Towards mapping competencies through learning analytics: real-time competency assessment for career direction through interactive simulation

Abstract

The selection of career paths and making of academic choices is a difficult and often confusing task for young people. The impact on their lives, however, is enormous as it can determine entire future career possibilities. In India, a general remedy to this stress is that instead of choosing a field of study tailored to individual preferences and strengths, topics are chosen that align with the choices of the students’ families or their friends. This can have the effect of entrenching patterns of intergenerational inequity. The aim of this research is to give students greater access to the knowledge capital which will help them make better choices. This is achieved by engaging students in the career planning process, in order to convey information in a likeable and credible way. The COMPCAT (Competency and Career Assessment Tool) game engine combines the use of learning analytics and real time, interactive computer simulations designed to gain insights into the students’ engagement in the making of these complex decisions. This paper presents the conceptual architecture of the game and demonstrates its role in enhancing the learning effectiveness of the students.     

The Suitability of Web Analytics Key Performance Indicators in the Academic Library Environment

As the demand for library assessment grows, academic libraries are becoming more interested in Web analytics. Data are automatically gathered and provide information about a wide variety of online interactions. Libraries have long used simple counts such as visits and page views, but have more recently begun to choose strategic benchmarks, also known as key performance indicators (KPIs). Many common KPIs were created for commercial websites and are challenging to adapt for libraries. However, the underlying concepts are sufficiently valuable that libraries should explore their use. By evaluating the validity of web metrics, libraries can further the development of standards and benchmarks to support future investigations. This article discusses how commercial web metrics might be adapted for use in academic libraries. First, the limitations of web analytics are presented. Major key performance indicators used in the commercial sector are reviewed in the academic library context. Finally, the article discusses how the various indicators might support specific library website goals and decisions and uses local data to illustrate one example case. As libraries choose web analytic methods, they should deliberately evaluate their validity. Over time, this will slowly build the profession's ability to use web analytics more effectively for library assessment.     

Big Data Analytics in Building the Competitive Intelligence of Organizations

Over recent years, organizations have started to capitalize on the significant use of Big Data and emerging technologies to analyze, and gain valuable insights linked to, decision-making processes. The process of Competitive Intelligence (CI) includes monitoring competitors with a view to delivering both actionable and meaningful intelligence to organizations. In this regard, the capacity to leverage and unleash the potential of big data tools and techniques is one of various significant components of successfully steering CI and ultimately infusing such valuable knowledge into CI strategies. In this paper, the authors aim to examine Big Data applications in CI processes within organizations by exploring how organizations deal with Big Data analytics, and this study provides a context for developing Big Data frameworks and process models for CI in organizations. Overall, research findings have indicated a preference for a rather centralized informal process as opposed to a clear formal structure for CI; the use of basic tools for queries, as opposed to reliance on dedicated methods such as advanced machine learning; and the existence of multiple challenges that companies currently face regarding the use of big data analytics in building organizational CI.     

More than just charts and graphs: What to teach in a data visualization course

Based on our experience developing and delivering a highly successful data visualization course within a Master of Science in Business Analytics program, we present a taxonomy for data visualization courses and recommend content and pedagogical features for each type of data visualization course therein. We also discuss the interdependence between data visualization and business communication as a critical consideration in course design.     

学习分析：助推大数据时代高校教师在线专业发展

随着“大数据时代”的到来,一股席卷全球的智能化在线教育浪潮正在蔓延,高校传统的教学模式趋向颠覆,高校教师的职业发展也将受到重大挑战。众多大学生在在线学习时将会产生海量的数据,高校教师如何挖掘、分析这些数据,对改进自身教学实践、促进自身专业发展都具有丰富的价值。学习分析在大数据时代的高等教育中被广泛应用已成必然趋势,并具有非常广阔的应用前景,高校教师应该具备较强的数据分析能力。学习分析从以下四个方面促进大数据时代高校教师在线专业发展：可以提升作为在线学习者的高校教师的学习效率,激发其自主的专业发展意识;可以提高高校教师作为在线教学者的教学效率,发展其在线教学实践智慧;可以提高高校教师作为研究者的研究绩效,提升其对学生在线学习的服务能力;可以提高高校教师作为管理者的管理效率,提升其在线教学领导力。     

Integration of big-data ERP and business analytics (BA)

Technology advancements in cloud computing, big data systems, No-SQL database, cognitive systems, deep learning, and other artificial intelligence techniques make the integration of traditional ERP transaction data and big data streaming from various social media platforms and Internet of Things (IOTs) into a unified analytics system not only feasible but also inevitable. Two steps are prominent for this integration. The first, coined as forming the big-data ERP, is the integration of traditional ERP transaction data and the big data and the second is to integrate the big-data ERP with business analytics (BA). As ERP implementers and BA users are facing various challenges, managers responsible for this big-data ERP-BA integration are also seriously challenged. To help them deal with these challenges, we develop the SIST model (including Strategic alignment, Intellectual and Social capital integration, and Technology integration) and propose that this integration is an evolving portfolio with various maturity levels for different business functions, likely leading to sustainable competitive advantages.     

公共图书馆业务数据体系的梳理分析研究

[目的/意义]由于各图书馆业务服务的内容与方式不同,业务过程中数字化程度与标准不一致,给数据资源的整合造成了困难,并导致相关工作举步维艰。本文对公共图书馆业务数据体系进行梳理与分析,期望促使公共图书馆业务逐步形成数据标准,让公共图书馆的大数据应用得以扩展。[方法/过程]利用扎根理论的方法,对公共图书馆内15位各部门工作负责人进行深度访谈,通过开放式编码、主轴编码和选择性编码等过程提炼出与公共图书馆业务数据有关的概念和范畴。[结果/结论]建构以用户服务类业务、资源建设类业务和运营维护类业务为核心的公共图书馆业务数据体系,涵盖20个主范畴和62个有关的概念。该体系揭示了公共图书馆业务数据的整体框架,为大数据分析提供业务理解的指导方向,并为公共图书馆业务数字化与大数据集成提供依据,笔者也依据该体系提供文献资源分析、用户画像、运营业务的大数据分析应用示例说明。     

The role of learning theory in multimodal learning analytics

This study presents the outcomes of a semi-systematic literature review on the role of learning theory in multimodal learning analytics (MMLA) research. Based on previous systematic literature reviews in MMLA and an additional new search, 35 MMLA works were identified that use theory. The results show that MMLA studies do not always discuss their findings within an established theoretical framework. Most of the theory-driven MMLA studies are positioned in the cognitive and affective domains, and the three most frequently used theories are embodied cognition, cognitive load theory and control–value theory of achievement emotions. Often, the theories are only used to inform the study design, but there is a relationship between the most frequently used theories and the data modalities used to operationalize those theories. Although studies such as these are rare, the findings indicate that MMLA affordances can, indeed, lead to theoretical contributions to learning sciences. In this work, we discuss methods of accelerating theory-driven MMLA research and how this acceleration can extend or even create new theoretical knowledge.

Practitioner notes

What is already known about this topic

• Multimodal learning analytics (MMLA) is an emerging field of research with inherent connections to advanced computational analyses of social phenomena.
• MMLA can help us monitor learning activity at the micro-level and model cognitive, affective and social factors associated with learning using data from both physical and digital spaces.
• MMLA provide new opportunities to support students' learning.

What this paper adds

• Some MMLA works use theory, but, overall, the role of theory is currently limited.
• The three theories dominating MMLA research are embodied cognition, control–value theory of achievement emotions and cognitive load theory.
• Most of the theory-driven MMLA papers use theory ‘as is’ and do not consider the analytical and synthetic role of theory or aim to contribute to it.

Implications for practice and/or policy

• If the ultimate goal of MMLA, and AI in Education in general, research is to understand and support human learning, these studies should be expected to align their findings (or not) with established relevant theories.
• MMLA research is mature enough to contribute to learning theory, and more research should aim to do so.
• MMLA researchers and practitioners, including technology designers, developers, educators and policy-makers, can use this review as an overview of the current state of theory-driven MMLA.