中学科学教材中的知识表征：概念意义分形视角 pdf epub mobi txt 电子书 下载 2025

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• 知识表征
• 概念意义
• 分形
• 科学教育
• 中学科学
• 教材分析
• 认知科学
• 课程与教学
• 科学概念
• 教育研究

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出版社： 科学出版社

ISBN：9787030498755

商品编码：29914463302

丛书名： 中学科学教材中的知识表征--概念意义分形视角

出版时间：2016-09-01

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中学科学教材中的知识表征：概念意义分形视角
	定价	78.00
	出版社	科学出版社
	版次	1
	出版时间	2016年09月
	开本	16
	作者	赵文超
	装帧	平装
	页数	268
	字数	300
	ISBN编码	9787030498755

目录
Contents
序前言
Preface
Chapter 1 Introduction 1
1.1 A Brief Introduction to Ideational Fractals 1
1.2 Background of the Study 3
1.3 Objectives of the Study 7
1.4 Methodology and Data Collection 9
1.5 Terminology 13
1.6 Organization of the Book 18
Chapter 2 Literature Review 21
2.1 Linguistic Studies on SD 21
2.2 Multimodal Studies on SD 36
2.3 Interpretations of Knowle 45
2.4 Summary 54
Chapter 3 Theoretical Framework 56
3.1 The Framework for Analyzing Knowle Representation 57
3.2 SFL’s Multidimensional Interpretation of Language 60
3.3 SFL’s Exposition of Ideational Fractals 67
3.4 Semiotic Integration and Inter-semiotic Ideational Fractals 73
3.5 Martin’s Systemic Functional Exposition of Genre 80
3.6 Summary 82
Chapter 4 Clause Complexing in Knowle Representation 84
4.1 The Symbolic Representation of ICCs 84
4.2 The Structuring of OEMICCs 87
4.3 The Structuring of PMICCs 113
4.4 Summary 127
Chapter 5 Image-language Integrating in Knowle Representation 131
5.1 Identification of the Visual and Verbal Resources 131
5.2 The Integration of Images with Captions 140
5.3 The Integration of Images with Labels and Glosses 160
5.4 Summary 169
Chapter 6 Genre Complexing in Knowle Representation 171
6.1 AnAccount of the Genres Involved 171
6.2 Genre Complexing via Extension 173
6.3 Genre Complexing via Elaboration 185
6.4 Genre Complexing via Enhancement 197
6.5 Summary 210
Chapter 7 Conclusion 212
7.1 Major Findings of the Current Study 212
7.2 Significance of the Current Study 216
7.3 Limitations and Suggestions for Future Research 218
Appendices 220
References 229
List of Tables
Table 1.1 TheAmerican MSSTs used for the current study 10
Table 1.2 Statistics about the textbook data 12
Table 2.1 Key foci of dialogue between code theory and SFL(Martin & Maton, 2013: 1) 50
Table 3.1 Semiotic dimensions—type, relation, and orders (values) (after Matthiessen et al., 2010: 191) 61
Table 3.2 Modes of meaning and modes of expression (Matthiessen, 2007c: 778) 62
Table 4.1 Basic types of clause complex (Halliday & Matthiessen, 2004: 380) 85
Table 4.2 The distribution of the six types of OEMICCs 88
Table 4.3 The uses of the top 9 favored structuring patterns of OEMICCs 112
Table 4.4 The distribution of the four types of PMICCs 115
Table 4.5 The uses of the top 10 favored structuring patterns of PMICCs 126
Table 4.6 The distribution of the ICCs in the three sets of American MSSTs 127
Table 4.7 The frequencies of the logico-semantic relations manifested by the ICCs concerned in the three sets of MSSTs 129
Table 5.1 The distribution of the captioned visual images in the textbookdata 134
Table 5.2 The distribution of the image-caption relations in the textbook data 141
List of Figures
Figure 1.1 Vertical discourse as complementarity and cline (Martin, 2011b: 9) 17
Figure 3.1 An SFL-oriented framework for analyzing knowle representation 57
Figure 3.2 The stratal organization of context and language in terms of metaredundancy (after Martin, 2008: 32) 64
Figure 3.3 Realization in relation to instantiation (all strata instantiate) (Martin, 2010: 22) 67
Figure 3.4 Ideational fractals in different semantic environments (Halliday & Matthiessen, 1999: 223) 68
Figure 3.5 Acline of integration in relation to intermodality(Matthiessen, 2009a: 16) 76
Figure 4.1 The categorization of the OEMICCs in the three sets ofAmerican MSSTs 87
Figure 4.2 The distributions of OEMICCs in the three science subjects 91
Figure 4.3 The categorization of the PMICCs in the three sets ofAmerican MSSTs 114
Figure 5.1 The densities of each category of the visual images (in terms of type) in the three science subjects 135
Figure 5.2 The densities of each category of the visual images (in terms of function) in the three science subjects 136
Figure 5.3 A case of image-language integrating with verbal resources identified (Biggs & Zike, 2005: 77) 138
Figure 5.4 An example of captions and sub-captions comprising two parts (Trefil et al., 2007a:194) 140
Figure 5.5 The proportions of the elaborating cases of image-caption integrating in the three science subjects 142
Figure 5.6 The proportions of exposition to elaboration 143
Figure 5.7 An example of image-caption exposition for demonstrating entities (Horton et al., 2005: 27) 144
Figure 5.8 An example of image-caption exposition for demonstrating processes (Ezrailson et al., 2005b: 16) 144
Figure 5.9 The proportions of exemplification to elaboration 145
Figure 5.10 A case of exemplifying a categor y of entities in the image (Eddleman, 2007: 326) 145
Figure 5.11 A case of exemplifying a theoretical thesis in the image (Trefil et al., 2007c: 45) 146
Figure 5.12 The proportions of clarification to elaboration 148
Figure 5.13 A phrasal caption clarified by visual images (from Hsu , 2007: 262) 148
Figure 5.14 A hybrid image clarifying a verbal caption (Trefil et al., 2007b: 197) 149
Figure 5.15 The proportions of the extending cases of image-caption integrating in the three science subjects 150
Figure 5.16 An example of image-caption integrating through augmentation (Trefil et al., 2007a: 119) 151
Figure 5.17 An integrating example with caption augmented by image (Eddleman , 2007: 272) 152
Figure 5.18 An example of image-caption integrating with divergence (Trefil et al., 2007c: 282) 153
Figure 5.19 The proportions of the enhancing cases of image-caption integrating in the three science subjects 154
Figure 5.20 Two examples of image-caption integrating through causal enhancement 155
Figure 5.21 An example of image-caption integrating through temporal enhancement (Trefil et al., 2007c: 457) 156
Figure 5.22 An example of image-caption integrating through the enhancement of purpose (Biggs & Zike, 2005: 16) 157
Figure 5.23 A comparison in between different science subjects 158
Figure 5.24 A comparison within the same science subject 159
Figure 5.25 An example of image-label integrating through exposition (Daniel & Zike,2005: 81) 160
Figure 5.26 An image with labels construing abstract things (Lillie et al.,2005:83) 161
Figure 5.27 Examples of image-label integrating through exemplification (Trefil et al., 2007c: 45) 162
Figure 5.28 An example of image-label integrating through spatial enhancement (Snyder & Zike, 2007: 19) 163
Figure 5.29 Examples of image-gloss integrating through elaboration and extension 165
Figure 5.30 Examples of image-gloss integrating through enhancement (Feather Jr.& Zike,2005a:160) 168
Figure 6.1 The implication sequence of the dissolution of ionic compounds 180
Figure 6.2 The implication sequence of the dissolution of molecular compounds 180
Figure 6.3 The implication sequence of the formation of a rotating system 183
Figure 6.4 The conditional implication sequence of the formation of hurricanes 184
Figure 6.5 The implication sequence of the promotion of density 194
Figure 6.6 The implication sequence of how the change of an object’s density is related to its floating and sinking in a fluid 196
Figure 6.7 The elaborating mode of genre complexing realized in Text 9 197
Figure 6.8 The reasoning processes concerning the danger of atherosclerosis 200

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Chapter 1
Introduction
In modern schooling contexts, pedagogic discourse, verbalized or visualized, is a crucial channel through which students acquire disciplinary knowle. Textbooks, as one major type of pedagogic discourse, have been investigated in the linguistic field from different perspectives. However, how knowle is represented in them remains an issue calling for answers. Intended to be one additional contribution to the solution of the issue, the study in this book looks into the pedagogic scientific discourse in middle school science textbooks (henceforth MSSTs), proposing that knowle representation therein is a semantic enterprise accomplished synergistically through the work of lexicogrammatical structures, visual representations, and genres. Specifically, the current study purports to bring out how knowle in three sets of American MSSTs is represented through clause complexing, image-language integrating, and genre complexing. As the first step of the study, the present chapter is designed to make explicit the background, the objectives, the methodology, and the data collection of the research, followed by a specification of the term ‘scientific discourse’ (henceforth SD) and the organization of the entire book. However, since the entire study is carried out from the perspective of ideational fractals, a term which is not very familiar to researchers in the linguistic field, the present chapter will first provide a brief introduction to the term.
1.1 A Brief Introduction to Ideational Fractals
In this book, the term of ideational fractals is derived from systemic functional linguistics (henceforth SFL). Within the term, the notion of fractal originates from mathematician Mandelbrot’s work on self-similarity in material systems (see Matthiessen et al., 2010). Etymologically, the word, coined by Mandelbrot, comes from the Latin adjective fractus, which has the same root as fraction and fragment and means irregular or fragmented (see Mandelbrot, 1977: 4). The mathematician used the word to describe many of the seemingly complex forms found in nature, for example, the forms of coastlines, snowflakes, and clouds. To Mandelbrot (1977), many fractal forms are of the feature of self-similarity, where self-similarity is taken as a scale-invariant property, meaning that “the object or phenomenon under consideration is found to remain (locally) identical to itself after application of a dilatation or contraction” (Nottale, 1993: 40).
As a theoretical term,‘fractal’ in SFL is used to refer to“a general semantic pattern that is manifested throughout the semantic and lexicogrammatical systems in different environments” (Matthiessen et al., 2010: 100). This means that SFL has borrowed the notion of ‘fractal’ from Mandelbrot’s work on self-similarity in material systems for the purpose of characterizing self-semilarity in semiotic systems. According to Matthiessen et al. (2010), fractals in the social semiotic system of language operate within all metafunctions.
Within the interpersonal metafunction, fractals manifest themselves mainly in the semantic environments occupied by the resources in the system of MODAL ASSESSEMENT (cf. Matthiessen et al., 2010: 100). Generally, these resources are the modal adjuncts (including mood adjuncts and comment adjuncts) operating in such grammatical domains as clauses and nominal groups (see Halliday & Matthiessen, 2004: 608-612). Within the textual metafunction, the fractals discerned are textual ones. Their manifestation is done by virtue of the systems of THEME and INFORMATION, in environments such as whole texts, rhetorical paragraphs, the clause nexus, the clause, the nominal group and the verbal group (cf.Matthiessen et al., 2010: 100).
Of particular relevance to the current study are the fractals identified in the ideational metafunction. These fractals are referred to in this book as ideational fractals. According to Matthiessen et al. (2010), these fractals are actually the logico-semantic types of projection and expansion, and their manifestation environments include those of whole texts and rhetorical paragraphs within texts, the tactic environment of a clause nexus, the transitivity environment of a clause, and the modification environment of a nominal group. Being ideational fractals, “expansion and projection are also manifested as logico-semantic relations that link clauses together to form clause complexes” (Halliday & Matthiessen, 2004: 367). The current study approaches knowle representation in science textbooks from the perspective of ideational fractals, arguing that ideational fractals are not only manifested in such semantic environments as created by clauses and clause complexes, but are also discernible in the semantic environments created by image-language integrating and genre complexing. Specifically, this study holds that the ideational fractals manifested in clause complexes, i.e. the logico-semantic relations, also obtain in the semantic environments created by image-language integrating and genre complexing.
1.2 Background of the Study
The current book investigates knowle representation in MSSTs. Such an investigation is motivated for both academic and practical reasons. Academically, the investigation is intended to add to people’s understanding of the knowle-representing resources, fashions, and patterns in MSSTs. Practically, the investigation is intended to provide implications for language educators, science educators, and science textbook writers. These motivations are derived from a consideration of the nature of learning science and a critical review of the previous studies on SD.
As is observable in modern schooling contexts, science is an indispensable component of middle school curriculum. It is not only a crucial resort for developing school students’ scientific literacy, but also one of the critical channels for expanding their knowle about the world. In respect of science education, there is an increasing awareness that students’ learning of science is in essence acquisition of a specialized language (cf. Christie, 1989; Halliday, 1993a; Wellington & Osborne, 2001; Schleppegrell, 2004). For this reason, Norris and Phillips (2003) insist that knowle and understanding of scientific language is critical to students’ development of scientific literacy in both its “fundamental” sense (i.e. ability to read and write science text) and “derived” sense (i.e. knowleability about science).
In SFL, knowle is recognized as the same thing as meaning and language is treated as a primary semiotic resource for knowle-representing or meaning-making (cf. Halliday & Matthiessen, 1999). This recognition suggests that unpacking the linguistic organization and configuration in MSSTs will not only promote science teachers’ understanding of the language demands imposed on students by different levels of scientific knowle, but will also give a boost to science learners’ development of scientific literacy and their perception of the knowle representation in this special type of SD.
The academic field of linguistics abounds with researches aimed at unpacking the linguistic organization and configuration in SD, no matter whether the SD is from the “field of production” or from the “recontextualizing field” (cf. Bernstein, 2000). When the SD is from the former field, it is generally in the forms of research articles and academic theses or dissertations. When the SD is from the latter field, it is typically in the form of science textbooks and scientific knowle developed in the former field gets systematically reformulated for pedagogic purposes. Whatever the forms, SD has been investigated with many inspiring results.
First, many lexicogrammatical features have been uncovered both within various forms of knowle-producing SD and within knowle-recontextualizing pedagogic textbooks of different levels. Notably, the lexicogrammatical researches from the field of SFL not only reveal a lot about the evolution and syndromes of scientific English, but also disclose a great deal about the Attic (i.e. the metaphorical) and the Doric (i.e. the congruent) styles of meaning in specific scientific texts (see e.g. Halliday, 1993b, 2004a, 1998a, 1998b, 1999, 2004b). With these researches, the development of the language of science is known to be functionally driven by the demands of constructing technical taxonomies and nominalizing processes (cf. Halliday, 1993b, 2004a; Wignell et al., 1993), and the discourse of science is demonstrated to be distinctive because of its own specialized format of representing and explaining the phenomena in the natural world (see e.g. Halliday, 1993b, 1998a; Martin, 1993a; Wignell et al., 1993; Veel, 1998). Moreover, SFL-oriented researches display the fact that the modes of meaning, metaphorical or congruent, have bearings on school students’learning of disciplinary knowle (cf. Halliday, 1993c, 2004a, 1998a, 1998b; Sriniwass, 2010).
The lexicogrammatical features uncovered also include those that perform “appraisal” (Martin & White, 2005) functions or “interpersonal” (Hyland, 2005b) functions. In this regard, the researches are usually focused on the SD produced for academic purposes. Thus, they can be considered as ESP (English for specific purposes) studies or more exactly, EAP (English for academic purposes) studies. These studies are contributive for their discoveries of the meaning-making strategies that are deployed either to exhibit authorial presence and reader sensibility, or to realize professional engagement, effective argumentation, and community-specific alignment. For a glimpse of the representative contributions made by these studies, as will be made clear in Chapter 2, a convenient but informative way is to refer to Hyland (1994, 1996a, 1996b, 1998a, 1998b, 2000, 2001, 2002a, 2002b, 2002c, 2003, 2005a, 2005b, 2008a, 2010a), Moore (2002), and Hyland and Tse (2005).
With regard to the above lexicogrammatical researches, it has to be noted that school science textbooks remain a type of SD short of systematic investigations in comparison with the massive explorations of SD in various academic forms. In particular, how multiple ranking clauses in MSSTs are integrated for the forming of intricate clause complexes (henceforth ICCs) remains an issue rarely accounted for. Given the critical role of congruent clause complexing in apprenticing middle school students into the metaphorical ways of knowle representation (cf. Sriniwass, 2010), and the importance of science textbooks in apprenticing middle school students into scientific ways of reading, writing, thinking, and reasoning, it is certain that a study of the structuring of ICCs in MSSTs will benefit both native and non-native science learners. For example, it will boost science learners’ consciousness of the range of clause-complexing possibilities available to them when they are engaged in disciplinary writing. Besides, it is thought that those devoted to science-teaching and textbook-writing will also benefit from the findings, considering their goals in developing students’ scientific literacy.
Second, many genre analyses have been done to SD both in academic forms (see e.g. Swales, 1993[1990], 2004; Bhatia, 1993, 2004; Kanoksilapatham, 2005; Soler-Monreal et al., 2011) and in textbook forms (see e.g. Martin, 1993c; Veel, 1997; Rose, 1997; Martin & Rose, 2008). Owing to those genre analyses devoted to academic SD, much is known about how different academic genres (e.g. Abstracts, Introductions, Discussions, and Results) are rhetorically organized in terms of moves and steps. Owing to those genre analyses devoted to science textbooks, much is known about the constituent genres in pedagogic SD. However, it has to be kept in mind that much less is revealed about how genres in a certain type of SD are related to each other. To science teachers, this is no doubt a barrier to familiarizing science learners with the macro-structures of subject-specific knowle. To science learners, this is also a barrier to developing a clear picture of the knowle-representing fashions and patterns in school science. For these reasons, the current study, which takes the genre complexing in three sets of American MSSTs as one of its major concerns, attempts to be conducive to overcoming the barrier, so that science learners can be kept aware of not only the range of genres in science textbooks, but also the ways in which the genres are logically sequenced and meaningfully integrated.
Modern SD does not merely depend on linguistic resources for knowle representation. Non-linguistic semiotic resources are equally indispensable, as strongly suggested by the American MSSTs used for the current study. Therefore, their role in representing knowle in SD should be given due consideration in the studies such as the current one. In fact, SD is a productive site for studies on knowle representation from the perspective of multimodality.
The existing multimodal studies on SD all put a high premium on the role of non-verbal semiotic resources in meaning-making or knowle-representing. When interpreting the non-verbal meaning-making mechanisms and the inter-semiotic interactions, most of them tend to draw insights from the theoretic expositions on language (see e.g. Lemke, 1998; Royce, 2002; O’Halloran, 2003; Unsworth, 2006a, 2006b; Baldry & Thibault, 2006; Unsworth & Cléirigh, 2009; Liu & Owyong, 2011). Moreover, it is recognized in these studies that SD has evolved to rely on the integration of both verbal and visual resources to represent knowle (see e.g. Lemke, 1998; Baldry & Thibault, 2006). As a consequence, developing analytical models for the interpretation of inter-semiotic interactions are always one of their major attempts (see e.g. Royce, 2002; Unsworth, 2006a, 2006b; Unsworth & Cléirigh, 2009), just as displayed by the studies on other kinds of multimodal discourse (see e.g. Martinec & Salway, 2005; O’Halloran, 2005, 2008a; Martin & Rose, 2007; Liu & O’Halloran, 2009; Chan, 2011).
However, it has to be pointed out that the inter-semiotic interactions in science textbooks deserve more attention and that more descriptive and explanatory work still
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科技前沿：人工智能驱动的未来城市构建与可持续发展 本书简介 在21世纪的浪潮中，城市正以前所未有的速度扩张与演变，随之而来的是能源消耗、交通拥堵、环境污染等一系列复杂挑战。本书《科技前沿：人工智能驱动的未来城市构建与可持续发展》汇集了全球顶尖的城市规划专家、计算机科学家、环境工程师和政策制定者的智慧，深入探讨了如何利用前沿人工智能（AI）技术，从根本上重塑城市的面貌与运行机制，实现真正意义上的可持续发展。 本书并非专注于单一技术或某一城市案例，而是提供了一个宏大且具有操作性的框架，用以理解和实施“智慧城市”的下一代范式。我们相信，未来的城市不再是钢筋水泥的集合体，而是由海量数据驱动、由智能系统协调的、具有自我优化能力的生命有机体。 核心议题与内容结构 全书共分为六个核心部分，旨在构建一个从理论基础到实际应用的完整知识体系。 第一部分：智慧城市的基础：数据、连接与智能感知 本部分首先为读者奠定了理解未来城市运行的基础。我们详尽阐述了支撑智慧城市运转的底层技术栈：物联网（IoT）的泛在部署、5G/6G网络的超低延迟通信，以及边缘计算在城市级决策中的关键作用。 重点章节包括： 城市级数据治理的挑战与范式转型： 探讨如何安全、高效地汇集交通、能源、公共安全等异构数据流，并建立统一的语义模型。 新型传感器网络与环境建模： 分析高精度LiDAR、空气质量传感器阵列在城市尺度上构建实时三维数字孪生体的可行性与局限性。 去中心化身份验证与数据安全： 考察区块链技术在保障市民隐私和城市基础设施安全方面的应用潜力。 第二部分：AI赋能的城市交通流优化 交通是城市活力的命脉，也是效率的瓶颈。本部分聚焦于AI如何彻底改变交通管理。我们超越了传统的信号灯优化，深入研究了基于深度强化学习（DRL）的自适应交通控制系统。 动态路径规划与需求预测： 阐述如何利用LSTM和Transformer模型对城市OD（起讫点）数据进行高精度预测，从而实现对公共交通和共享出行服务的动态调度。 自动驾驶生态系统的融合挑战： 探讨L4/L5级别自动驾驶车辆与现有城市基础设施（如非结构化道路使用者、临时施工区）的交互模型与安全协议设计。 多模态出行集成平台（MaaS）的AI引擎： 分析如何通过个性化推荐算法，激励市民从私家车转向更可持续的出行方式。 第三部分：能源与资源管理的智能化转型 可持续发展的核心在于能源效率和资源循环。本书将AI视为实现城市能源系统的去碳化与弹性的关键工具。 智能电网的预测性维护与负荷平衡： 详细介绍了基于概率建模和生成对抗网络（GANs）的极端天气下的电力需求预测方法，以及分布式能源（如屋顶太阳能）并网的优化策略。 建筑能耗的AI驱动优化： 深入探讨了楼宇管理系统（BMS）如何通过实时学习室内外环境参数，实现暖通空调（HVAC）系统的能耗最小化，而不牺牲居住舒适度。 城市水务系统的泄漏检测与质量控制： 考察了利用声学传感器数据和异常检测算法，提前预警供水管网的潜在故障点。 第四部分：韧性城市与公共安全：AI的伦理与实践 构建面向未来的城市，必须具备抵御突发事件和自然灾害的韧性。本部分侧重于AI在危机管理中的应用，同时强调了技术应用中的伦理边界。 灾害响应与资源分配优化： 分析了在地震、洪水等场景下，如何利用实时卫星图像和无人机数据，结合图神经网络（GNNs）快速评估受损情况，并优化应急物资的投放路线。 预测性警务与社会公平性： 坦诚地讨论了利用AI进行犯罪风险评估的潜力，并着重分析了模型偏见（Bias）的来源及其对弱势群体的潜在负面影响，提出了可解释性AI（XAI）在公共安全领域的应用要求。 城市数字孪生体在应急推演中的作用： 展示了高保真数字模型如何被用于模拟复杂的人群疏散和基础设施失效情景。 第五部分：城市治理的数字化与公民参与 未来的城市治理需要从自上而下的控制转向多方协同的生态系统。 AI辅助的政策制定与模拟： 探讨了如何使用复杂的系统动力学模型，结合机器学习，评估不同城市规划决策（如税收调整、绿地分配）的长期社会经济后果。 增强公民参与的平台设计： 介绍了基于自然语言处理（NLP）的工具，用于高效分析市民反馈、识别关键诉求，并将其转化为可执行的市政任务。 跨部门协作的AI集成框架： 提出了一个统一的治理框架，确保交通、环境、卫生等不同市政部门的智能系统能够无缝协同工作。 第六部分：展望未来：超越智慧城市——共生城市 本书的最后一部分放眼未来十年，探讨AI技术可能带来的颠覆性变革，以及我们应该如何主动引导这些变革，迈向一个更具人文关怀的“共生城市”。 人机共存的城市空间设计： 讨论了随着机器人技术和增强现实（AR）的普及，物理空间与数字信息如何更紧密地交织在一起。 面向“零碳零浪费”的循环经济路径： 分析了AI如何优化城市材料流，实现从线性到完全循环的经济转变。 可持续发展的长效指标体系： 提出了一套超越传统GDP和碳排放指标的、以人类福祉和生态健康为核心的未来城市评估体系。 本书特色 本书的独特之处在于其强大的跨学科整合能力。它不仅提供了深厚的技术细节（如特定算法的性能分析），更着重于在复杂的现实约束（如政治阻力、既有基础设施的限制、社会公平性）下，如何进行系统性的工程落地。作者们力求避免技术乌托邦式的空谈，而是提供一套基于现实数据、经过严格验证的、面向大规模应用的解决方案集。 《科技前沿：人工智能驱动的未来城市构建与可持续发展》是城市管理者、规划师、基础设施开发者、AI研究人员以及关注未来城市形态的公众的必备参考书。它描绘了一幅清晰的蓝图：一个更高效、更安全、更具韧性，并最终实现人类与环境和谐共生的未来城市愿景。

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当我看到“中学科学教材”这个具体的应用场景时，我更加期待了。科学知识的学习，往往需要学生掌握大量的概念、原理和定律，并且理解它们之间的复杂联系。而“分形视角”和“概念意义”的结合，似乎为解决这一难题提供了新的思路。我不禁想象，这本书是否在论述，如何通过设计具有分形特征的教材内容，来帮助中学生更好地理解科学知识。例如，将一个复杂的科学概念，分解成若干个具有相似逻辑结构的小概念，每个小概念又可以进一步细化，但始终保持着与整体的内在联系。这种方式，会不会让学生在学习过程中，既能把握整体框架，又能深入理解细节，从而避免“只见树木不见森林”的困境？此外，“概念意义”的强调，也意味着这本书可能关注的不仅仅是知识的结构，更是知识背后的深层含义和应用价值，这对于培养学生的科学素养至关重要。

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这本书的书名，尤其是“分形视角”的引入，让我对其中关于“概念意义”的阐述产生了强烈的好奇。教育的本质是意义的传递与建构，而概念是知识的基石。如果能够用分形这样一种能够揭示复杂系统内在秩序的工具来审视概念的生成、发展和相互关系，那将是多么富有洞察力的视角。我猜想，作者可能是在探讨，如何让抽象的概念在学生头脑中形成一种“有生命力”的结构，这种结构能够随着学习的深入而不断细化、延展，如同分形图案一样，每一个局部都蕴含着整体的基因。我甚至联想到，这或许可以为设计更具启发性的教学案例、更有效的学习路径提供理论支持。比如，如何通过类比、隐喻等方式，让学生看到不同概念之间的“自相似性”，从而加速理解和迁移。这本书的出现，似乎为我们提供了一种全新的工具和思维方式，去重新审视和设计教育内容，让知识的表征不再是枯燥的条条框框，而是生动、立体的知识森林。

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一本值得细细品味的著作，即使我并非其核心读者群体，也被其书名所吸引，并在翻阅过程中获得了不少启发。首先，它传递出的“知识表征”这一概念，本身就极具深度与广度。在当下信息爆炸的时代，如何有效地组织、呈现和传递知识，是教育领域乃至社会发展都面临的挑战。这本书似乎在探索这一问题的根本，通过“概念意义”的梳理，试图构建一种更具内涵和生命力的知识图谱。而“分形视角”，更是将这一探索提升到了一个新的高度。分形，这种在自然界中随处可见的自相似结构，在复杂系统中展现出惊人的规律性。如果能将这种思想引入到教育知识的表征中，那将是对传统教学模式的颠覆性创新。我设想，这本书或许在论证如何让知识的内在结构像分形一样，既有宏观的整体性，又能层层深入，展现出细腻的局部特征，从而帮助学习者构建更扎实、更融会贯通的知识体系。这种跨学科的思考方式，本身就足够吸引人。

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这本书的标题，特别是“分形视角”的出现，着实让我眼前一亮。它暗示了一种不同于传统知识呈现方式的探索。我推测，作者可能试图利用分形几何中“整体与部分的自相似性”这一特性，来重塑中学科学教材中的知识表征。想象一下，一个核心科学概念，可以像一个精美的分形图案，在不同的层级和尺度上，都展现出相似的规律和结构。这种表征方式，或许能够让学生在学习过程中，更容易把握知识的脉络，理解概念之间的内在联系，从而形成一个系统、深刻的知识体系。此外，对“概念意义”的关注，也表明这本书不仅仅停留在知识的结构层面，更可能深入探讨知识的深层含义、应用价值以及学生对知识的理解与建构过程。这对于提升科学教学的有效性，培养具有批判性思维和创新能力的学生，无疑具有重要的理论和实践意义。

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作为一名对教育方法论感兴趣的旁观者，这本书的书名触及了我的一些核心关切。我一直认为，科学教育的深度和广度，很大程度上取决于我们如何表征和传递科学知识。而“分形视角”这个概念，在我看来，提供了一个极具潜力的分析框架。我设想，作者可能是在探索，如何将自然界中普遍存在的“自相似性”规律，应用到科学概念的组织和呈现上。比如，一个基础的科学原理，可以像分形一样，在不同的尺度和语境下，展现出相似的逻辑和结构。这种表征方式，或许能够帮助学生更轻松地建立起不同知识点之间的联系，形成一个有机、 interconnected 的知识网络，而不是零散的知识碎片。更重要的是，“概念意义”的引入，表明这本书可能不仅仅关注知识的形式，更注重知识的内涵和价值，这对于培养学生深刻理解科学、运用科学解决实际问题具有重要意义。