scholarly journals A Review of Tools and Techniques for Data-Enabled Formative Assessment

2017 ◽  
Vol 46 (4) ◽  
pp. 505-526 ◽  
Author(s):  
Rob Nyland
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Literature Review ◽  
Formative Assessment ◽  
Real Time ◽  
Stream Data ◽  
Descriptive Data ◽  
Current State ◽  
State Of Research ◽  
Tools And Techniques

The purpose of this literature review is to understand the current state of research on tools that collect data for the purpose of formative assessment. We were interested in identifying the types of data collected by these tools, how these data were processed, and how the processed data were presented to the instructor or student for the purpose of formative assessment. We identified two categories of data: machine-graded and activity stream data. The data were processed using three methods: unprocessed activity streams, descriptive data analysis, and data mining. Processed data were presented to students through reports and real-time feedback and to instructors through reports and visual dashboards.

Sport in business studies: a state-of-the-art literature review

2018 ◽  
Vol 8 (5) ◽  
pp. 529-546
Author(s):  
Christofer Laurell ◽  
Sten Soderman
Keyword(s):  
Systematic Review ◽  
Literature Review ◽  
Marketing Strategy ◽  
Design Methodology ◽  
State Of The Art ◽  
Future Research ◽  
Content Type ◽  
Business Studies ◽  
Current State ◽  
State Of Research

PurposeThe purpose of this paper is to provide a systematic review of articles on sport published in leading business studies journals within marketing, organisational studies and strategy.Design/methodology/approachBased on a review of 38 identified articles within the subfields of marketing, strategy and organisation studies published between 2000 and 2015, the articles’ topical, theoretical and methodological orientation within the studied subfields were analysed followed by a cross-subfield analysis.FindingsThe authors identify considerable differences in topical, theoretical and methodological orientation among the studied subfields’ associated articles. Overall, the authors also find that articles across all subfields tend to be focussed on contributing to mature theory, even though the subfield of marketing in particular exhibits contributions to nascent theory in contrast to organisation studies and strategy.Originality/valueThis paper contributes by illustrating the current state of research that is devoted or related to the phenomenon of sport within three subfields in business studies. Furthermore, the authors discuss the role played by leading business studies journalsvis-à-vissport sector-specific journals and offer avenues for future research.

A Classification Framework for Data Mining Applications in Criminal Science and Investigations

2020 ◽  
pp. 277-293
Author(s):  
Mahima Goyal ◽  
Vishal Bhatnagar ◽  
Arushi Jain
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Data Mining Techniques ◽  
Road Map ◽  
Classification Framework ◽  
Challenges And Opportunities ◽  
Crucial Information ◽  
Tools And Techniques ◽  
Day By Day ◽  
Mining Tools

The importance of data analysis across different domains is growing day by day. This is evident in the fact that crucial information is retrieved through data analysis, using different available tools. The usage of data mining as a tool to uncover the nuggets of critical and crucial information is evident in modern day scenarios. This chapter presents a discussion on the usage of data mining tools and techniques in the area of criminal science and investigations. The application of data mining techniques in criminal science help in understanding the criminal psychology and consequently provides insight into effective measures to curb crime. This chapter provides a state-of-the-art report on the research conducted in this domain of interest by using a classification scheme and providing a road map on the usage of various data mining tools and techniques. Furthermore, the challenges and opportunities in the application of data mining techniques in criminal investigation is explored and detailed in this chapter.

Translating Advances in Data Mining in Business Operations

2008 ◽  
pp. 2734-2748
Author(s):  
Henry Dillon ◽  
Beverley Hope
Keyword(s):  
Data Mining ◽  
Information Technology ◽  
Data Analysis ◽  
Knowledge Discovery ◽  
Knowledge Discovery In Databases ◽  
Business Context ◽  
Business Operations ◽  
Analysis Tools ◽  
It Managers ◽  
Tools And Techniques

Knowledge discovery in databases (KDD) is a field of research that studies the development and use of various data analysis tools and techniques. KDD research has produced an array of models, theories, functions and methodologies for producing knowledge from data. However, despite these advances, nearly two thirds of information technology (IT) managers say that data mining products are too difficult to use in a business context. This chapter discusses how advances in data mining translate into the business context. It highlights the art of business implementation rather than the science of KDD.

Incorporation of Depth in Two Dimensional Video Captures

2016 ◽  
pp. 88-109
Author(s):  
Manami Barthakur ◽  
Kandarpa Kumar Sarma
Keyword(s):  
Literature Review ◽  
Three Dimensional ◽  
Video Image ◽  
Stereoscopic Vision ◽  
Two Dimensional ◽  
Video Images ◽  
Current State ◽  
State Of Research ◽  
Generic System ◽  
2D To 3D

Stereoscopic vision in cameras is an interesting field of study. This type of vision is important in incorporation of depth in video images which is needed for the ability to measure distances of the object from the camera properly i.e. conversion of two dimensional video image into three dimensional video. In this chapter, some of the basic theoretical aspects of the methods for estimating depth in 2D video and the current state of research have been discussed. These methods are frequently used in the algorithms for estimating depth in the 2D to 3D video techniques. Some of the recent algorithms for incorporation depth in 2D video are also discussed and from the literature review a simple and generic system for incorporation depth in 2D video is presented.

scholarly journals Data Preprocessing: The Techniques for Preparing Clean and Quality Data for Data Analytics Process

2021 ◽  
Vol 13 (0203) ◽  
pp. 78-81
Author(s):  
Ashish P. Joshi ◽  
Biraj V. Patel
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Real Time ◽  
Data Preprocessing ◽  
Quality Data ◽  
Data Conversion ◽  
Time Data ◽  
Quality Of Data ◽  
Real Time Data ◽  
Integration Data

The model and pattern for real time data mining have an important role for decision making. The meaningful real time data mining is basically depends on the quality of data while row or rough data available at warehouse. The data available at warehouse can be in any format, it may huge or it may unstructured. These kinds of data require some process to enhance the efficiency of data analysis. The process to make it ready to use is called data preprocessing. There can be many activities for data preprocessing such as data transformation, data cleaning, data integration, data optimization and data conversion which are use to converting the rough data to quality data. The data preprocessing techniques are the vital step for the data mining. The analyzed result will be good as far as data quality is good. This paper is about the different data preprocessing techniques which can be use for preparing the quality data for the data analysis for the available rough data.

scholarly journals Reconstructing Vindonissa as a living document – A case-study of digital reconstruction for output to pre-rendered and real-time applications

2017 ◽  
Vol 1 (2) ◽  
pp. 396-408
Author(s):  
Jonas Christen
Keyword(s):  
Real Time ◽  
Time Use ◽  
3D Models ◽  
Digital Reconstruction ◽  
Current State ◽  
Starting Point ◽  
Reconstructive Process ◽  
The Alps ◽  
State Of Research

The legion camp “Vindonissa” in Switzerland is considered one of the most important roman sites north of the alps. Research there has been going on for over a century and reconstructive drawings have always been a way to showcase scientific findings of the site, the earliest of them dating back as far as 1909.In 2015, it was decided to produce a new series of illustrations. The whole camp and its surrounding settlements had to be constructed as hand-generated 3D models, allowing for quick changes during the reconstructive process and flexibility in future adaptations. Topographical data, archaeological plans as well as building profiles provided by experts were the basis for the model.The main focus was on a general impression of the camp and not on individual buildings but some landmarks as the newly postulated circus were crafted with a higher level of detail as they are the topic of scientific discourse and it helps the discussion if they have a certain fidelity. The circus also serves as a good example for the value of the imaging process in research: Only after trying to fit it into the topography it was noted that it would overlap with a street that was previously thought to run through this area. In the discussion between archaeologists and illustrators a new path for the street was chosen that fits into the landscape and is scientifically acceptable.The new series of illustrations was originally published in the annual report of the archaeological society Vindonissa. The resulting model represents the current state of research but mainly serves as a starting point for future discussion: All buildings are constructed so that they can easily be adapted for real-time use and a Virtual Reality application is the logical next step for its use. 

scholarly journals A Review of the Internet of Floods: Near Real-Time Detection of a Flood Event and Its Impact

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2275 ◽  
Author(s):  
Van Ackere ◽  
Verbeurgt ◽  
Sloover ◽  
Gautama ◽  
De Wulf ◽  
...  
Keyword(s):  
Real Time ◽  
Flood Event ◽  
The Internet ◽  
Flood Events ◽  
Cultural Impact ◽  
Current Trends ◽  
Current State ◽  
Flood Detection ◽  
State Of Research ◽  
Ideal Method

Worldwide, flood events frequently have a dramatic impact on urban societies. Time is key during a flood event in order to evacuate vulnerable people at risk, minimize the socio-economic, ecologic and cultural impact of the event and restore a society from this hazard as quickly as possible. Therefore, detecting a flood in near real-time and assessing the risks relating to these flood events on the fly is of great importance. Therefore, there is a need to search for the optimal way to collect data in order to detect floods in real time. Internet of Things (IoT) is the ideal method to bring together data of sensing equipment or identifying tools with networking and processing capabilities, allow them to communicate with one another and with other devices and services over the Internet to accomplish the detection of floods in near real-time. The main objective of this paper is to report on the current state of research on the IoT in the domain of flood detection. Current trends in IoT are identified, and academic literature is examined. The integration of IoT would greatly enhance disaster management and, therefore, will be of greater importance into the future.

Cloud computing and human resource management: systematic literature review and future research agenda

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Juan Manuel Maqueira Marín ◽  
Diessica De Oliveira-Dias ◽  
Nima Jafari Navimipour ◽  
Bhaskar Gardas ◽  
Mehmet Unal
Keyword(s):  
Cloud Computing ◽  
Literature Review ◽  
Human Resource ◽  
Research Agenda ◽  
Future Research ◽  
Content Type ◽  
Future Research Agenda ◽  
Current State ◽  
State Of Research

PurposeThis study aims to provide an overview of what characterizes the current state of research in the field of cloud computing use in human resource management (HRM) with the identification, analysis and classification of the existing literature and lines of research addressed and to provide guidance for future research.Design/methodology/approachThe systematic literature review (SLR) technique has been used to identify, select, analyze and evaluate the existing publications on cloud computing and HRM. A total of 35 papers published up to December 2020 have been obtained from the Web of Science (WoS) scientific database. The research design has allowed us to determine what characterizes the current state of research on the use of cloud computing in HRM and obtain a novel classification of the literature that identifies four lines of research and the contributions in each line and has allowed us to define the future research agenda.FindingsThe four groups into which the papers on the cloud computing-HRM relationship have been classified are: (1) studies focused on the development of cloud platforms for HRM that highlight technical aspects, (2) papers that focus on the concept of human resource elasticity, (3) papers on the adoption and/or implantation of cloud platforms for HRM and (4) studies that highlight the effects or implications of cloud platforms for HRM. This paper proposes some new opportunities for future research and presents some helpful implications from the theoretical and management perspectives.Research limitations/implicationsThis study uses only scientific articles in the WoS database with a Journal Citation Report (JCR) or SCImago Journal Rank (SJR) impact.Originality/valueThis paper provides an overview of the knowledge on cloud computing and HRM research and offers recommendations for future research.

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