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"Conceptual knowledge"
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An introduction to description logic
Description logics (DLs) have a long tradition in computer science and knowledge representation, being designed so that domain knowledge can be described and so that computers can reason about this knowledge. DLs have recently gained increased importance since they form the logical basis of widely used ontology languages, in particular the web ontology language OWL. Written by four renowned experts, this is the first textbook on description logics. It is suitable for self-study by graduates and as the basis for a university course. Starting from a basic DL, the book introduces the reader to their syntax, semantics, reasoning problems and model theory and discusses the computational complexity of these reasoning problems and algorithms to solve them. It then explores a variety of reasoning techniques, knowledge-based applications and tools and it describes the relationship between DLs and OWL.-- Source other than Library of Congress.
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Preparatory effects of problem solving versus studying examples prior to instruction
The Productive Failure (PF) approach prompts students to attempt to solve a problem prior to instruction – at which point they typically fail. Yet, research on PF shows that students who are involved in problem solving prior to instruction gain more conceptual knowledge from the subsequent instruction compared to students who receive the instruction first. So far, there is no conclusive evidence, however, that the beneficial effects of PF are explained by the attempt to generate one’s own solutions prior to instruction. The literature on example-based learning suggests that observing someone else engaging in problem-solving attempts may be an equally effective means to prepare students for instruction. In an experimental study, we compared a PF condition, in which students were actively engaged in problem solving prior to instruction, to two example conditions, in which students either observed the complete problem-solving-and-failing process of another student engaging in PF or looked at the outcome of this process (i.e., another student’s failed solution attempts). Rather than worked examples of the correct solution procedure, the students observed examples of failed solution attempts. We found that students’ own problem solving was not superior to the two example conditions. In fact, students who observed the complete PF process even outperformed students who engaged in PF themselves. Additional analyses revealed that the students’ prior knowledge moderated this effect: While students who observed the complete PF process were able to take advantage of their prior knowledge to gain more conceptual knowledge from the subsequent instruction, prior knowledge did not affect students’ post-test performance in the PF condition.
Journal Article
Identity work in organizations and occupations
Understanding how, why, and when individuals create particular self-meanings has preoccupied scholars for decades, leading to an explosion of research on identity work. We conducted a wide-ranging review of this literature with the aim of presenting an overarching framework that comprehensively summarizes and integrates the vast amount of recent research in this domain. Drawing on our analysis of the empirical literature, we present an enhanced conceptual understanding of identity work. We then summarize the four dominant theoretical approaches researchers have used to explain how, when, and why individuals engage in identity work. This side-by-side comparison of these theoretical perspectives allows us to parse out the unique contribution of each theoretical lens and highlights how these theories can be integrated into a holistic view of an inherently multifaceted concept. Lastly, we critically analyze the state of the field and lay a detailed roadmap for future researchers to draw from to expand our current understanding of how individuals work on their identities in occupations and organizations.
Journal Article
Lower- and higher-level models of right hemisphere language. A selective survey
The models advanced to explain right hemisphere (RH) language function can be divided into two main types. According to the older (lower-level) models, RH language reflects the ontogenesis of conceptual and semantic-lexical development; the more recent models, on the other hand, suggest that the RH plays an important role in the use of higher-level language functions, such as metaphors, to convey complex, abstract concepts. The hypothesis that the RH may be preferentially involved in processing the semantic-lexical components of language was advanced by Zaidel in splitbrain patients and his model was confirmed by neuropsychological investigations, proving that right brain-damaged patients show selective semanticlexical disorders. The possible links between lower and higher levels of RH language are discussed, as is the hypothesis that the RH may have privileged access to the figurative aspects of novel metaphorical expressions, whereas conventionalization of metaphorical meaning could be a bilaterally-mediated process involving abstract semantic-lexical codes.
Journal Article
Higher education contributing to local, national, and global development
Higher education offers the potential to support glonacal (global, national, and local) development. This study presents new empirical and conceptual insights into the ways in which higher education can help to achieve and exceed the outcomes enshrined in the Sustainable Development Goals. Open-ended online surveys were used to learn how academics in Georgia and Kazakhstan view the contributions of universities to addressing self-identified development challenges; and how universities work with the government and the private sector for realising their glonacal development potential. While the study provides ample evidence on the national manifestations of the developmental role of universities, it also shows that limited academic freedom and institutional autonomy impede the full realisation of the potential of higher education. The assumptions underpinning the academics’ views on how higher education can support development are discussed in the light of an innovative framework of essentialist and anti-essentialist approaches. Juxtaposing the national with the global development missions of universities, the paper raises questions on the possibility of delinking higher education from the immediate human capital and modernisation needs of the nation-state and becoming concerned with the global, on promoting freedom to cultivate intellectual curiosity through education and research, and stimulating a more holistic imaginary of the developmental purposes of higher education.
Journal Article
Comparing alternative sequences of examples and problem-solving tasks: the case of conceptual knowledge
In cognitive load theory, the superiority of the Example-Problem sequence over the Problem-Example sequence has become a classic paradigm. The comparative effectiveness of these sequences, however, is subject to the influence of the factors of element interactivity and prior knowledge, and studies have examined these influences focused mostly on procedural rather than conceptual knowledge. This paper takes a deeper look at the effect of types of knowledge concentrating on conceptual knowledge. An experiment is reported comparing the Problem-Example and Example-Problem sequences on two levels of element interactivity, low versus high, which were associated with two types of conceptual knowledge (general principle knowledge and knowledge of principles underlying procedures, accordingly). Since there was no difference found between these sequences for either level of element interactivity, the paper discusses conditions of effectiveness of example-based instructions for different knowledge types in the broader context of Explicit Instruction First and Problem-Solving First approaches.
Journal Article
Neurocognitive insights on conceptual knowledge and its breakdown
Conceptual knowledge reflects our multi-modal ‘semantic database’. As such, it brings meaning to all verbal and non-verbal stimuli, is the foundation for verbal and non-verbal expression and provides the basis for computing appropriate semantic generalizations. Multiple disciplines (e.g. philosophy, cognitive science, cognitive neuroscience and behavioural neurology) have striven to answer the questions of how concepts are formed, how they are represented in the brain and how they break down differentially in various neurological patient groups. A long-standing and prominent hypothesis is that concepts are distilled from our multi-modal verbal and non-verbal experience such that sensation in one modality (e.g. the smell of an apple) not only activates the intramodality long-term knowledge, but also reactivates the relevant intermodality information about that item (i.e. all the things you know about and can do with an apple). This multi-modal view of conceptualization fits with contemporary functional neuroimaging studies that observe systematic variation of activation across different modality-specific association regions dependent on the conceptual category or type of information. A second vein of interdisciplinary work argues, however, that even a smorgasbord of multi-modal features is insufficient to build coherent, generalizable concepts. Instead, an additional process or intermediate representation is required. Recent multidisciplinary work, which combines neuropsychology, neuroscience and computational models, offers evidence that conceptualization follows from a combination of modality-specific sources of information plus a transmodal ‘hub’ representational system that is supported primarily by regions within the anterior temporal lobe, bilaterally.
Journal Article
Toward Virtual Community Knowledge Evolution
This paper puts forth a vision and an architecture for a community knowledge evolution system. We propose augmenting a multimedia document repository (digital library) with innovative knowledge evolution support, including computer-mediated communications, community process support, decision support, advanced hypermedia features, and conceptual knowledge structures. These tools, and the techniques developed around them, would enable members of a virtual community to learn from, contribute to, and collectively build upon the community's knowledge and improve many member tasks. The resulting Collaborative Knowledge Evolution Support System (CKESS) would provide an enhanced digital library infrastructure serving as an ever-evolving repository of the community's knowledge, which members would actively use in everyday tasks and regularly update.
Journal Article
When combinations of humans and AI are useful: A systematic review and meta-analysis
Inspired by the increasing use of artificial intelligence (AI) to augment humans, researchers have studied human–AI systems involving different tasks, systems and populations. Despite such a large body of work, we lack a broad conceptual understanding of when combinations of humans and AI are better than either alone. Here we addressed this question by conducting a preregistered systematic review and meta-analysis of 106 experimental studies reporting 370 effect sizes. We searched an interdisciplinary set of databases (the Association for Computing Machinery Digital Library, the Web of Science and the Association for Information Systems eLibrary) for studies published between 1 January 2020 and 30 June 2023. Each study was required to include an original human-participants experiment that evaluated the performance of humans alone, AI alone and human–AI combinations. First, we found that, on average, human–AI combinations performed significantly worse than the best of humans or AI alone (Hedges’
g
= −0.23; 95% confidence interval, −0.39 to −0.07). Second, we found performance losses in tasks that involved making decisions and significantly greater gains in tasks that involved creating content. Finally, when humans outperformed AI alone, we found performance gains in the combination, but when AI outperformed humans alone, we found losses. Limitations of the evidence assessed here include possible publication bias and variations in the study designs analysed. Overall, these findings highlight the heterogeneity of the effects of human–AI collaboration and point to promising avenues for improving human–AI systems.
Vaccaro et al. present a systematic review and meta-analysis of the performance of human–AI combinations, finding that on average, human–AI combinations performed significantly worse than the best of humans or AI alone. They also found performance losses in decision-making tasks and significantly greater gains in content creation tasks.
Journal Article
An Investigation of Algebra Performance and Conceptual Knowledge of Arithmetic in Adults
Conceptual understanding of arithmetic is considered a key component for success in advanced mathematics topics such as algebra, but the link between them has rarely been investigated, particularly in adults. Participants solved conducive (3 х 26 + 26) and nonconducive (26 х 3 + 26) inversion problems, conducive (3 x 26 + 13) and nonconducive (26 x 3 + 13) associativity problems, and multiplication (3 x 6 x 12 = 3 x ?) and division (36 + 8 + 4 = 36 + ?) equivalence problems and completed an algebra task. Conceptually based shortcut use on the nonconducive inversion problems was the strongest predictor of algebra scores. Participants who used conceptually based shortcuts on more problem types had higher algebra scores than participants who had low use of conceptually based shortcuts on most problem types. The results support the relationship between algebra and conceptual understanding of arithmetic and demonstrate that even in adulthood there are pronounced individual differences in conceptual understanding of arithmetic, which may impact success in advanced mathematics.
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