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通过大数据学习分析模型,能够深入探究学习者的学习过程与情境,发现学习规律,根据每一个学生的需求和能力为其提供个性化自适应学习。本研究综述了大数据的内涵及应用,从微观视角提出了大数据之“大”,不在于其表象的“大容量”,而在于分析数据的全面性和潜在的“大价值”。基于大数据分析,从数据与环境(What)、关益者(Who)、方法(How)和目标(Why)等4个维度构建个性化自适应在线学习分析模型。以《C语言程序设计》课程学习为例,从基于大数据个性化自适应的学习过程结构、学习过程可视化及学习效果实证等方面进行分析,研究结果表明对学生学习行为与知识掌握的数据分析,能够推荐合理的学习路径与恰当难度的学习资源,可对学生的学习效果做及时准确的反馈,提供个性化服务干预,有利于促进教与学。 相似文献
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Preparing a Data Scientist: A Pedagogic Experience in Designing a Big Data Analytics Course 
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下载免费PDF全文 Daniel Adomako Asamoah Ramesh Sharda Amir Hassan Zadeh Pankush Kalgotra 《Decision Sciences Journal of Innovative Education》2017,15(2):161-190
In this article, we present an experiential perspective on how a big data analytics course was designed and delivered to students at a major Midwestern university. In reference to the MSIS 2006 Model Curriculum, we designed this course as a level 2 course, with prerequisites in databases, computer programming, statistics, and data mining. Students in the class were mostly seniors or at the graduate level, and had a strong technical and quantitative background. We include details of concepts covered in the course, as well as summaries of four major sample course assignments used. Some of the concepts covered include large‐scale data collection and management using the Hadoop ecosystem, stream mining, visual analytics, and social network analytics. Besides Hadoop, the course also introduced various IBM and Teradata big data tools. We show how the course modules align with the intended learning goals and course objectives. A post‐course survey indicated that the structure and organization of the course helped students clearly and concisely assimilate the course content. 相似文献
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What happens to writing instructors’ feedback when they use a common rubric and an online tool to respond to student papers in a first-year composition course at a large state university in the United States? To investigate this question, we analyze the 118,611 comments instructors made when responding to 17,433 student essays. Using concordance software to quantify teachers’ use of rubric terms, we found instructors were primarily concerned with global, substantive, higher-order concerns—such as responding to students’ rhetorical situations, use of reason, and organization—rather than lower-order concerns about grammar or formatting. Given past research has determined teachers overemphasize lower-order concerns such as grammar, mechanics, and punctuation (Connors and Lunsford, 1988, Lunsford and Lunsford, 2008, Moxley and Joseph, 1989, Moxley and Joseph, 1992, Schwartz, 1984, Sommers, 1982, Stern and Solomon, 2006), these results may suggest the possibility of a generational shift when it comes to response to student writing. Aggregating teacher commentary, student work, and peer review responses via digital tools and employing concordance software to identify big-data patterns illuminates a new assessment practice for Writing Program Administrators—the practice of Deep Assessment. 相似文献
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Julio Guerra Margarita Ortiz-Rojas Miguel Angel Zúñiga-Prieto Eliana Scheihing Alberto Jiménez Tom Broos Tinne De Laet Katrien Verbert 《British journal of educational technology : journal of the Council for Educational Technology》2020,51(4):973-1001
Despite the success of academic advising dashboards in several higher educational institutions (HEI), these dashboards are still under-explored in Latin American HEI's. To close this gap, three different Latin American universities adapted an existing advising dashboard, originally deployed at the KU Leuven to their own context. In all three cases, the context was the main ruling factor to these adaptations. In this paper, we describe these adaptions using a framework that focuses on four different elements of the context: Objectives, Stakeholders, Key moment and Interactions. Evaluation of the adapted dashboards in the three different Latin American universities is conducted through pilots. This evaluation shows the value of the dashboard approach in different contexts in terms of satisfaction, usefulness and impact in academic decision-making and advising tasks. The main contribution of this paper is the systematic reporting of the adaptations to an academic advising dashboard and showing the value of an academic advising dashboard on academic decision-making and advising tasks. 相似文献
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Elizabeth Joan Kelly 《Journal of Web Librarianship》2018,12(1):28-45
This article outlines evidence-based methods for cultural heritage institutions to look for news and mentions about their collections and services online. Google Alerts were created for repository names, websites, and finding aid websites for 66 institutions randomly selected from the Archive Grid database. Results were analyzed to determine Google Alerts' accuracy, what types of institutions would benefit most from using Google Alerts, what the content of the sources found by the alerts was, what types of publications returned the most results, and if Google Alerts could also identify image reuse. While Google Alerts' accuracy for returning usable results for analysis was not very high, the structure of alert e-mails makes discarding irrelevant results simple and quick. Mid- to large-sized museums and institutions staging frequent exhibits and events, as well as those with active collections, return the largest number of alerts. News publications and social media publish the most content related to cultural heritage institutions. Though the sample set was small, Google Alerts also was able to identify image reuse. 相似文献
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Wilbur W. Stanton Angela D'Auria Stanton 《Decision Sciences Journal of Innovative Education》2020,18(1):138-165
Fact‐based decision making is changing job functions within organizations more than any other technology. Analytics, once the purview of the data scientist, is now spread throughout organizations. No longer is there a single job title, job function, or set of required skills and credentials for an analytics career. Companies have moved away from seeking applicants with a specific degree to now recruiting analytics talent based on required skill sets. For more than a decade, business schools have been developing new programs in analytics in response to industry's needs. However, in developing meaningful career‐ready professionals, business programs must understand the skills required across different analytics job functions. In this article, the authors present a comprehensive assessment of the skills sought by employers when considering a candidate for an entry‐level analytics position. The authors describe the demand for various types of analytics professionals, identify the job titles and functions with the most significant demand, and then draw a comparison of the job requirements of hard skills, soft skills, software skills, and credentials between three of the most sought‐after analytics areas: data science, data analytics, and business analytics. The authors conclude by providing faculty and administrators with recommendations on how to adapt their courses and programs to provide students with the fundamental preparation necessary for careers in data science, data analytics, and business analytics. 相似文献
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Marina E. Johnson Abdullah Albizri Rashmi Jain 《Decision Sciences Journal of Innovative Education》2020,18(1):90-118
Recent technological advancements in data storage and processing have changed how companies conduct their business. An increasing number of firms have started putting their efforts in extracting information from their databases to improve profitability and reduce costs using quantitative approaches. Thus, the job market has been experiencing a rapidly growing demand for business analytics (BA) practitioners, and universities across the globe are increasingly responding to this newly emerged field by offering both undergraduate and graduate level degrees as well as certificate programs. Thus, this research aims to provide a framework for academic institutions to develop a state‐of‐the‐art master's in business analytics (MSBA) curriculum by identifying concepts, skills, knowledge, and tools (CSKT) that industry seeks in BA practitioners. Our data‐driven methodology utilizes peer institution analysis, indeed.com web scraping, and focus group analysis with mid‐ and senior‐level analytics leaders from major companies. Our contribution to the literature and recommendations to institutions developing MSBA programs are offered at the end. 相似文献
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在线学习已成为教师专业发展的主要途径,参加学习的人员规模大、行为表现复杂。为了探析教师在线学习行为的群体特征,该文以Y市四期教师在线培训为例,应用统计分析、序列分析、关联规则、社会网络分析等方法,从学习活跃、学习投入时间、学习行为序列、社会交互四个方面分析了教师在线学习行为的群体特征。研究发现:教师在线学习活跃性较高;在线学习时间投入充足;在线学习目的性较强且行为活动方式简单;社会交互情况不够理想。因此,建议实施在线学习与线下集中研讨相结合的混合式教师培训,培训安排与支持服务、学习内容与活动设计应符合教师在线学习规律,并提供有效的技术脚手架和干预机制,以期提高教师培训效益。 相似文献
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Betsy Page Sigman William Garr Robert Pongsajapan Marie Selvanadin Mindy McWilliams Kristin Bolling 《Decision Sciences Journal of Innovative Education》2016,14(4):362-381
The expression “big data” is ubiquitous in the business world today, but few undergraduate business students have the opportunity to gain practical experience with how new business analytics tools can be used in decision making. This article describes a set of hands‐on labs that prepare students to incorporate streaming data analysis into group research projects. Splunk is used to help students analyze and visualize streaming social media data. An evaluation of student projects and student survey results show that this practical approach of training students to manipulate and visualize big data was largely successful in achieving instructional goals. 相似文献
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Gerti Pishtari María J. Rodríguez-Triana Edna M. Sarmiento-Márquez Mar Pérez-Sanagustín Adolfo Ruiz-Calleja Patricia Santos Luis P. Prieto Sergio Serrano-Iglesias Terje Väljataga 《British journal of educational technology : journal of the Council for Educational Technology》2020,51(4):1078-1100
Mobile and Ubiquitous Learning (m/u-learning) are finding an increasing adoption in education. They are often distinguished by hybrid learning environments that encompass elements of formal and informal learning, in activities that happen in distributed settings (indoors and outdoors), across physical and virtual spaces. Despite their purported benefits, these environments imply additional complexity in the design, monitoring and evaluation of learning activities. The research literature on learning design (LD) and learning analytics (LA) has started to deal with these issues. This paper presents a systematic literature review of LD and LA, in m/u-learning. Apart from providing an overview of the current research in the field, this review elicits elements of common ground between both communities, as shown by the similar learning contexts and complementary research contributions, and based on the research gaps, proposes to: address m/u-learning beyond higher education settings, reinforce the connection between physical and virtual learning spaces, and more systematically align LD and LA processes. 相似文献