Infrastructures of abstraction: how computer science education produces anti-political subjects

ABSTRACT

Abstraction, defined in Computer Science (CS) as bracketing unnecessary information from diverse components within a system, serves as a central epistemological axis in CS disciplinary and pedagogical practices. Its impressions can be seen across curricula, syllabi, classroom structures, IT systems; and other dimensions of the epistemic infrastructure of CS (Malazita [Forthcoming]. “Epistemic Infrastructures, the Instrumental Turn, and the Digital Humanities.” In Debates in the Digital Humanities: Infrastructures, Institutions at the Interstices, edited by Angel Nieves, Siobhan Senier, and Anne McGrail. University of Minnesota Press). As we will argue in this essay, abstraction in CS serves as an epistemic, cultural, and ideological wall to integrated critical-technical education, rather than as a bridge. Further, this wall is disguised as a bridge: the common language used across CS and the Humanities gives the impression that abstraction can be leveraged as a boundary object (Star [2010]. “This is Not a Boundary Object: Reflections on the Origin of a Concept.” Science, Technology, & Human Values 35 (5): 601–617), as a point of connection among conflicting or incommensurable epistemic cultures (Knorr Cetina [1999]. Epistemic Cultures: How the Sciences Make Knowledge. Cambridge: MIT Press). Rather, computational knowledge practices leverage abstraction’s homographic-ness, epistemically structuring collaborative efforts in anti-political ways. To illustrate the impacts of abstraction, this essay will introduce ‘Critical CS1,’ a hybrid pedagogical approach to teaching Computer Science through feminist and critical race theory. However, other components of the epistemic infrastructures of Computer Science, from curricular structure, to IT systems, to classroom culture, to the epistemic practices of coding itself, resisted these intervention efforts, and reproduced marginalizing effects upon students within the course.     

Why zombies cannot write significant source code: The Knowledge Game and the art of computer programming

This article analyses the knowledge needed to understand a computer program within the philosophy of information. L. Floridi's method of levels of abstraction is applied to the relation between an ideal programmer and a modern computer seen together as an informational organism. The results obtained by the mental experiment known as the Knowledge Game are applied to this relation, so to explain what a programmer should know in order to program a modern computer. In particular, this analysis clearly shows why non-conscious agents have no hopes to write significant programs. Two main objections are then presented and attacked by corresponding counterobjections.     

Abstraction of levels of abstraction

The notion of level of abstraction (LoA) is one of the foundations of the Floridi's Philosophy of Information. It also serves for many practical purposes as in information ethics. But the notion of abstraction is not new; it has been given many different meanings in various fields, especially in scientific disciplines and, in particular, in computer science. Our purpose here is to examine the use of abstraction in Floridi's works in conjunction with some of the meanings of abstraction in computer science. The article is divided into five sections. After a general introduction to the Floridi's method of abstraction (MoA) in Section 1, Section 2 revisits Floridi's definition of abstraction and Section 3 gives the different senses of abstraction in computer science. The Section 4 compares them with the Floridi's LoAs and proposes to generalise the Floridi's approach to abstraction using an abstraction of the LoAs, while Section 5 concludes on what we think to be some new arguments in favour of MoA and LoA.     

A framework for knowledge-based temporal abstraction

A new domain-independent knowledge-based inference structure is presented, specific to the task of abstracting higher-level concepts from time-stamped data. The framework includes a model of time, parameters, events and contexts. A formal specification of a domain's temporal abstraction knowledge supports acquisition, maintenance, reuse and sharing of that knowledge.

The knowledge-based temporal abstraction method decomposes the temporal abstraction task into five subtasks. These subtasks are solved by five domain-independent temporal abstraction mechanisms. The temporal abstraction mechanisms depend on four domain-specific knowledge types: structural, classification (functional), temporal semantic (logical) and temporal dynamic (probabilistic) knowledge. Domain values for all knowledge types are specified when a temporal abstraction system is developed.

The knowledge-based temporal abstraction method has been implemented in the RÉSUMÉ system and has been evaluated in several clinical domains (protocol-based care, monitoring of children's growth and therapy of diabetes) and in an engineering domain (monitoring of traffic control), with encouraging results.     

Assessment frequency in introductory computer programming disciplines

Introductory computer programming disciplines commonly show a significant failure rate.Although several reasons have been advanced for this state of affairs, we argue that for a beginner student it is hard to understand the difference between know-about disciplines and know-how-to-do-it disciplines, such as computer programming. This leads to failure because when students understand they are not able to solve a programming problem it is usually too late to catch all the time meanwhile lost.In order to make students critically analyse their progress, instructors have to provide them with realistic indicators of their performance.To achieve this awareness and to trigger corrective actions in a timely manner there is a need to increase assessment frequency. This paper discusses how this can be done, analyses benefits of the proposed approach and presents data on the effects of changes in assessment frequency for a university first year course in fundamentals of computer programming.     

论函数编程技术在计算机数学教学中的应用

计算机数学作为计算机学科一门重要专业基础课程在计算机的教授与学习中起到承上启下的作用.随着网络时代的到来,企业、政府、个人都看到了计算机在生产生活中必不可少的作用,计算机成为生活中必不可少的东西.网络时代的发展也带动了计算机学科的发展,成为热门学科.计算机学科和数学是分不开的,因此也称为最有难度的一个学科.虽然很多学生选择计算机学科,但是在实际课堂教育中,学生的听课效率却不如预期,主要因为计算机数学内容理论性很强,而且一些概念知识很抽象,让学生很难理解,从而对学科内容不感兴趣.函数编程技术在教学中应用,对计算机数学的学习起到了辅助作用,让学生可以利用这种编程语言了解计算机数学的一些抽象性概念,更好的在实践中运用计算机数学.函数编程技术在计算机数学中应用,使得死板的理论学科变得稍显活泼,这回让学生对该学科更感兴趣,带动学生积极主动地学习.     

Exploring barriers to knowledge flow at different knowledge management maturity stages

A significant amount of work has been done to better understand the barriers to knowledge flow and develop models of KM maturity; this was intended to help in assessing the progress of KM initiatives in the firm. However, to date there has been no comprehensive research that considers both these issues at the same time, and thus it is still necessary to explore the evolution of barriers to knowledge flow when the level of KM maturity is changing. We reviewed the progress of KM initiatives in recent years, categorized the barriers to knowledge flow according to the cultural historical activity theory (CHAT), and used one of the existing models of KM maturity (the Knowledge Navigator Model—KNM), to address gaps in the current literature. As part of our exploratory study, a longitudinal survey, involving constant observation, development and use of questionnaires and qualitative interviews with managers of seven firms were conducted. We selected the firms so they covered a wide range of KM maturity levels; triangulation was adopted to enhance the quality of the process. The major findings indicated that: (1) barriers to knowledge flow were inherently different at different KM maturity levels; and (2) various changes in the barriers to knowledge flow were associated with the maturity of the KM.     

视频摘要技术综述

目的 类似于文本摘要,视频摘要是对视频内容的总结。为了合理地评估视频摘要领域的研究进展,正确导向视频摘要的继续研究,本文归纳总结视频摘要技术的主要研究方法和显著性成果,对视频摘要技术进行综述。方法 依据视频摘要的两个主要生成步骤:视频内容分析和摘要生成分别介绍视频摘要的主要研究方法。同时,分析了近5年视频摘要领域的研究状况,对视频摘要发展的新趋势:实时视频摘要和多视角视频摘要进行了阐述。最后,还对视频摘要的评价系统进行了分类总结。结果 对视频摘要进行综述,对摘要中的语义获取难题提出了2种指导性建议。并依据分析结果,展望了视频摘要技术未来的发展方向。结论 视频摘要技术作为视频内容理解的重要组成部分,有较大研究价值。而目前,视频摘要在视频语义表达和摘要评价系统方面并不精确完善,还需进一步的深入研究。     

A multivariate comparison of computer anxiety levels between candidate and tenured school principals

School administrators should be able to follow technological advancements and promote the role of leadership with regard to technology in their institutions. However, affective factors such as computer anxiety might hinder administrators’ roles in this process. Therefore, this study investigated multivariate differences between candidate and tenured administrators on computer anxiety levels, after accounting for differences in age. The sample of the study included 216 candidates and 368 tenured school principals. The Computer Anxiety Scale and a set of demographic questions were used to collect the data. One-way multivariate analysis of covariance (MANCOVA) was performed on three dependent variables that are the three dimensions of computer anxiety (i.e., Affective Anxiety, Damaging Anxiety, and Learning Anxiety). Independent variable had two levels (i.e., candidate versus tenured administrators) and age was used as a covariate. Results showed multivariate significant differences. Candidate administrators reported higher levels of affective and learning anxiety compared to their tenured colleagues. We conclude that the sample of the study had accessibility and familiarity with computers; yet, showed different experiences. Finally, refinement is still needed in the area of computer anxiety and its relationships with other variables among educational administrators.     

A creative arts approach to computer programming

This paper describes how the creative arts can provide an alternative approach to computer programming that may benefit students in the humanities in general. It focuses on creative arts projects using text, graphics and music that allow students to encounter the same programming concepts from a number of different perspectives. It also discusses the importance of symbolic programming for the arts and how the creative arts can provide a particularly rich environment for developing approaches to object-oriented programming.Gary Greenberg received his B. A. and M. A. in Music from Stanford University and his Ph.D. in Music from Harvard University. His activities include creating compositional programming environments (Composing with Performer Objects, The Proceedings of the 1988 International Computer Music Conference) and developing ways of using the computer to learn about music through compositional activities (Music Learning-Compositional Thinking). He is currently manager of the Northwestern University Advanced Technology Group where he coordinates the Computer Media Studio and is exploring ways to use computer multimedia in instruction and research.     

The training of knowledge structures for manufacturing tasks: an empirical study

Abstract

Knowledge structure refers to the manner in which a human organizes knowledge with a given domain. Research has identified knowledge structure as a determinant of the human ability to perform cognitive-oriented tasks. Yet uncertainty still exists about how to improve an individual's cognitive task performance through the controlled utilization of the individual's knowledge structure. The purpose of this study is to investigate whether the development of individual's knowledge structure in a particular domain can be manipulated through training. The experiment utilized the manufacturing domain of plastic extrusion machine operation. Sixteen subjects, having no previous knowledge of the domain, were randomly assigned to one of two experimental groups. Each of the experimental groups corresponded to a distinct training condition. Over a three-day period, both training groups received the same instructional content; however, the sequence in which the training material was presented differed. One group initially received the abstract, conceptual relationships between domain concepts, followed by more detailed relationships associated with the lower level aspects of the domain. The other group received the training material in the reverse order; i.e. the lower level information followed by the abstract. Prior to and concluding the training sessions, each individual's knowledge structure was assessed along two dimensions, hierarchical levels and multiple relations, through a computer-based measurement technique.entitled KSAT. The group which received the abstract relationships first showed significant improvement following training along both dimensions of knowledge structure. No significant changes in the knowledge structure dimensions were found for the group which received the lower level relationships first. This study suggests that an individual's knowledge structure can be manipulated through training, with a significant effect being attributed to the training sequence of abstract material followed by the more detailed material.     

基于能力培养的计算机程序设计课程的教学方法的探索与研究

《计算机程序设计》课程在军队院校教育中有着非常重要的地位。分析探究了几种应用于程序设计课程中的教学方法,旨在使计算机课程的教育能够真正促进学员提升综合能力和素质。     

Designing an API at an appropriate abstraction level for programming social robot applications

Whilst robots are increasingly being deployed as social agents, it is still difficult to program them to interact socially. To create usable tools for programming these robots, tool developers need to know what abstraction levels are appropriate for programming social robot applications. We explore this through the iterative design and evaluation of an API for programming social robots. The results show that high level primitives, with a close mapping to social interaction, are suitable for programming social robot applications. However, the abstraction level should not be so high that it takes away too much control from programmers. This has the potential to enable programmers to produce high quality social robot applications with less programming effort.     

Parallel programming for a chess endgame database

This paper presents a parallel implementation in APL of an algorithm to set up a database for the KRK -endgame in chess. It shows clearly the techniques necessary to achieve the parallelism and thereby proves that APL can be a valuable productivity increasing aid in this kind of Artificial Intelligence (AI)-research. The complete APL-functions are given in the Appendix. Both reversed pigeon hole and bit map techniques are used. Move generation is table driven with a new technique to cater for the blockage of sliding pieces like a rook. In order to maintain parallelism ‘if’ statements are avoided and extensive use is made of compression and identity elements.     

Modeling diagnosis at multiple levels of abstraction. I. Representing causal relations at multiple levels of abstraction

A significant body of causal knowledge for diagnostic problem-solving is organized at multiple levels of abstraction. By this we mean that causal relations are specified in terms of disorder and manifestation classes that can be further refined as well as in terms of specific, unrefinable disorders and manifestations. Such knowledge enables diagnostic problem-solvers (human or automated) to efficiently form initial, high-level diagnostic hypotheses while avoiding the explicit consideration of unnecessary details. This article develops a knowledge representation framework to precisely yet naturally capture causal relations at multiple levels of abstraction. Different interpretations of high-level causal associations are precisely defined and systematically tabulated. Rules to infer implicit causal relations from explicitly declared causal relations are also identified. These ideas have been implemented in a working system for medical diagnosis. the results presented in this article also offers a new perspective on studying the semantics of knowledge representation in general.     

An ontological basis for computer aided innovation

Knowledge acquisition and capitalization to solve problems concerning artefact evolution, still called inventive design, has a certain quantity of specific characteristics. It needs the choice of certain pieces of knowledge that may induce evolutions; it leads to reformulating the initial problem to build an abstract model of the artefact. The theoretical approach we are interested in, called TRIZ (the Russian acronym for Theory for Inventive Problem Solving), when translated into a methodological procedure, has not been fully formalized yet. This article proposes an ontology of the main notions of the concepts associated to knowledge acquisition in this framework. This ontology, beyond the clarification it brings to the involved notions, will be the support of a software architecture for implementing the method for knowledge acquisition and problem formulation.