Investigation of sequence processing: A cognitive and computational neuroscience perspective

Serial order processing or sequence processing underlies many human activities such as speech, language, skill learning, planning, problem-solving, etc. Investigating the neural bases of sequence processing enables us to understand serial order in cognition and also helps in building intelligent devices. In this article, we review various cognitive issues related to sequence processing with examples. Experimental results that give evidence for the involvement of various brain areas will be described. Finally, a theoretical approach based on statistical models and reinforcement learning paradigm is presented. These theoretical ideas are useful for studying sequence learning in a principled way. This article also suggests a two-way process diagram integrating experimentation (cognitive neuroscience) and theory/ computational modelling (computational neuroscience). This integrated framework is useful not only in the present study of serial order, but also for understanding many cognitive processes

USING THE REVISED BLOOM\u27S TAXONOMY TO SCAFFOLD STUDENT LEARNING IN BUSINESS INTELLIGENCE/BUSINESS ANALYTICS

The paper aims to make a theoretical and practical contribution to the field of Business Intelligence/Business Analytics (BI) education, by addressing the following practice-inspired, teaching-related research question: How to design learning activities to scaffold student learning in Business Intelligence (Business Analytics) towards more advanced cognitive and knowledge dimensions, and along the way help students to further develop their meta-cognitive skills of learning how to learn The paper adopts the revised Bloom?s taxonomy as a theoretical framework and demonstrates its use in designing and implementation of BI-related learning activities at different levels of cognitive and knowledge dimensions. The paper also offers some research contributions related to the framework itself, in particular correlation of different levels of cognitive process and knowledge dimensions, not captured by the revised taxonomy

Framework for Studying Spatially Ordered Treemaps

We propose a comprehensive research framework to empirically investigate complex visual inference tasks, support mechanisms (animated transition using morphing or vector overlay), and how spatial ability affects people’s learning and knowledge construction process from Spatially Ordered Treemaps (SOTs) as compared to conventional choropleth maps. This effort is inspired by the call of the new International Cartographic Association commission on Cognitive Visualization (CogVis), which proposes “developing a sound theoretical framework based upon cognition and perception discipline” (Fabrikant, 2011). The framework aims to explore SOTs in the context of both ‘in-vitro’ and ‘in-vivo’ settings. This study is grounded in cartography but also conforms to experimental design standards in per-ception and cognitive sciences

Regional Learning Networks in Medium-Tech Technologies and European Integration

The paper aims at investigating the transfer of tacit knowledge both at the regional and at the interregional level and it focuses on the factors and forms of the processes of interactive learning between small and medium size in medium technology sectors. The analysis proceeds from the contributions of four strands of literature, focusing on economics of agglomeration, cognitive economics, industrial strategic alliances and governance in a knowledge economy. While industrial economics interprets technology spill-over at the local level as an automatic and chaotic process allowed by geographical proximity of the firms, regional economics identifies different specific types of flows and networks, which link together in an organized way the various firms and other private and public actors within a given regional innovation system. Cognitive economics may bring a significant contribution, as it considers the relevance for economics of human cognitive aspects and it discovers the key role in the creation of new ideas of selected factors, such as the stimulus by changes in the external environment, the process of “neurognosis†or negative reaction aiming to the protection of the internal integrity, the search process constrained by cognitive proximity, the success in pattern making and the achievement of consistency and compatability, the process of “exaptation†or reconversion leading to path-dependency, the creation of new connections and routines and institutions, which allows to save the limited cognitive capacity of individuals and organizations. This theoretical framework in the analysis of the processes of knowledge creation may be schematically represented through the model of “Territorial Knowledge Managementâ€, which aims at promoting the interactive learning processes within the regional innovation systems and focuses on a selected list of knowledge levers, such as: market orientation, accessibility, receptiveness, common identity, creativity and governance. On the base of these theoretical concepts and tools, the paper analyses various case studies of firms embedded in different industrial clusters in Europe, focusing on the forms of the process of interactive learning and innovation between the various regional actors. Finally, the paper attempts to derive from that analysis useful indications for the possible extension of knowledge and innovation networks at the interregional and international level and for decreasing the regional divide in a modern knowledge economy. The research has been undertaken within the framework of the project: “IKINET – International Knowledge and Innovation Network†(EU FP6, N° CIT2-CT-2004-506242). Keywords: knowledge creation, interactive learning processes, industrial clusters, innovation policies, European integration, medium technology sectors, small and medium size firms.

Cognitive processes underlying mathematical concept construction: The missing process of structural abstraction

The purpose of this paper is twofold: On the one hand, this work frames a variety of considerations on cognitive processes underlying mathematical concept construction in two research strands, namely an actions-first strand and an objects-first strand, that mainly shapes past and current approaches on abstraction in learning mathematics. This classification provides the identification of an often overlooked fundamental cognitive process, namely structural abstraction. On the other hand, this work shows a theory-driven and research-based approach illuminating the hidden architecture of cognitive processes involved in structural abstraction that gives new insights into an integrated framework on abstraction in learning mathematics. Based on our findings in empirical investigations, the paper outlines a theoretical framework on the cognitive processes taking place on mental (rather than physical) objects

Fundamental processes in sensorimotor learning: Reasoning, refinement, and retrieval.

Motor learning is often viewed as a unitary process that operates outside of conscious awareness. This perspective has led to the development of sophisticated models designed to elucidate the mechanisms of implicit sensorimotor learning. In this review, we argue for a broader perspective, emphasizing the contribution of explicit strategies to sensorimotor learning tasks. Furthermore, we propose a theoretical framework for motor learning that consists of three fundamental processes: reasoning, the process of understanding action-outcome relationships; refinement, the process of optimizing sensorimotor and cognitive parameters to achieve motor goals; and retrieval, the process of inferring the context and recalling a control policy. We anticipate that this 3R framework for understanding how complex movements are learned will open exciting avenues for future research at the intersection between cognition and action

A framework for re-thinking learning in science from recent cognitive science perspectives

Recent accounts by cognitive scientists of factors affecting cognition imply the need to reconsider current dominant conceptual theories about science learning. These new accounts emphasize the role of context, embodied practices and narrative-based representation rather than learners&rsquo; cognitive constructs. In this paper we analyze data from a longitudinal study of primary school children&rsquo;s learning to outline a framework based on these contemporary accounts, and to delineate key points of difference from conceptual change perspectives. The findings suggest this framework provides strong theoretical and practical insights into how children learn and the key role of representational negotiation in this learning. We argue that the nature and process of conceptual change can be re-interpreted in terms of the development of students&rsquo; representational resources.<br /

Meta-Learning Strategies through Value Maximization in Neural Networks

Biological and artificial learning agents face numerous choices about how to learn, ranging from hyperparameter selection to aspects of task distributions like curricula. Understanding how to make these meta-learning choices could offer normative accounts of cognitive control functions in biological learners and improve engineered systems. Yet optimal strategies remain challenging to compute in modern deep networks due to the complexity of optimizing through the entire learning process. Here we theoretically investigate optimal strategies in a tractable setting. We present a learning effort framework capable of efficiently optimizing control signals on a fully normative objective: discounted cumulative performance throughout learning. We obtain computational tractability by using average dynamical equations for gradient descent, available for simple neural network architectures. Our framework accommodates a range of meta-learning and automatic curriculum learning methods in a unified normative setting. We apply this framework to investigate the effect of approximations in common meta-learning algorithms; infer aspects of optimal curricula; and compute optimal neuronal resource allocation in a continual learning setting. Across settings, we find that control effort is most beneficial when applied to easier aspects of a task early in learning; followed by sustained effort on harder aspects. Overall, the learning effort framework provides a tractable theoretical test bed to study normative benefits of interventions in a variety of learning systems, as well as a formal account of optimal cognitive control strategies over learning trajectories posited by established theories in cognitive neuroscience.Comment: Under Revie

Is there a Connection between Learning Style Preferences and Video Game Genres?

The purpose of this research was to determine if a correlation exists between video game genres and learning style preferences The framework used was the cognitive behavioral theoretical framework The quantitative research that guided the study was the relationship between learning style preference and an individual s preferred genre of video game A VARK Survey was implemented to collect data the second data collection process was the different video game genres people play The data was analyzed using the Chi-square test of independence For most video game genres and learning style preferences there was no correlation Teachers administration and workshop educators might benefit by learning how to integrate video game genres to differentiate the lessons for their student

Cognitive modeling and learning with sparse binary hypervectors

Following the general theoretical framework of VSA (Vector Symbolic Architecture), a cognitive model with the use of sparse binary hypervectors is proposed. In addition, learning algorithms are introduced to bootstrap the model from incoming data stream, with much improved transparency and efficiency. Mimicking human cognitive process, the training can be performed online while inference is in session. Word-level embedding is re-visited with such hypervectors, and further applications in the field of NLP (Natural Language Processing) are explored.Comment: 12 page