结构分析法在物理教材分析中的运用

介绍了物理教学中的结构分析法的内容及方法,并运用结构分析法对初中物理“力”这一章教材进行了分析与研究。     

Understanding the dynamics of MOOC discussion forums with simulation investigation for empirical network analysis (SIENA)

This study attempts to make inferences about the mechanisms that drive network change over time. It adopts simulation investigation for empirical network analysis to examine the patterns and evolution of relationships formed in the context of a massive open online course (MOOC) discussion forum. Four network effects—homophily, reciprocity, transitivity, and preferential attachment—were tested to explain the dynamic mechanisms of interaction in the MOOC forum. Understanding the network dynamics of relationships will allow us to explore how to develop a robust peer-supported learning environment and in turn improve the online learning experience in MOOCs.     

Students' privacy concerns in learning analytics: Model development

Understanding students' privacy concerns is an essential first step toward effective privacy-enhancing practices in learning analytics (LA). In this study, we develop and validate a model to explore the students' privacy concerns (SPICE) regarding LA practice in higher education. The SPICE model considers privacy concerns as a central construct between two antecedents—perceived privacy risk and perceived privacy control, and two outcomes—trusting beliefs and non-self-disclosure behaviours. To validate the model, data through an online survey were collected, and 132 students from three Swedish universities participated in the study. Partial least square results show that the model accounts for high variance in privacy concerns, trusting beliefs, and non-self-disclosure behaviours. They also illustrate that students' perceived privacy risk is a firm predictor of their privacy concerns. The students' privacy concerns and perceived privacy risk were found to affect their non-self-disclosure behaviours. Finally, the results show that the students' perceptions of privacy control and privacy risks determine their trusting beliefs. The study results contribute to understand the relationships between students' privacy concerns, trust and non-self-disclosure behaviours in the LA context. A set of relevant implications for LA systems' design and privacy-enhancing practices' development in higher education is offered.

Practitioner notes

What is already known about this topic

• Addressing students' privacy is critical for large-scale learning analytics (LA) implementation.
• Understanding students' privacy concerns is an essential first step to developing effective privacy-enhancing practices in LA.
• Several conceptual, not empirically validated frameworks focus on ethics and privacy in LA.

What this paper adds

• The paper offers a validated model to explore the nature of students' privacy concerns in LA in higher education.
• It provides an enhanced theoretical understanding of the relationship between privacy concerns, trust and self-disclosure behaviour in the LA context of higher education.
• It offers a set of relevant implications for LA researchers and practitioners.

Implications for practice and/or policy

• Students' perceptions of privacy risks and privacy control are antecedents of students' privacy concerns, trust in the higher education institution and the willingness to share personal information.
• Enhancing students' perceptions of privacy control and reducing perceptions of privacy risks are essential for LA adoption and success.
• Contextual factors that may influence students' privacy concerns should be considered.

     

Rankings in professional men’s tennis: a rich but underutilized source of information

Abstract

Success in professional tennis is measured, at least in part, by rankings. However, there is little quantitative evidence to inform stakeholders regarding what represents the typical ranking progress of top-ranked players. The objective of this study was therefore to compare the ranking trajectories of male players whom achieved peak professional rankings in the Top 250, 175, 100, 50, 20 and 10. The 11,396 birthdates and weekly professional rankings of all players between 27 August 1973 and 31 October 2011 were collated. The peak ranks for each athlete according to their both chronological age and number of years on tour were identified and athletes were categorised into one of six career–peak ranking bands. One-way analysis of variance tests confirmed distinctive ranking trajectories, which were most pronounced among Top 10 players. The rankings of these players were statistically distinguishable following players’ second year on tour or by 17 years of age. The ranking signature of all Top 100 players emerged as significantly different to players that failed to enter the Top 100 by their fourth year on the tour. Indeed, the representation of ranking as a function of years on tour should be considered for use by tennis policy-makers in the future.     

学习分析:大学教学信息化研究与实践的新领域

随着大学教学信息化进程的不断深化与发展,如何测量、挖掘、分析与利用在学习平台中积累的大量数据,以更好地支持教学与学习,进而改善和提升教与学的质量与效能,已成为摆在大学教学信息化研究者与实践者面前的现实课题。学习分析的兴起则为解决这一难题,提供了一系列的方法、工具和手段。文章将基于国内外学者的已有研究,通过对学习分析的发展脉络的梳理,对学习分析的内涵、过程、工具和方法作较为深入的解读,并尝试从推动大学教学创新的视角,阐释学习分析对促进大学教学信息化深入发展的重要价值和深远影响。     

Toward a Usable Academic Library Web Site: A Case Study of Tried and Tested Usability Practices

Usability testing is an important element when designing useful, usable academic library Web sites. Since 2001, members of the Florida International University Libraries Web team have worked toward establishing a process that identifies user needs through usability testing. Starting with the libraries’ first Web site redesign project in 2001, the team has taken an active part in improving Web site user experience. After engaging in multiple redesign efforts, the Web team has developed a process that supports awareness of user experience through continual usability testing and feedback gathering. This article presents strategies and practices to measure Web site user experience, including classic usability testing methods (e.g., card sorting activities, focus groups, and task-based user testing), as well as the team's latest effort to assess Web site analytics and content to identify Web site usage patterns and areas of concern. A history of the Florida International University Libraries’ Web site redesign process is presented to illustrate lessons learned and best practices to facilitate future redesign and testing efforts. Taking a longitudinal look at usability testing at one institution, the study aims to inform the development of an effective strategy for user research and content management.     

Demonstrating Success: Web Analytics and Continuous Improvement

As free and low-cost Web analytics tools become more sophisticated, libraries’ approach to user analysis can become more nuanced and precise. Tracking appropriate metrics with a well-formulated analytics program can inform design decisions, demonstrate the degree to which those decisions have succeeded, and thereby inform the next iteration in the design process. The Health Sciences Libraries of the University of Minnesota have been using Google Analytics as their primary analytics solution since 2005, and as Google has continued to add functionality and flexibility to the platform, the Health Sciences Libraries has capitalized on the opportunities made available. In this article the author outlines the Health Sciences Libraries strategy for using Google Analytics and describes several of the more novel methods they have developed, providing a roadmap for others seeking to strengthen their understanding of the behavior of users on their library's Web sites.     

Cloud-based big data analytics for customer insight-driven design innovation in SMEs

Fast development of IT and ICT facilitate customers to post a large volume of their concerns and expectation online, which are widely accepted to be a valuable resource for product designers. However, it is found that only a small number of small and medium-sized enterprises (SMEs) have capabilities to leverage customer online insights for design innovation, which often demonstrate a significant share in national economies growth. To discover the beneath reasons regarding the barrier that prevent them to make effective utilization, in this study, as a concrete example, manufacturing SMEs in the South Wales and Greater Manchester industrial areas of the UK are focused and their potential motivations for using and knowledge of big data-based customer analytics are investigated. An exploratory survey was conducted in terms of the type of customer data they have, the storage approaches, the volume of customer data, etc. Next, a carefully devised exploratory study was undertaken to understand how SMEs perceive the relations between customer data and product design, how about their expectations from big customer data analytics and what really challenges SMEs to exploit the value of big customer data. Besides, a demonstration platform is developed to present SMEs an automatic process of analysing customer online reviews and the capacity on customer insights acquisition and strategic decision making. Finally, findings from two focus groups indicate the different managerial and technical considerations required for SMEs considering implementing big data and customer analytics. This study encourages SMEs to welcome big customer data and suggests that a cloud-based approach may be the most appropriate way of giving access to big data analytics techniques.     

Assessing collaborative learning: big data,analytics and university futures

Assessment in higher education has focused on the performance of individual students. This focus has been a practical as well as an epistemic one: methods of assessment are constrained by the technology of the day, and in the past they required the completion by individuals under controlled conditions of set-piece academic exercises. Recent advances in learning analytics, drawing upon vast sets of digitally stored student activity data, open new practical and epistemic possibilities for assessment, and carry the potential to transform higher education. It is becoming practicable to assess the individual and collective performance of team members working on complex projects that closely simulate the professional contexts that graduates will encounter. In addition to academic knowledge, this authentic assessment can include a diverse range of personal qualities and dispositions that are key to the computer-supported cooperative working of professionals in the knowledge economy. This paper explores the implications of such opportunities for the purpose and practices of assessment in higher education, as universities adapt their institutional missions to address twenty-first century needs. The paper concludes with a strong recommendation for university leaders to deploy analytics to support and evaluate the collaborative learning of students working in realistic contexts.     

智慧科研:让管理更科学——精细化自然科学基金项目管理新思维

本文针对传统的国家自然科学基金(以下简称科学基金)项目管理方式在项目管理各阶段呈现的问题,提出了一种科学基金项目管理的新思维,即从经验式到精细化的科学基金项目管理方案。其基本原理是用数据说话,即基于优质数据的科学化管理。具体包括:如何从科学文献库中检索和收集科研成果数据、如何全面分析科研成果数据和如何智能辅助科学基金项目管理各个环节的管理决策。这一思路的应用将有效提升科学基金项目管理的效能,提高科学基金的使用效益。