Capturing and Authoring Tools for Graphics in E-Learning

2010 ◽  
pp. 118-141
Author(s):  
Shalin Hai-Jew
Keyword(s):  
Open Source ◽  
Digital Images ◽  
Authoring Tools ◽  
Continuous Image ◽  
Digital Imagery ◽  
Image Capture ◽  
Still Images ◽  
Image Information ◽  
Wide Range ◽  
E Learning

A wide range of capturing and authoring tools for the raw image capture, creation and deployment of digital imagery for e-learning exists. Image information may be captured using light and sound. The digital images may be captured from realia, as in digital archival efforts; they may be wholly “born digital” and not have much relation to reality. They may be still images or dynamic ones. Some technologies offer continuous image capture and live analysis or annotation of the information. This chapter covers common capturing and authoring tools. A sidebar by Dr. Jason Caudill, a professor, addresses the use of open –source software for creating digital images.

Future Digital Imagery

2010 ◽  
pp. 312-323
Author(s):  
Shalin Hai-Jew
Keyword(s):  
Teaching And Learning ◽  
Digital Imagery ◽  
Shared Resources ◽  
Image Capture ◽  
Pedagogical Strategies ◽  
Complex Information ◽  
Research And Teaching ◽  
E Learning ◽  
Near Term ◽  
Information Streams

The use of digital imagery in e-learning will likely become more widespread and pedagogically sophisticated, both in the near-term and far-term. The technologies for image capture and manipulation will allow more graphical affordances, including uses in 3D, 4D, ambient spaces, augmented realities and augmented virtualities. Visualizations will likely offer a greater variety of functionalities: more aid for real-time decision-making, more complex information streams, and synchronous real-world mitigations of crises and actions. The pedagogical strategies used around images may also grow more supportive of learning, with more shared research and teaching-and-learning experiences. More accurate labeling and storage of e-learning visuals will continue, with additions on both the privately held collections and the publicly shared resources. There may well be greater diversification of the applications of digital imagery capture, authoring, use, and sharing in different learning domains. Ideally, more professional creators of digital imagery will come online from various parts of the world to enhance the shared repository of learning for a global community.

Applied Ethics for Digital Imagery

2010 ◽  
pp. 288-311
Author(s):  
Shalin Hai-Jew
Keyword(s):  
Cultural Values ◽  
Applied Ethics ◽  
Digital Imagery ◽  
Ethical Guidelines ◽  
Image Capture ◽  
The Social ◽  
E Learning ◽  
Technological Affordances ◽  
Personal Ethics ◽  
Social Uses

Graphical images have much power to evoke and represent realities, convey experiences, and share information. They may be used to share history. They may be used to discover realities and truths. In terms of the social uses of images, they may persuade individuals or whole populaces of people to take courses of action. With the growing technological affordances of image capture and creation, those who would build e-learning with imagery need to be aware of ethical guidelines in capturing, creating, handling and using digital imagery in a learning environment. The sources of these ethical guidelines include cultural values, laws, professional educational practices, professional journalistic practices, and personal ethics.

Designing Informational Graphics for a Global Multi-Cultural Context

2010 ◽  
pp. 267-287
Author(s):  
Shalin Hai-Jew
Keyword(s):  
Visual Imagery ◽  
Cultural Context ◽  
Digital Images ◽  
Global Environment ◽  
Learning Needs ◽  
Digital Imagery ◽  
Cultural Milieu ◽  
Cultural Implications ◽  
Explanatory Depth ◽  
E Learning

With many e-learning courses, modules, and artifacts being created for global delivery, those who design informational graphics need to be aware of the global environment for which they are building. They need to be more aware of the diverse cultural milieu and learning needs of the global learners. Visual imagery contains embedded meanings that may have different cultural implications in different milieu. This chapter will explore strategies to create digital images that are culturally neutral or at least culturally non-offensive. Building a layer of self-explanatory depth will also be helpful—for digital imagery with higher transferability and global utility.

Types of Graphics in E-Learning

2010 ◽  
pp. 67-88
Author(s):  
Shalin Hai-Jew
Keyword(s):  
Digital Imagery ◽  
Still Images ◽  
Different Types ◽  
E Learning ◽  
Types Of Information ◽  
Informational Value

Digital graphics commonly used in e-learning come in various image types and dimensions, each of which enables different types of information communications. The concept of dimensionality builds on how images work on the x, y, and z axes. This also builds on the affordances of digital imagery with live updates, movements, interactivity, emotionality, and other features that may be overlaid or imbued into visuals. This chapter addresses still images to dynamic ones. Considering the types of graphics and the informational value of each category should enhance their development and use in e-learning.

Promoting Hybrid Learning through an Open Source EBook Approach

2010 ◽  
Vol 14 (3) ◽  
Author(s):  
Xin Bai ◽  
Michael B. Smith
Keyword(s):  
Open Source ◽  
Building Blocks ◽  
Educational Technologies ◽  
Just In Time ◽  
Learning Modules ◽  
Learning Content ◽  
Long Run ◽  
E Learning ◽  
Teaching Efficiency ◽  
Content Design

Educational technology is developing rapidly, making education more accessible, affordable, adaptable, and equitable. Students now have the option to choose a campus that can provide excellent blended learning curriculum with minimal geographical restraints. We proactively explore ways to maximize the power of educational technologies to increase enrollment, reduce failure rates, improve teaching efficiency, and cut costs without sacrificing high quality or placing extra burden on faculty. This mission is accomplished through open source learning content design and development. We developed scalable, shareable, and sustainable e-learning modules as book chapters that can be distributed through both computers and mobile devices. The resulting e-learning building blocks can automate the assessment processes, provide just-in-time feedback, and adjust the teaching material dynamically based upon each student’s strengths and weaknesses. Once built, these self-contained learning modules can be easily maintained, shared, and re-purposed, thus cutting costs in the long run. This will encourage faculty from different disciplines to share their best teaching practices online. The end result of the project is a sustainable knowledge base that can grow over time, benefit all the discipline, and promote learning.

STEGANOGRAFI DENGAN MENGGUNAKAN METODE LSB DAN ALGORITMA HILL CIPHER

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Sherly Gina Supratman
Keyword(s):  
Digital Images ◽  
Text Messages ◽  
The Internet ◽  
Digital Imagery ◽  
Least Significant Bit ◽  
Hill Cipher ◽  
Secure Data ◽  
Audio Video ◽  
The Hill

AbstrakJaringan Komunikasi seperti Internet� merupakan jaringan yang tidak aman untuk mentransmisi data, seperti teks, audio,video dan citra digital. Salah satu cara untuk pengamanan data dapat dilakukan dengan menggunakan proses kriptografi dan �steganografi. Penggunaan ini dengan tujuan untuk merahasiakan pesan yang dikirim dan sekaligus menghindarkan pesan tersebut dari kecurigaan pihak lain yang tidak berkepentingan.Pesan yang digunakan dalam makalah ini adalah berupa text dengan menyisipkannya pada gambar. Pada proses kriptografi, pesan yang berupa text akan dienkrip dengan algoritma Hill Chiper, dan kemudian pesan yang telah dienkrip akan dilakukan proses steganografi pada citra digital� 8 bit dengan skala 0 � 255, dengan metode Least Significant Bit ( LSB ).�Kata kunci: Kriptografi, Hill Chiper, Steganografi, Least Significant Bit�AbstractCommunication Networks such as the Internet are unsafe networks for transmitting data, such as text, audio, video and digital imagery. One way to secure data can be done by using cryptography and steganography process. This use is for the purpose of concealing messages being transmitted and avoiding such messages from the suspicion by others who are not interested.The message used in this paper is text by inserting it in the image. In the cryptographic process, text messages will be encrypted with the Hill Chiper algorithm, and then the encrypted message will be steganographed on 8-bit digital images on a scale of 0-255, using the Least Significant Bit (LSB) method.�Keywords: Cryptography, Hill Chiper, Steganography, Least Significant Bit

Unique views on obesity-related behaviors and environments: research using still and video images (Preprint)

2018 ◽  
Author(s):  
Jordan Carlson ◽  
J. Aaron Hipp ◽  
Jacqueline Kerr ◽  
Todd Horowitz ◽  
David Berrigan
Keyword(s):  
Physical Activity ◽  
Ethical Issues ◽  
Data Extraction ◽  
Dietary Assessment ◽  
Extraction Methods ◽  
Image Capture ◽  
Still Images ◽  
Key Informants ◽  
Technological Advances ◽  
Computer Scientists

BACKGROUND Image based data collection for obesity research is in its infancy. OBJECTIVE The present study aimed to document challenges to and benefits from such research by capturing examples of research involving the use of images to assess physical activity- or nutrition-related behaviors and/or environments. METHODS Researchers (i.e., key informants) using image capture in their research were identified through knowledge and networks of the authors of this paper and through literature search. Twenty-nine key informants completed a survey covering the type of research, source of images, and challenges and benefits experienced, developed specifically for this study. RESULTS Most respondents used still images in their research, with only 26.7% using video. Image sources were categorized as participant generated (N = 13; e.g., participants using smartphones for dietary assessment), researcher generated (N = 10; e.g., wearable cameras with automatic image capture), or curated from third parties (N = 7; e.g., Google Street View). Two of the major challenges that emerged included the need for automated processing of large datasets (58.8%) and participant recruitment/compliance (41.2%). Benefit-related themes included greater perspectives on obesity with increased data coverage (34.6%) and improved accuracy of behavior and environment assessment (34.6%). CONCLUSIONS Technological advances will support the increased use of images in the assessment of physical activity, nutrition behaviors, and environments. To advance this area of research, more effective collaborations are needed between health and computer scientists. In particular development of automated data extraction methods for diverse aspects of behavior, environment, and food characteristics are needed. Additionally, progress in standards for addressing ethical issues related to image capture for research purposes are critical. CLINICALTRIAL NA

Learning objects management and evaluatio in an e-learning environment

1970 ◽  
Vol 6 (2) ◽  
Author(s):  
Hugo Rego ◽  
Tiago Moreira ◽  
Francisco José García-Peñalvo
Keyword(s):  
Knowledge Management ◽  
Learning Environment ◽  
Learning Process ◽  
Group Learning ◽  
Learning Objects ◽  
Authoring Tools ◽  
Learning Platform ◽  
E Learning ◽  
Teaching Learning ◽  
Educational Contents

The main aim of the AHKME e-learning platform is to provide a system with adaptive and knowledge management abilities for students and teachers. This system is based on the IMS specifications representing information through metadata, granting semantics to all contents in the platform, giving them meaning. In this platform, metadata is used to satisfy requirements like reusability, interoperability and multipurpose. The system provides authoring tools to define learning methods with adaptive characteristics, and tools to create courses allowing users with different roles, promoting several types of collaborative and group learning. It is also endowed with tools to retrieve, import and evaluate learning objects based on metadata, where students can use quality educational contents fitting their characteristics, and teachers have the possibility of using quality educational contents to structure their courses. The learning objects management and evaluation play an important role in order to get the best results in the teaching/learning process.

An open-source R-package and web application for high-quality probabilistic predictions in hydrology

2021 ◽  
Author(s):  
Jason Hunter ◽  
Mark Thyer ◽  
Dmitri Kavetski ◽  
David McInerney
Keyword(s):  
Open Source ◽  
Web Application ◽  
R Package ◽  
Error Model ◽  
Objective Functions ◽  
High Quality ◽  
Wide Range ◽  
Probabilistic Error

<p>Probabilistic predictions provide crucial information regarding the uncertainty of hydrological predictions, which are a key input for risk-based decision-making. However, they are often excluded from hydrological modelling applications because suitable probabilistic error models can be both challenging to construct and interpret, and the quality of results are often reliant on the objective function used to calibrate the hydrological model.</p><p>We present an open-source R-package and an online web application that achieves the following two aims. Firstly, these resources are easy-to-use and accessible, so that users need not have specialised knowledge in probabilistic modelling to apply them. Secondly, the probabilistic error model that we describe provides high-quality probabilistic predictions for a wide range of commonly-used hydrological objective functions, which it is only able to do by including a new innovation that resolves a long-standing issue relating to model assumptions that previously prevented this broad application.  </p><p>We demonstrate our methods by comparing our new probabilistic error model with an existing reference error model in an empirical case study that uses 54 perennial Australian catchments, the hydrological model GR4J, 8 common objective functions and 4 performance metrics (reliability, precision, volumetric bias and errors in the flow duration curve). The existing reference error model introduces additional flow dependencies into the residual error structure when it is used with most of the study objective functions, which in turn leads to poor-quality probabilistic predictions. In contrast, the new probabilistic error model achieves high-quality probabilistic predictions for all objective functions used in this case study.</p><p>The new probabilistic error model and the open-source software and web application aims to facilitate the adoption of probabilistic predictions in the hydrological modelling community, and to improve the quality of predictions and decisions that are made using those predictions. In particular, our methods can be used to achieve high-quality probabilistic predictions from hydrological models that are calibrated with a wide range of common objective functions.</p>

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