Enhancing Practicing Primary School Teachers' Pedagogical Content Knowledge in Technology

This paper describes the frameworks and cognitive tools that have been developed to enhance practising teachers' pedagogical content knowledge in primary school technology education. The frameworks evolved from our research that firstly examined existing teaching practices, secondly enhanced formative interactions and thirdly enhanced summative assessment strategies. The evidence gained over the three years demonstrated how the effective use of frameworks could be utilised to enhance teacher pedagogical content knowledge (PCK). How we see learning is of prime importance in examining the development of teacher pedagogical content knowledge. A sociocultural view of learning is taken where human mental processes are situated within their historical, cultural and institutional setting. In the research project we strongly emphasised the need for teachers to build a knowledge base for teaching technology. Critical aspects identified as enhancing PCK included: negotiated intervention, planning frameworks, reflection on case studies, workshops and support in classrooms, appropriate resources, teacher agreement meetings, portfolios of student work and summative profiles. The increased PCK resulted in: enhanced teacher knowledge about technology including the nature of technology, areas of technology and specific technological knowledge, changed pedagogical approaches, enhanced teacher student interaction, refinement of appropriate learning outcomes, critical decision making, improved teacher confidence, and enhanced student learning. Seven characteristics or features of pedagogical content knowledge that we believe are important for effective teaching and learning in technology are presented. This revised version was published online in July 2006 with corrections to the Cover Date.     

Zombie Board: Board Tenure and Firm Performance

We show that board tenure exhibits an inverted U‐shaped relation with firm value and accounting performance. The quality of corporate decisions, such as M&A, financial reporting quality, and CEO compensation, also has a quadratic relation with board tenure. Our results are consistent with the interpretation that directors’ on‐the‐job learning improves firm value up to a threshold, at which point entrenchment dominates and firm performance suffers. To address endogeneity concerns, we use a sample of firms in which an outside director suffered a sudden death, and find that sudden deaths that move board tenure away from (toward) the empirically observed optimum level in the cross‐section are associated with negative (positive) announcement returns. The quality of corporate decisions also follows an inverted U‐shaped pattern in a sample of firms affected by the death of a director.     

Machine learning in individual claims reserving

Machine learning techniques make it feasible to calculate claims reserves on individual claims data. This paper illustrates how these techniques can be used by providing an explicit example in individual claims reserving.     

Learning minimum variance discrete hedging directly from the market

Option hedging is a critical risk management problem in finance. In the Black–Scholes model, it has been recognized that computing a hedging position from the sensitivity of the calibrated model option value function is inadequate in minimizing variance of the option hedge risk, as it fails to capture the model parameter dependence on the underlying price (see e.g. Coleman et al., J. Risk, 2001, 5(6), 63–89; Hull and White, J. Bank. Finance, 2017, 82, 180–190). In this paper, we demonstrate that this issue can exist generally when determining hedging position from the sensitivity of the option function, either calibrated from a parametric model from current option prices or estimated nonparametricaly from historical option prices. Consequently, the sensitivity of the estimated model option function typically does not minimize variance of the hedge risk, even instantaneously. We propose a data-driven approach to directly learn a hedging function from the market data by minimizing variance of the local hedge risk. Using the S&P 500 index daily option data for more than a decade ending in August 2015, we show that the proposed method outperforms the parametric minimum variance hedging method proposed in Hull and White [J. Bank. Finance, 2017, 82, 180–190], as well as minimum variance hedging corrective techniques based on stochastic volatility or local volatility models. Furthermore, we show that the proposed approach achieves significant gain over the implied BS delta hedging for weekly and monthly hedging.     

Forecasting U.S. money growth using economic uncertainty measures and regularisation techniques

This paper examines the out-of-sample forecasting properties of six different economic uncertainty variables for the growth of the real M2 and real M4 Divisia money series for the U.S. using monthly data. The core contention is that information on economic uncertainty improves the forecasting accuracy. We estimate vector autoregressive models using the iterated rolling-window forecasting scheme, in combination with modern regularisation techniques from the field of machine learning. Applying the Hansen-Lunde-Nason model confidence set approach under two different loss functions reveals strong evidence that uncertainty variables that are related to financial markets, the state of the macroeconomy or economic policy provide additional informational content when forecasting monetary dynamics. The use of regularisation techniques improves the forecast accuracy substantially.     

基于探索性因子分析的河南省农业旅游开发研究

农业旅游是农业与旅游业相融合的产物。河南省是旅游资源大省,同时又是农业大省,具有发展农业旅游的有利条件。文章在河南省郑州、新乡、信阳、南阳、开封、商丘等地进行调研,运用SPSS17.0对所得数据进行探索性因子分析,以了解河南省农业旅游的发展现状。结合研究结论,该文分别从强化旅游基础设施、提高硬件接待水平;构建高质量、高品位的旅游环境,提高软件接待水平;开发创意农业旅游产品,满足旅游者的多样化需求;增强旅游参与性,提高旅游体验效果;提高从业人员素质,完善旅游服务质量等方面为农业旅游活动的顺利进行提供合理化建议。     

西北地区城乡收入差距的时空分异及影响因素

目的 为准确把握市域尺度下西北地区城乡收入差距的时空演变特征,促进该区域城乡融合发展。方法 文章基于2010—2018年51个市域单元城乡居民收入比数据,综合运用核密度估计、探索性空间数据分析和空间回归模型等方法研究了西北地区城乡收入差距的时空分异及影响因素。结果 （1）西北地区城乡居民收入比由3.189下降至2.736,下降幅度为14.21%;（2）空间分布格局上形成了东西方向的“U型”特征和南北方向由北及南平滑上升的特征;（3）全局莫兰指数在波动中由0.322上升至0.358,上升幅度为11.18%;（4）空间滞后模型表明城镇化对城乡收入差距有正向影响,产业结构高级化、农业现代化和金融效率对城乡收入差距有负向影响,而经济发展虽然能够缩小城乡收入差距,但两者在计量结果上显示“U型”关系。结论 西北地区城乡收入差距在小幅波动中表现出缩小的趋势,且市域之间的差异呈现出收敛的态势;西北地区城乡收入差距在空间分布上表现出较为显著的正自相关性,且在局部地区有板块集聚特征;空间因素是西北地区缩小城乡收入差距不可忽视的重要因素。     

以开放的理念推动团队学习和创新——上海市电力公司市区供电公司团队学习新模式

企业要实现可持续发展,如何激发广大员工主动学习、团队合作以及管理创新的意识,使员工积极自觉参与公司发展,是企业必须解决的一大课题。基于上述考虑,上海市电力公司市区供电公司以"思维前线·智力风暴"人力资源开发解决方案青年设计大赛为基础,提出了供电公司团队学习新模式。文中首先对新模式内容进行了介绍,包括本次大赛的形式、内容等;接着结合相关理论,就新模式对企业团队学习、创新与可持续发展、创建和谐企业等方面产生的积极影响进行了论述。     

岭南文化嵌入性对珠三角本土企业组织学习的影响

组织学习对企业的自主创新乃至整体进化具有重大影响,而组织学习在很大程度上是嵌入一定文化环境的珠三角本土企业的组织学习不可避免地受到岭南文化嵌入性的影响,而这种影响有很大一部分是"阻碍性"的岭南文化的偏向闭锁凝滞、拙于自我创造、缺乏价值理性、排斥正统正规、忽略正式组织等局限性在珠三角本土企业组织学习的取向上留下了明显烙印,并具体反映在知识来源、知识传播、学习主体、学习幅度和学习效果等方面     

A derivatives trading recommendation system: The mid‐curve calendar spread case

Derivative traders are usually required to scan through hundreds, even thousands of possible trades on a daily basis. Up to now, not a single solution is available to aid in their job. Hence, this work is aimed to develop a trading recommendation system, and to apply this system to the so‐called Mid‐Curve Calendar Spread (MCCS) trade. To suggest that such approach is feasible, we used a list of 35 different types of MCCSs; a total of 11 predictive and 4 benchmark models. Our results suggest that linear regression with l1‐regularisation (Lasso) compared favourably to other approaches from a predictive and interpretability point of views.