provide learners with courses which fit their needs more accurately. Furthermore, consideration of learning styles and cognitive traits can contribute to more accurate student modelling. In this paper, the relationship between learning styles, in particular the Felder–Silverman learning style model (FSLSM), and working memory capacity, a cognitive trait, is investigated. For adaptive educational systems that consider either only learning styles or only cognitive traits, the additional information can be used to provide more holistic adaptivity. For systems that already incorporate both learning styles and cognitive traits, the relationship can be used to improve the detection process of both by including the additional information of learning style into the detection process of cognitive traits and vice versa. This leads to a more reliable student model. [Copyright &y& Elsevier]

The field of learning design has extensively studied the use of technology for the authoring of learning activities. However, the social dimension of the learning design process is still underexplored. In this paper, we investigate communities of teachers who used a social learning design platform (ILDE). We seek to understand how community awareness facilitates the learning design activity of teachers in different educational contexts. Following a design-based research methodology, we developed a community awareness dashboard (inILDE) based on the Cultural Historical Activity Theory (CHAT) framework. The dashboard displays the activity of teachers in ILDE, such as their interactions with learning designs, other members, and with supporting learning design tools. Evaluations of the inILDE dashboard were carried out in four educational communities – two secondary schools, a master programme for pre-service teachers, and in a Massive Open Online Course (MOOC) for teachers. The dashboard was perceived to be useful in summarizing the activity of the community and in identifying content and members' roles. Further, the use of the dashboard increased participants' interactions such as profile views and teachers showed a willingness to build on the contributions of others. As conclusions of the study, we propose five design principles for supporting awareness in learning design communities, namely community context, practice-related insights, visualizations and representations, tasks and community interests. [ABSTRACT FROM AUTHOR]

The development of neural implants to increase people's memory is enabling the creation of cyborgs (human-machine hybrids) with superior capacities. This paper aims to advance new technology acceptance models by analyzing the moderating effect of ethics on an integrative Cognitive-Affective-Normative (CAN) model to understand the acceptance of brain implants to increase capacities. The model is tested on a sample of 900 individuals segmented by their ethical assessment of these insideables: ethically in favor, ethically against, or ethically indifferent. The results show that an individual's ethical assessment of memory implants explains differences in his or her intention to use them but does not moderate the influence of performance expectancy, effort expectancy, positive emotions, negative emotions, or social influence on the intention to use them. The results have theoretical implications for technology acceptance models and open new lines of research concerning the future cyborg society. [ABSTRACT FROM AUTHOR]

Decision justification provides assurance and reduces negative post-decision emotions, while simultaneously expends decision costs (i.e., cognitive effort). The current paper investigated the function of justification and cognitive effort related to regret, specifically in the online shopping context in two studies. In Study 1, 112 participants reviewed vignettes in a 2 × 2 within-subjects design involving cognitive effort (high versus low) and justification of action (easy versus difficulty), and reported the regret level when their purchase decision yielded subpar consequences. As expected, high cognitive effort and easy justification reduced regret. However, the effect of justification on regret was moderated by cognitive effort. In Study 2, 178 participants were randomly assigned to conditions in a 2 × 2 between-subjects design involving cognitive effort (high versus low) and decision justification (waste versus control). Participants followed a cover story and shopped for a laptop online; then they rated the regret level had they made an unplanned purchase. Results confirmed the hypothesis; regret was greater when justification was wasted. However, wasted justification only worsened regret when more cognitive effort was exerted. The current studies shed light on understanding an intricate dynamic between information processing and justification in relation to regret when shopping online. [ABSTRACT FROM AUTHOR]

Computational thinking (CT) is being consolidated as a key set of problem-solving skills that must be developed by the students to excel in our software-driven society. However, in psychological terms, CT is still a poorly defined construct, given that its nomological network has not been established yet. In a previous paper, we started to address this issue studying the correlations between CT and some fundamental cognitive variables, such as primary mental abilities and problem-solving ability. The current work deepens in the same direction as it aims to extend the nomological network of CT with non-cognitive factors, through the study of the correlations between CT, self-efficacy and the several dimensions from the ‘Big Five’ model of human personality: Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. To do so, the Computational Thinking Test (CTt) and some additional self-efficacy items are administered on a sample of 1251 Spanish students from 5th to 10th grade ( N = 1251), and the Big Five Questionnaire-Children version (BFQ-C) is also taken by a subsample from the above ( n = 99). Results show statistically significant correlations between CT and self-efficacy perception relative to CT performance ( r s = 0.41), in which gender differences in favor of males are found ( d = 0.42). Moreover, results show statistically significant correlations between CT and: Openness to Experience ( r = 0.41), Extraversion ( r = 0.30), and Conscientiousness ( r = 0.27). These findings are consistent with the existing literature except for the unexpected correlation between CT and the Extraversion factor of personality, which is consequently discussed in detail. Overall, our findings corroborate the existence of a non-cognitive side of CT that should be taken into account by educational policies and interventions aimed at fostering CT. As a final contribution, the extended nomological network of CT integrating cognitive and non-cognitive variables is depicted. [ABSTRACT FROM AUTHOR]

This paper identifies and examines the factors that make Snapchat a unique social medium. Snapchat departs from mainstream media forms in that they are fundamentally visual and occur real-time, thus demonstrating a stronger sense of “being present” in multiple spaces at the same time. Specifically, we argue that what adds to the appeal of Snapchat is a focus on Social Presence as well as on Theory of Mind, a construct that could potentially play a key role in the degree of Social Presence generated by a medium. A sample of 656 Snapchat users, aged from 18 to 29, showed significant links between measures of various precursors and components of Theory of Mind with dimensions of Social Presence, Snapchat Intensity, and frequency of Snapchat usage patterns. Further, the results of a mediation analysis suggest that increasing elements of Social Presence underlie the relationship between mechanisms of Theory of Mind and the intensity of a social media (Snapchat) in users’ daily life. Taken in context of different social media platform uses, the results highlight how a platform that emphasizes such visual and real-time features over other features can fulfill a desired gap in established social media platforms and their practices. [ABSTRACT FROM AUTHOR]

Computational thinking (CT) is being located at the focus of educational innovation, as a set of problem-solving skills that must be acquired by the new generations of students to thrive in a digital world full of objects driven by software. However, there is still no consensus on a CT definition or how to measure it. In response, we attempt to address both issues from a psychometric approach. On the one hand, a Computational Thinking Test (CTt) is administered on a sample of 1,251 Spanish students from 5th to 10th grade, so its descriptive statistics and reliability are reported in this paper. On the second hand, the criterion validity of the CTt is studied with respect to other standardized psychological tests: the Primary Mental Abilities (PMA) battery, and the RP30 problem-solving test. Thus, it is intended to provide a new instrument for CT measurement and additionally give evidence of the nature of CT through its associations with key related psychological constructs. Results show statistically significant correlations at least moderately intense between CT and: spatial ability ( r = 0.44), reasoning ability ( r = 0.44), and problem-solving ability ( r = 0.67). These results are consistent with recent theoretical proposals linking CT to some components of the Cattel-Horn-Carroll (CHC) model of intelligence, and corroborate the conceptualization of CT as a problem-solving ability. [ABSTRACT FROM AUTHOR]

The study examined differences on flow experiences and different kinds of cognitive loads (intrinsic, extraneous, and germane cognitive loads) between game-based learning and non-game-based learning groups. Participants were students of two classes taking a general education course, named Life and Technology , in a university. There were a total of 103 participants in the experiment: 50 students in one class (experimental group) used game-based learning materials; 53 students in the other class (control group) used non-game-based learning materials (webpage-based learning material). The results revealed that the game-based learning group significantly created more flow experiences than the non-game-based learning group ( p < 0.01). The game-based learning group were significantly more interested, concentrated and able to control over their learning than the non-game-based learning group ( p < 0.05). The game-based learning group had significantly lower extraneous cognitive loads ( p < 0.05) and higher germane cognitive loads than the non-game-based learning group ( p < 0.05). There were no significant differences in intrinsic cognitive loads between both groups. The relationships of flow experiences with intrinsic ( r = −0.239; p < 0.05) and extraneous cognitive loads were negative ( r = −0.337; p = <0.01). The relationship between flow experiences and germane cognitive loads was positive ( r = 0.202; p < 0.05). Suggestions for educators, learners and future studies were also elaborated in the paper. [ABSTRACT FROM AUTHOR]

Across a broad range of design professions, there has been extensive research on design practices and considerable progress in creating new computer-based systems that support design work. Our research is focused on educational/instructional design for students' learning. In this sub-field, progress has been more limited. In particular, neither research nor systems development have paid much attention to the fact that design is becoming a more collaborative endeavor. This paper reports the latest research outcomes from R&D in the Educational Design Studio (EDS), a facility developed iteratively over four years to support and understand collaborative, real-time, co-present design work. The EDS serves to (i) enhance our scientific understanding of design processes and design cognition and (ii) provide insights into how designers' work can be improved through appropriate technological support. In the study presented here, we introduced a complex, multi-user, digital design tool into the existing ecology of tools and resources available in the EDS. We analysed the activity of four pairs of ‘teacher-designers’ during a design task. We identified different behaviors - in reconfiguring the task, the working methods and toolset usage. Our data provide new insights about the affordances of different digital and analogue design surfaces used in the Studio. [ABSTRACT FROM AUTHOR]

This paper explores how game and message related characteristics of interactivity and brand anthropomorphism interact each other with gamers' cognition demand (high cognition versus low cognition demand) to influence gamers' brand attention, brand recall, and brand recognition in advergames. The mixed-measures experimental design study revealed that in high cognition demand game play, gamers' brand attention, recognition, and recall are low, in comparison with low cognition demand game. However, in high cognition demand condition, gamers exposed to brand interactivity game (versus no interactivity and game interactivity) showed higher brand attention and memory. The results also showed that gamers’ brand anthropomorphism works as a boundary condition which further shapes the above-said effects. [ABSTRACT FROM AUTHOR]

As computers and internet access become more readily available at home, online testing and self-assessment are growing in popularity. In this article we briefly discuss the challenges and opportunities of online testing in general and then describe our experience with putting a standalone cognitive test battery online for users with special needs. Thereby the emphasis is on adopting the human-centered design process for the design of online tests and on the steps needed to be taken to arrive at a usable and validated online test battery. If the experience and process described in this paper turns out to be of value to researchers and/or practitioners in the field of using computers for human flourishing, this article will have achieved its purpose. [ABSTRACT FROM AUTHOR]

Studies show that virtual desktops have become a widespread approach to window management within desktop environments. However, despite their success, there is no experimental evidence of their effect on multitasking. In this paper, we present an experimental study incorporating 16 participants in which a traditional Windows 7 environment is compared to one augmented by virtual desktops. Within the experimental condition, each virtual desktop acts as a dedicated workspace devoted to an independent goal-oriented task, as opposed to the control condition where only one single workspace is available to perform the same tasks. Results show that adopting virtual desktops as dedicated workspaces allows for faster task resumption (10 s faster on average) and reduced cognitive load during sequential multitasking. Within our experiment the majority of users already benefited from using dedicated workspaces after three switches to a previously suspended task, as the time lost on setting up workspaces was compensated for by faster subsequent task resumption. These results provide a strong argument for supporting goal-oriented dedicated workspaces within desktop environments. [ABSTRACT FROM AUTHOR]

Academic studies reveal that copyright enforcement regimes are not reaching their full potential in lowering digital piracy rates. Still, very few demand-side studies tap into the reasons why this occurs. We conducted a scenario-based experiment on a sample of 401 consumers engaged in content streaming. We draw on cognitive appraisal theory to reveal that digital piracy beliefs shape consumers' emotional reactions (positive emotions vs. indignation) differently in opposing copyright enforcement regimes. Through reactance theory, we unfold consumers' coping mechanisms through which they comply with or show reactance to the designated regime (measured by intention to use illegal or legal streaming services). Our findings show that positive digital piracy beliefs drive positive emotions in loose and indignation in tight copyright enforcement regime. In terms of coping, we reveal that compliance to the regime is driven by positive while negative emotions drive reactance. Our study provides valuable insights by revealing antecedents that have not been previously addressed in digital piracy literature. Findings provide value to policymakers and managerial practice to better understand digital piracy's realities and redesign their policies and strategies accordingly. • We use a demand-side approach to reveal why copyright enforcement regimes fail. • This paper uses cognitive appraisal and reactance theories. • Two opposing copyright enforcement regimes (loose and tight) are designed. • (Mis)alignment between beliefs and regime triggers positive emotions (indignation). • Positive emotions (indignation) lead to compliance (reactance). [ABSTRACT FROM AUTHOR]

This paper stems from a mixed-methods study in which we scientifically tested 15 computer games to investigate their suitability for cognitive training. After determining which cognitive functions are utilized while playing these games, we were able to relate schoolchildren's game performance to their cognitive abilities (e.g., executive functioning, perception, memory). As a continuation, we sought to identify the factors that lead to greater engagement in games, such as children's age, gender, and cognitive skills, as well as game genres and features. Forty-one children played 15 computer games, each three times, under the scrutiny of two raters who completed an observational scale for each game. This scale was constructed as a reliable measure of engagement, comprising factors such as enjoyment, frustration, and effort. The data were analyzed using correlations and content analyses. The results indicated that game performance increased with greater levels of engagement and that games involving planning and problem solving tended to be too difficult for younger children. The findings of this study are informative for psychologists, educators, as well as game designers, and can be used to recommend engaging and beneficial games for children. [ABSTRACT FROM AUTHOR]

In high-risk domains such as human space flight, cognitive performances can be negatively affected by emotional responses to events and conditions in their working environment (e.g., isolation and health incidents). The COgnitive Performance and Error (COPE) model distinguishes effects of work content on cognitive task load and emotional state, and their effect on the professional's performance. This paper examines the relationships between these variables for a simulated Mars-mission. Six volunteers (well-educated and -motivated men) were isolated for 520 days in a simulated spacecraft in which they had to execute a (virtual) mission to Mars. As part of this mission, every other week, several computer tasks were performed. These tasks consisted of a negotiation game, a chat-based learning activity and an entertainment game. Before and after these tasks, and after post-task questionnaires, the participants rated their emotional state consisting of arousal, valence and dominance, and their cognitive task load consisting of level of information processing, time occupied and task-set switches. Results revealed significant differences between cognitive task load and emotional state levels when work content varied. Significant regression models were also found that could explain variation in task performance. These findings contribute to the validation of the COPE model and suggest that differences in appraisals for tasks may bring about different emotional states and task performances. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to describe an experimental study to reduce cognitive load and enhance usability for interactive geometry software. Design/methodology/approach The Graphical User Interface is the main mechanism of communication between user and system features. Educational software interfaces should provide useful features to assist learners without generate extra cognitive load. In this context, this research aims at analyzing a reduced and a complete interface of interactive geometry software, and verifies the educational benefits they provide. We investigated whether a reduced interface makes few cognitive demands of users in comparison to a complete interface. To this end, we designed the interfaces and carried out an experiment involving 69 undergraduate students. Findings The experimental results indicate that an interface that hides advanced and extraneous features helps novice users to perform slightly better than novice users using a complete interface. After receiving proper training, however, a complete interface makes users more productive than a reduced interface. Originality/value In educational software, successful user interface designs minimize the cognitive load on users; thereby users can direct their efforts to maximizing their understanding of the educational concepts being presented. [ABSTRACT FROM AUTHOR]

The effects of videogame play is a growing research field in the recent decades, however, little is known about how ‘out-of-school’ use of videogames influences creativity and emotions. This interdisciplinary study employed a within-participant design to explore the effects of two different types of online videogames (an action videogame and a non-action videogame) on subsequent creativity performance measured using an idea generation task and emotional responses. Results showed that after playing the action game participants performed higher on originality, elaboration and flexibility than after playing the non-action game, but not productivity. Furthermore, playing both types of game elicited positive emotion (i.e., pleasantness) high in approach motivation (i.e., desire). However, action video game play elicited higher arousal and stress than non-action videogame play. The current research suggests that the relationships between the quantity (productivity and flexibility) and the quality (in this paper, originality and elaboration) of creativity performance may be complex and emotional response of arousal might be a significant emotional factor which influences subsequent creativity performance after videogame play. The cognitive and emotional effects of videogames are discussed along with implications for future emotion–creativity–videogame research. [ABSTRACT FROM AUTHOR]

The literature so far has been focused on technological sophistication rather than the aspects of blockchain adoption that can hinder or facilitate the use of the technology. To address this gap this paper aims to study the cognitive factors underpinning adoption decision-making moderated by user characteristics. Using a cross-sectional research design, the study recruited 506 respondents to participate and test the relationships hypothesised in the research model. The results of the analysis demonstrated that perceived threat vulnerability, response cost, response efficacy and self-efficacy determine adoption intention. These factors have varying effects on intention depending on users' subjective knowledge, objective knowledge and innovativeness. This evidence contributes to the understanding of users' perspectives on blockchain adoption, which has been under-researched so far. The findings shed light on the cognitive factors motivating blockchain-based technology use and the individual characteristics of users who are likely to adopt the technology in the context of data privacy and security. In turn, these findings can inform practitioners about the aspects of user behaviour that should be considered while developing and marketing the technology. • The study provides an individual's perspective on blockchain-enabled technologies. • The study explores cognitive factors underpinning adoption decision-making. • Perceived threat and coping appraisal induce intention to use blockchain-enabled services. [ABSTRACT FROM AUTHOR]

Decision making is a fundamental building block of people’s lives. Each decision requires expenditure of cognitive effort, though to a varying degree, which is considered a valuable yet limited resource in the decision making literature. Though the importance of a cognitive effort minimization goal is well-established in the marketing literature, this paper examined how cognitive effort exertion can be useful to minimize negative emotions such as regret in the consumer decision making context. Study 1 explored the impact of cognitive effort on the experience of regret by conducting a 2 (Cognitive effort: High vs. Low) × 2 (Store type: Offline vs. Online) experiment and found higher cognitive effort exertion led to less regret after missing out on a lower price. This effect was most prominent in an offline purchase situation. Study 2 further examined the elements of online shopping that led to a higher regret by conducting a 2 (Cognitive effort: High vs. Low) × 2 (Type of Information: Touch vs. Visual) experiment. Study 2 confirmed the benefits of touch information in reducing experienced regret; but cognitive effort moderated this effect. Overall, the current studies contribute to the progression of knowledge between cognitive effort and experienced regret when shopping online and offline. [ABSTRACT FROM AUTHOR]

Spreading news in Web 2.0 is easy and ubiquitous, especially in Twitter via retweeting. However, while some news develops viral power, other remains disregarded. The paper presents two laboratory experiments about potentially influencing criteria on retweeting. Study 1 investigated whether content criteria (informational value) and context criteria (agent awareness) influence retweeting decisions. It was hypothesized that agent awareness would moderate the influence of informational value on retweeting. Results did not confirm the hypothesis but instead revealed that both high informational value and agent awareness information led to retweeting. Further, the influence of both informational value and agent awareness on retweeting was mediated by the perceived importance of the tweets. Study 2 investigated the influence of the informational value of the news, agent awareness, and in-group reference. It was hypothesized that the influence of informational value and of agent awareness on retweeting are moderated by in-group reference. The results confirmed these assumptions and showed that informational value had more influence if agents did not belong to a salient in-group compared to if they did. In contrast, agent awareness had more influence if agents belonged to a salient in-group compared to if they did not. [ABSTRACT FROM AUTHOR]

Studies have shown a correlation between reading comprehension and the visual appearance of the displayed text. One of the factors that affect the visual look of a text is its alignment. The purpose of this paper is to develop and implement a sophisticated algorithm to output a properly justified Arabic text. Most of the tools geared for e-document have not been tailored with Arabic in mind. And so, these either violate several calligraphic rules, or are a far cry from the aesthetics developed by the centuries old tradition of Arabic calligraphy. The scheme we developed is more realistic calligraphically and more pleasing aesthetically. It is a two-step process. Lines are populated with whole words, afterwards we use alternate form of the letters to compress or stretch the line as needed. In the second step we use kashida (elongation of the connecting line between the letters) to fill in the remaining gaps. There are strict rules which dictate which, when, and the minimum/maximum length of the kashida a word can have. We tested our justified Arabic text on university students. The experiment revealed the participants were able to read faster and had a better comprehension when presented with our justified text. The scheme we devised could be extended to other languages which share the basic Arabic script, e.g. Persian, and Urdu. [ABSTRACT FROM AUTHOR]

In the last decades, research has claimed facial micro-expressions are a reliable means to detect deception. However, experimental results showed that trained and naïve human judges observing facial micro-expressions can distinguish liars from truth-tellers with an accuracy just slightly above the chance level. More promising results recently came from the field of artificial intelligence, in which machine learning (ML) techniques are used to identify micro-expressions and are trained to distinguish deceptive statements from genuine ones. In this paper, we test the ability of different feature extraction methods (i.e., improved dense trajectories, OpenFace) and ML techniques (i.e., support vector machines vs. deep neural networks) to distinguish liars from truth-tellers based on facial micro-expressions, using a new video data set collected in low-stakes situations. During the interviews, a technique to increase liars' cognitive load was applied, facilitating cues of lies to emerge. Results highlighted that support vector machines (SVMs) coupled with OpenFace resulted in the best performing method (AUC = 0.72 videos without cognitive load; AUC = 0.78 videos with cognitive load). All the tested classifiers performed better when a cognitive load was imposed on the interviewee, confirming that the technique of increasing cognitive load during an interview facilitates deception recognition. In the same task, human judges obtained an accuracy of 57%. Results are discussed and compared with the previous literature, confirming that artificial intelligence performs better than humans in lie-detection tasks do, even when humans have more information to make a decision. • Automatic systems are better than humans in detecting deception from videos. • AI is a promising methodology to detect deception through facial micro-expressions. • AI performs better when the cognitive load of the interviewees is increased. • SVM is more able in distinguish liars from truth-tellers when trained with AUs as features. [ABSTRACT FROM AUTHOR]