Appropriate use of a CAS in the teaching and learning of mathematics

If the use of a computer algebra system (CAS) is to be meaningful and have an impact on students, then it must be grounded in good pedagogy and have some clearly defined goals. It is the authors' belief that an important goal for teaching mathematics with the CAS is that courses be designed so that students can become active participants in their learning experience, planning the problem-solving strategies and carrying them out. The CAS becomes an important tool and a partner in this learning process. To this end, here the authors' have linked the use of the CAS to an existing classification scheme for Mathematical Tasks, called the MATH Taxonomy, and illustrated, through concrete examples, how the goals of teaching and learning of mathematics can be set using this classification together with the CAS.     

Multiply Charged Anions,Maximum Charge Acceptance,and Higher Electron Affinities of Molecules,Superatoms,and ClustersSCI北大核心CSCD

The addition of electrons to form gas-phase multiply charged anions (MCAs) normally requires sophisticated experiments or calculations.In this work, the factors stabilizing the MCAs, the maximum electron uptake of gas-phase molecules, X, and the electronic stability of MCAs X^Q-, are discussed. The drawbacks encountered when applying computational and/or conceptual density functional theory (DFT) to MCAs are highlighted. We develop and test a different model based on the valence-state concept. As in DFT, the electronic energy, E(N, v_ex), is a continuous function of the average electron number, N, and the external potential, v_ex, of the nuclei. The valence-state-parabola is a second-order polynomial that allows extending E(N, v_ex) to dianions and higher MCAs. The model expresses the maximum electron acceptance, Q_max, and the higher electron affinities, A_Q, as simple functions of the first electron affinity, A₁, and the ionization energy, I, of the "ancestor" system. Thus, the maximum electron acceptance is Q_{max, calc} = 1 + 12A₁/7(I -A₁). The ground-state parabola model of the conceptual DFT yields approximately half of this value, and it is termed Q_{max, GS} = ${}^{1}\!\!\diagup\!\!{}_{2}\; $ + A₁/(I -A₁). A large variety of molecules are evaluated including fullerenes, metal clusters, super-pnictogens, super-halogens (OF₃), super-alkali species (OLi₃), and neutral or charged transition-metal complexes, AB_mL_n^0/+/-. The calculated second electron affinity A_{2, calc} = A₁-(7/12)(I -A₁) is linearly correlated to the literature references A_{2, lit} with a correlation coefficient R = 0.998. A₂ or A₃ values are predicted for further 24 species. The appearance sizes, n_ap^3-, of triply charged anionic clusters and fullerenes are calculated in agreement with the literature.     

化学师范生学科理解能力的培养研究:问题与对策*

新时代卓越教师培养对师范生的能力培养提出更高要求。以化学为例,对新手型教师学科理解能力进行调查和分析,结果显示新手型化学教师存在知识理解错误、本质思考不足、微观探析缺乏等问题。因此对化学师范生培养提出4个建议,即高校应加强化学师范生中学与大学专业课程的衔接,学科教学论教师应促进化学师范生主动进行学科理解,学科教学论教师应构建师范生学科理解的典型案例,科学开设相关课程保障师范生学科理解的学习空间。     

化学哲学:化学学科理解维度解构与水平提升路径

经文献分析发现在化学学科理解相关研究中出现一个共性问题,即对化学学科理解的对象认知不一,具有不同程度的差异性。基于此,通过对化学学科理解对象的文献观点分析发现,文献所述化学学科理解对象皆差异性地指向化学知识、化学史及化学哲学三大范畴,但其指向化学哲学的过程是不自觉的、不系统的。因此通过分析化学哲学本体、化学教学的理论基础及其本质、化学教学与化学哲学的“供需”关系,探讨基于化学哲学视角系统梳理化学学科理解对象的可行性、合理性及必要性。最终认为化学哲学是一个系统且具学理性的化学学科理解维度解构路径,同时也是认知主体获得深度且系统的化学学科理解的水平提升路径。     

“基于尺度再探原子结构”的教学设计与实施*

教学设计阶段首先进行原子结构学科理解研究,通过阐释如何基于原子核认识原子的构成,如何基于核外电子运动认识原子的结构这2个本原性问题,对主题大概念原子结构模型进行本原性、结构化地理解。继而从教学目标和教学思路设计、教学实施过程、学生收获、教师反思及专家评价等方面,系统地呈现了基于学科理解的“素养为本”“基于尺度再探原子结构”课堂教学的研究过程。     

结构化学和计算化学有机结合实现“1+1>2”追求理解的学习

针对结构化学和计算化学的课程特点和学生学习两门课时的学情分析,提出了结构化学和计算化学在授课过程中有机结合、相互渗透,实现“1+1>2”的教学效果和追求理解的学习,为学生理解结构化学的抽象概念和理论以及理解计算化学的基础知识提供一种很好的学习方法,也为教师提供一种很好的教学策略。     

基于化学学科理解的“化学平衡常数”教学设计与实施研究*

基于化学学科理解,凝练了化学平衡主题的学科本原性问题,抽提了认识视角,建构了概念的层级结构。从教学目标和教学思路、教学实施、学生收获、教师反思及专家评价等方面,系统呈现了基于化学学科理解的“素养为本”的课堂教学研究过程。     

The Process Analytical Technology initiative and multivariate process analysis, monitoring and control

Process analytical technology is an essential step forward in pharmaceutical industry. Real-time analyzers will provide timely data on quality properties. This information combined with process data (temperatures, flow rates, pressure readings) collected in real time can become a powerful tool for this industry, for process understanding, process and quality monitoring, abnormal situation detection and for improving product quality and process reliability. A very important tool for this achievement is the multivariate analysis. Dr. Theodora Kourti is Research Manager in the McMaster Advanced Control Consortium (MACC) and Adjunct Professor in the Chemical Engineering Department at McMaster University. She is the co-recipient of the 2003 University – Industry Synergy Award for Innovation, given by the Natural Science & Engineering Research Council of Canada. Dr. Kourti has been working on Multivariate Statistical Methods for Process and Product Improvement and Abnormal Situation Detection in Process Industries since 1992 and has been involved in more than 80 major industrial applications in North America and Europe. These are either off-line or real-time applications for batch and continuous processes, in diverse industries such as Chemicals, Pharmaceuticals, Semiconductor, Mining, Pulp and Paper, Petrochemicals, Photographic and Steel Industry. She has published extensively in this area and has provided training for numerous industrial practitioners.