How navigation systems transform epistemic virtues: Knowledge,issues and solutions

In this paper, we analyse how GPS-based navigation systems are transforming some of our intellectual virtues and then suggest two strategies to improve our practices regarding the use of such epistemic tools. We start by outlining the two main approaches in virtue epistemology, namely virtue reliabilism and virtue responsibilism. We then discuss how navigation systems can undermine five epistemic virtues, namely memory, perception, attention, intellectual autonomy, and intellectual carefulness. We end by considering two possible interlinked ways of trying to remedy this situation: [i] redesigning the epistemic tool to improve the epistemic virtues of memory, perception, and attention; and [ii] the cultivation of cognitive diligence for wayfinding tasks scaffolding intellectual autonomy and carefulness.     

The Evolution of Business: Learning,Innovation, and Sustainability in the Twenty-First Century

This article-as part of a broader evolutionary inquiry toward human fulfillment, societal wellbeing, and environmental sustainability-explores new frontiers for business. In a rapidly changing global environment, corporations can become evolutionary change agents for the creation of a sustainable global civilization by fostering financial, social, and environmental results. The contemporary metaphors used to describe the business world can be limited in times when an emergent paradigm calls for new visions and actions. An evolutionary understanding, grounded in evolutionary systems theory, can open possibilities for leadership and innovation toward sustainability. Complex systems, such as organizations, need to learn to learn in harmony with the dynamics of their milieu in order to co-evolve and create value. The paper concludes with a reflection on the implications of the evolutionary paradigm for business education.     

A review of competitive sport motivation research

ObjectivesThe purpose of this review was to synthesise contemporary research on competitive sport motivation (1995–2016) with a view to identifying trends and gaps in sample characteristics, research designs and analytical strategies, and classifying associated topics.DesignNarrative review.MethodFour databases were searched using a focused search strategy, leading to 63 studies that met the inclusion criteria. These were then evaluated in five sections: Theoretical Frameworks, Sample Characteristics, Research Designs, Analytical Strategies and Topics.ResultsA total of 63 studies comprising 12,440 participants were appraised. The average sample size and participant age were 197 and 22.6 years, respectively. Just over half of the studies described their sample as high-level. The majority of studies were quantitative and employed a cross-sectional design. A range of innovative statistical analyses were used, with structural equation modelling being increasingly adopted. In addition to studies focusing on motivation as a stand-alone topic, researchers in the area also investigated its relationship with motivational climate, burnout, doping, perfectionism, injury, and several other related variables.ConclusionsAfter reviewing the body of research on this specific topic area, promising directions for future research are presented. The focused approach particularly seeks to encourage researchers to employ different methodologies, and prioritise underused topics in future research on competitive athlete groups. Furthermore, the review points to several practical implications for competitive sport stakeholders.     

MetrIntMeas a novel metric for measuring the intelligence of a swarm of cooperating agents

We propose a novel metric called MetrIntMeas (Metric for the Intelligence Measuring) for an accurate and robust measurement of the difficult problem-solving intelligence of a swarm system. The metric allows the classification if a swarm system belongs to the same class with the systems which have a specific reference intelligence value. For proving the efficiency of the proposed metric we realized a case study on a swarm system specialized in solving a NP-hard problem. As an application of the proposed metric, we present the measurement of the swarm systems’ evolution in intelligence. We gave a new definition to the intelligent evolving systems. The evolution of intelligent systems can be verified using the proposed MetrIntMeas metric.     

Changing Perspective: Building Creative Mindsets

The search for new ideas often frustratingly cycles back to old ones, a phenomenon known as fixation. Recent research has shown ways to kick-start finding new uses for familiar objects, a prototypical creativity task: wandering in the mind or the world or working on a messy desk. Those techniques seem to succeed by helping break fixation, but do not guide the search for new ideas. The perspective-taking or human-centric or empathic mindset championed by many in HCI and in design firms does provide a search strategy. We compared the mind-wandering mindset to a perspective-taking mindset, the latter priming thinking of ways that people in different roles (gardener, artist, etc.) might use the objects. In two studies, the Perspective-Taking mindset yielded more ideas and more original ideas than Mind-Wandering, which did not differ from a No-Mindset control. Original ideas came late, rewarding persistence. The perspective-taking mindset is productive for problem-solving, forecasting, and social interactions as well as innovation.     

Designing and evaluating an intelligent augmented reality system for assisting older adults’ medication management

Intelligent Assistive Systems (IASs) provide personalised support to individuals to increase their autonomy and competence in performing activities. The personalisation of such technology represents a particular challenge, for the individuals abilities typically change over time. The aim of this research was to explore a theory-based, activity-centred framework for the development of IASs that both facilitate the active involvement of caregivers and target users and allow for adaptation to the individual over time.Medication management was focused on as a case study. Three older adults and two caregivers were involved in a co-design process of an IAS prototype system, the MED-AR, which uses projection-based augmented reality as the user interface technology. The theoretical framework for the design and evaluation of the MED-AR was activity theory. For the decision-making process of the MED-AR, formal argumentation theory was used. The major contributions of the study are (i) a formal framework for understanding the level of independence in activities and the way an IAS can tailor support to an individual and a situation, including caregivers; and (ii) a model for involving older adults and caregivers in a co-design process in the first phases of developing IASs.     

Highlights as an Early Predictor of Student Comprehension and Interests

When engaging with a textbook, students are inclined to highlight key content. Although students believe that highlighting and subsequent review of the highlights will further their educational goals, the psychological literature provides little evidence of benefits. Nonetheless, a student’s choice of text for highlighting may serve as a window into her mental state—her level of comprehension, grasp of the key ideas, reading goals, and so on. We explore this hypothesis via an experiment in which 400 participants read three sections from a college-level biology text, briefly reviewed the text, and then took a quiz on the material. During initial reading, participants were able to highlight words, phrases, and sentences, and these highlights were displayed along with the complete text during the subsequent review. Consistent with past research, the amount of highlighted material is unrelated to quiz performance. Nonetheless, highlighting patterns may allow us to infer reader comprehension and interests. Using multiple representations of the highlighting patterns, we built probabilistic models to predict quiz performance and matrix factorization models to predict what content would be highlighted in one passage from highlights in other passages. We find that quiz score prediction accuracy reliably improves with the inclusion of highlighting data (by about 1%–2%), both for held-out students and for held-out student questions (i.e., questions selected randomly for each student), but not for held-out questions. Furthermore, an individual’s highlighting pattern is informative of what she highlights elsewhere. Our long-term goal is to design digital textbooks that serve not only as conduits of information into the reader’s mind but also allow us to draw inferences about the reader at a point where interventions may increase the effectiveness of the material.     

Spanning seven orders of magnitude: a challenge for cognitive modeling

Much of cognitive psychology focuses on effects measured in tens of milliseconds while significant educational outcomes take tens of hours to achieve. The task of bridging this gap is analyzed in terms of Newell's (1990) bands of cognition—the Biological, Cognitive, Rational, and Social Bands. The 10 millisecond effects reside in his Biological Band while the significant learning outcomes reside in his Social Band. The paper assesses three theses: The Decomposition Thesis claims that learning occurring at the Social Band can be reduced to learning occurring at lower bands. The Relevance Thesis claims that instructional outcomes at the Social Band can be improved by paying attention to cognition at the lower bands. The Modeling Thesis claims that cognitive modeling provides a basis for bridging between events on the small scale and desired outcomes on the large scale. The unit‐task level, at the boundary of the Cognitive and Rational Bands, is useful for assessing these theses. There is good evidence for all three theses in efforts that bridge from the unit‐task level to educational applications. While there is evidence for the Decomposition Thesis all the way down to the 10 millisecond level, more work needs to be done to establish the Relevance Thesis and particularly the Modeling Thesis at the lower levels.     

An effective metacognitive strategy: learning by doing and explaining with a computer‐based Cognitive Tutor

Recent studies have shown that self‐explanation is an effective metacognitive strategy, but how can it be leveraged to improve students' learning in actual classrooms? How do instructional treatments that emphasizes self‐explanation affect students' learning, as compared to other instructional treatments? We investigated whether self‐explanation can be scaffolded effectively in a classroom environment using a Cognitive Tutor, which is intelligent instructional software that supports guided learning by doing. In two classroom experiments, we found that students who explained their steps during problem‐solving practice with a Cognitive Tutor learned with greater understanding compared to students who did not explain steps. The explainers better explained their solutions steps and were more successful on transfer problems. We interpret these results as follows: By engaging in explanation, students acquired better‐integrated visual and verbal declarative knowledge and acquired less shallow procedural knowledge. The research demonstrates that the benefits of self‐explanation can be achieved in a relatively simple computer‐based approach that scales well for classroom use.