Becoming the Expert - Interactive Multi-Class Machine Teaching

Compared to machines, humans are extremely good at classifying images into categories, especially when they possess prior knowledge of the categories at hand. If this prior information is not available, supervision in the form of teaching images is required. To learn categories more quickly, people should see important and representative images first, followed by less important images later - or not at all. However, image-importance is individual-specific, i.e. a teaching image is important to a student if it changes their overall ability to discriminate between classes. Further, students keep learning, so while image-importance depends on their current knowledge, it also varies with time. In this work we propose an Interactive Machine Teaching algorithm that enables a computer to teach challenging visual concepts to a human. Our adaptive algorithm chooses, online, which labeled images from a teaching set should be shown to the student as they learn. We show that a teaching strategy that probabilistically models the student's ability and progress, based on their correct and incorrect answers, produces better 'experts'. We present results using real human participants across several varied and challenging real-world datasets.Comment: CVPR 201

The Virtual Runner Learning Game

A learning game has been developed which allows learners to study and learn about the significance of three important variables in human physiology (lactate, glycogen, and hydration) and their influence on sports performance during running. The player can control the speed of the runner, and as a consequence the resulting physiological processes are simulated in real-time. The performance degradation of the runner due to these processes requires that different strategies for pacing the running speed are applied by the player, depending on the total length of the run. The game has been positively evaluated in a real learning context of academic physiology teaching

Teaching Inverse Reinforcement Learners via Features and Demonstrations

Learning near-optimal behaviour from an expert's demonstrations typically relies on the assumption that the learner knows the features that the true reward function depends on. In this paper, we study the problem of learning from demonstrations in the setting where this is not the case, i.e., where there is a mismatch between the worldviews of the learner and the expert. We introduce a natural quantity, the teaching risk, which measures the potential suboptimality of policies that look optimal to the learner in this setting. We show that bounds on the teaching risk guarantee that the learner is able to find a near-optimal policy using standard algorithms based on inverse reinforcement learning. Based on these findings, we suggest a teaching scheme in which the expert can decrease the teaching risk by updating the learner's worldview, and thus ultimately enable her to find a near-optimal policy.Comment: NeurIPS'2018 (extended version

Measuring cognitive load and cognition: metrics for technology-enhanced learning

This critical and reflective literature review examines international research published over the last decade to summarise the different kinds of measures that have been used to explore cognitive load and critiques the strengths and limitations of those focussed on the development of direct empirical approaches. Over the last 40 years, cognitive load theory has become established as one of the most successful and influential theoretical explanations of cognitive processing during learning. Despite this success, attempts to obtain direct objective measures of the theory's central theoretical construct – cognitive load – have proved elusive. This obstacle represents the most significant outstanding challenge for successfully embedding the theoretical and experimental work on cognitive load in empirical data from authentic learning situations. Progress to date on the theoretical and practical approaches to cognitive load are discussed along with the influences of individual differences on cognitive load in order to assess the prospects for the development and application of direct empirical measures of cognitive load especially in technology-rich contexts

Optimal Activation of French for Specific Purposes for Human Development in Nigeria

It would not be far from the truth to say that communication through the use of the natural language plays a paramount role in the quest for development, be it human, social, political, technological and any other form of development. A paramount role because knowledge, which is the life wire of any development effort, is acquired through information. Information comes through communication powered by language. Looking at Nigeria as a country, English which is the official language and language of instruction in schools seems to have become inadequate for a sustainable human development which must take into account new trends in the globalized world. It is based on this background that this paper aims at exploring the concept of French for Specific Purposes (FSP), a paradigm of French studies, which has not been optimally activated in Nigeria as against what obtains in countries such as USA, Britain, Japan etc. The paper begins by defining the concept of French for Specific Purposes and goes further to examine the importance of French in Nigeria. The paper also makes a critical analysis of developmental benefits that are derivable from the optimal activation of this concept in Nigeria. To conclude, the paper recommends various practical and pragmatic approaches, which include the introduction of FSP certificate and diploma programmes in Nigerian universities, as steps towards the optimal activation of the concept in the countr

Optimizing Cycle Exercise Performance During Normobaric Hypoxia Exposure

Introduction: The purpose of the present study was to examine whether implementing factors of OPTIMAL Theory: Enhanced Expectancies (EE), Autonomy Support (AS), and External Focus (EF) during a cycle exercise bout at a simulated altitude of 21,000 feet elevation had an effect on exercise performance and EPOC response in comparison to a control condition. Methods: Sixteen participants (n = 8 women, n = 8 men) completed resting oxygen measurements (resting metabolic rate) between 6:00 A.M. and 8:00 A.M. Cycle exercise to fatigue at a constant workload was performed (100 W) while breathing air with reduced oxygen content to simulate exercising at altitude (9.4% fraction of oxygen, equivalent of 6401 m above sea level). All participants performed under two conditions, an optimized and a control condition. The order of conditions were counterbalanced. Following cycle to fatigue protocol, participants were reconnected to the metabolic analysis system and instructed to sit quietly until they returned to their baseline oxygen values (EPOC duration). EPOC magnitude was determined by adding up the net oxygen consumption for every minute during the EPOC duration. Data analysis consisted of paired t-tests. Results: In summary, the results of this study reveal that cycle exercise performance between both conditions was significant, p = .03. Performance outcome measures included duration of cycle exercise to fatigue and mean watts (W). Participants were able to cycle longer in the optimized condition relative to the control, with exercise carried out at the same absolute workload. EPOC duration and magnitude in participants (N = 16) who performed cycling exercise at 100 W under simulated altitude of 6401 m (21,001 ft) to fatigue, resulted in no statistically significant difference between the following optimized and control conditions. Therefore, despite longer cycle exercise duration in the optimized condition, EPOC duration and magnitude in both conditions was not significantly different. Discussion: The present findings adds to evidence that key variables in the OPTIMAL theory influence energy expenditure, enhance movement efficiency, and reduce oxygen consumption. To the best of our knowledge, this is the first study to investigate aerobic exercise performance and EPOC response where all three variables in OPTIMAL theory are applied consecutively during exercise. Thus, further investigation is necessary to examine the physiological parameters of other exercise intensities to asses if similar results are produced