Learning Through Activity – Basic research on mathematical cognition

Simon and colleagues propose a line of pure basic research in what is fundamentally an applied domain, mathematics education. Learning Through Activity (LTA) has all the advantages and many of the disadvantages that a pure theory in an applied domain is likely to have. The seven papers in this special issue aptly demonstrate many of the advantages. An additional advantage is that explicating the theory, as they do, raises many important questions and issues. In this commentary, I discuss some of these questions and issues concerning both, the pure research and its potential applicability to real classrooms.     

播种化学梦铸造科学魂——西北大学化学科普实验室的实践与反思

Under the background of college entrance examination reform, it becomes imperative to improve the students' interest in chemistry. During the effort to investigate how to present the chemistry knowledge, to cultivate and promote students' interest and professional attitude towards chemistry, we developed the public science education laboratory of College of Chemistry and Materials Science, Northwest University. In the current paper, we introduced the background of setting-up, the missions and targets of the laboratory, as well discussed the construction, evaluation systems and prospection of the laboratory.     

Empirical reconstruction of learning progressions based on teachers’ tagging of didactic metadata

In their enactment of the curriculum, teachers have a substantial role as instructional designers. Accordingly, any evaluation of the progression of students’ learning should first be concerned with the pedagogical intentions of the teacher. In this article we present a method for reconstructing teachers’ implicit and tacit considerations in their selection, sequencing and enactment of tasks. Two 11^th grade teachers tagged all of the tasks that comprised a 5-week learning progression. Tagging consisted of assigning values to prescribed categories of metadata. Visual representations of the metadata revealed patterns in the tagged progressions, and allowed the teachers to reflect upon these patterns. Both teachers, though guided by very different didactical considerations, validated that many of their explicit and implicit intentions were revealed in the representations of the progressions. Furthermore, both teachers had the opportunity to reflect on tacit aspects of their instructional design that they were not previously aware of.     

多元教学模式在分析化学教学中的应用探索

构建了以培养学生主动学习为中心,以能力提升为核心的分析化学多元教学模式,并探索了适应多元教学模式的学业评价机制的建立。     

LAHS: A novel harmony search algorithm based on learning automata

This study presents a learning automata-based harmony search (LAHS) for unconstrained optimization of continuous problems. The harmony search (HS) algorithm performance strongly depends on the fine tuning of its parameters, including the harmony consideration rate (HMCR), pitch adjustment rate (PAR) and bandwidth (bw). Inspired by the spur-in-time responses in the musical improvisation process, learning capabilities are employed in the HS to select these parameters based on spontaneous reactions. An extensive numerical investigation is conducted on several well-known test functions, and the results are compared with the HS algorithm and its prominent variants, including the improved harmony search (IHS), global-best harmony search (GHS) and self-adaptive global-best harmony search (SGHS). The numerical results indicate that the LAHS is more efficient in finding optimum solutions and outperforms the existing HS algorithm variants.     

超高温(200-250 ℃)聚合物电解质膜燃料电池的机遇与挑战

低温质子交换膜燃料电池的商业化受到高纯度氢气制取、储存、运输及加注的制约。将燃料电池工作温度提高到200-250 ℃可显著提高电极动力学,提高对一氧化碳等杂质气体的耐受性,降低氢气制取成本,简化水和热管理,为燃料电池提供更多燃料选择,使得高温质子交换膜燃料电池有望实现原位甲醇重整制氢系统与燃料电池系统的无温差耦合,同时较高的运行温度为直接甲醇燃料电池和非贵金属催化剂替代铂基催化剂提供了有利条件。但超高温（200-250 ℃）聚合物电解质膜燃料电池的发展依然面临着艰巨的挑战,为促进超高温聚合物电解质膜燃料电池的发展,本文将系统总结近年的相关进展,探讨超高温聚合物电解质膜燃料电池面临的机遇与挑战。     

Adjusting learning motivation to promote cooperation

An evolutionary prisoner’s dilemma game with players adjusting their learning motivation is studied. At each time step, each player can adjust his/her learning motivation according to the difference between the current payoff and payoff aspiration. Greater payoff aspiration means stronger learning motivation, and vice versa. We find that the density of cooperation in a spatial prisoner’s dilemma game is enhanced when the learning motivation mechanism is considered. Meanwhile, we show that proper noise can not only induce the highest cooperation level but also can maintain the cooperation phenomenon even though there is more temptation to defect.     

学习理论中基于负相关序列的样本误差估计

给定数据(x1,y1),(x2,y2),…,(xm,ym),考虑一般的损失函数ψ(y-f(x))下,当ψ(z)连续及ξ1=ψ(y1-f(x1)),ξ2=ψ(y2-f(x2)),…,ξm=ψ(ym-f(xm))是一个负相关序列时,本文研究了样本误差估计问题.     

Learning Electricity with NIELS: Thinking with Electrons and Thinking in Levels

Electricity is regarded as one of the most challenging topics for students of all ages. Several researchers have suggested that na?ve misconceptions about electricity stem from a deep incommensurability (Slotta and Chi 2006; Chi 2005) or incompatibility (Chi et al. 1994) between na?ve and expert knowledge structures. In this paper we argue that adopting an emergent levels-based perspective as proposed by Wilensky and Resnick (1999), allows us to reconceive commonly noted misconceptions in electricity as behavioral evidences of “slippage between levels,” i.e., these misconceptions appear when otherwise productive knowledge elements are sometimes activated inappropriately due to certain macro-level phenomenological cues only. We then introduce NIELS (NetLogo Investigations In Electromagnetism), a curriculum of emergent multi-agent-based computational models. NIELS models represent phenomena such as electric current and resistance as emergent from simple, body-syntonic interactions between electrons and other charges in a circuit. We discuss results from a pilot implementation of NIELS in an undergraduate physics course, that highlight the ability of an emergent levels-based approach to provide students with a deep, expert-like understanding of the relevant phenomena by bootstrapping, rather than discarding their existing repertoire of intuitive knowledge.

Comments on “A note on minimizing maximum lateness in an m-machine scheduling problem with a learning effect”

The purpose of this paper is to point out that if there are some machines that do not process any job then the mathematical programming model provided by Eren [T. Eren, A note on minimizing maximum lateness in an m-machine scheduling problem with a learning effect, Applied Mathematics and Computation 209 (2009) 186-190] may not be a valid one. A simple way to fix this problem is given. Furthermore, based on the idea of Eren’s model, a general mathematical programming model is proposed.