About this paper

Appears in:
Page: 3013 (abstract only)
Publication year: 2012
ISBN: 978-84-695-3491-5
ISSN: 2340-1117

Conference name: 4th International Conference on Education and New Learning Technologies
Dates: 2-4 July, 2012
Location: Barcelona, Spain

AUTOMATED TRADING STRATEGY, SELF-FUNDING LECTURE CAPTURE SYSTEMS METHODOLOGY TO ENHANCE INSTANT AUTHORSHIPS, CREATE AUTOMATED TEST BANK PRODUCTION, AND SUPPLEMENT EDUCATIONAL BACKUP AND RECOVERY PLANS

A. Rushinek, S. Rushinek

University of Miami (UNITED STATES)
This paper describes a methodology for self-funding of the lecture capture process. This automated fund generation approach takes advantage of the efforts of the instructor in the lecture capture process. In connecting the surveillance cameras to the instructor classrooms, the PC capture card automatically burns media in real-time. All that the instructors have to do is press the Start, Stop, and Record buttons on the virtual video recording software running on their PCs and swap out the full disks. As the system records the lectures, it also transcribes the audio into text, snaps the instructors first video image as a cover picture for the disk. The automated system attaches the materials to the digital copies and uploads them to a shopping cart based web site published on the World Wide Web. As the system transcribes the lecture audio, it also automates the production of quiz questions and an answer key based on the lecture. This is totally free and we propose instructor profit sharing on an On-Demand basis with the distributor.

Our research explores on how to use these totally free On-Demand services without the need for any financial or administrative support. Our methodology is to use free software, such as Panapto for lecture capture that is hosted on a free local host classroom computer. Real Simple Syndication (RSS) feeds subscribe to XML coded video that is re-purposed from surveillance video cameras that are part of the existing classroom infrastructure. Direct video camera personnel are not needed and podcasts are automatically uploaded to the internet. Social media networks are uploaded automatically along with Search Engine Optimization (SEO) algorithms are employed and constantly update in the background. We investigate how instructors can deploy effective learning strategies and student assessments with the aid of these automated systems. All lectures and additional materials can be incorporated into the institution’s Business Continuity Contingency Planning (BCCP), Emergency Preparedness Response (EPR), Disaster and Backup Recovery (DBR) plans. When a disaster strikes, all instructional materials can be accessed from anywhere in the world and instruction does not have to be interrupted.

Automated Trading Strategy describes a course about trading securities, stocks, equities, Exchange Traded Funds (ETFs), commodities, futures, currencies that extends the instructor led classes to World Wide Web (WWW) webinars by streaming, archiving, the classroom audio video (AV) by using re-purposed surveillance systems for a zero marginal cost. Using Search Engine Optimization (SEO) techniques, and reversed engineering methodologies, the videos top the search engines, such as Google, and stay at the top for more than 5 years, for a given key word such as "Nets-Expert." Such a keyword search produced "About 18,600,000 results" or hits, last time the authors accessed it on April 4, 2012. Following is an example of such lecture capture: http://www.google.com/search?q=Nets-Expert

Automated Day-traders need fast reliable information. Most universities do not teach such high risk topics, which enables the few that teach it to easily monopolize the WWW, charge abnormally high rates, & easily fund their operations. Likewise, the mathematical complexity of algorithmic High Frequency Trading (HFT) trading, limits the instructors to Ph.D.s that have had significant training & experience raising the barriers to entry. It can be very lucrative!
@InProceedings{RUSHINEK2012AUT,
author = {Rushinek, A. and Rushinek, S.},
title = {AUTOMATED TRADING STRATEGY, SELF-FUNDING LECTURE CAPTURE SYSTEMS METHODOLOGY TO ENHANCE INSTANT AUTHORSHIPS, CREATE AUTOMATED TEST BANK PRODUCTION, AND SUPPLEMENT EDUCATIONAL BACKUP AND RECOVERY PLANS},
series = {4th International Conference on Education and New Learning Technologies},
booktitle = {EDULEARN12 Proceedings},
isbn = {978-84-695-3491-5},
issn = {2340-1117},
publisher = {IATED},
location = {Barcelona, Spain},
month = {2-4 July, 2012},
year = {2012},
pages = {3013}}
TY - CONF
AU - A. Rushinek AU - S. Rushinek
TI - AUTOMATED TRADING STRATEGY, SELF-FUNDING LECTURE CAPTURE SYSTEMS METHODOLOGY TO ENHANCE INSTANT AUTHORSHIPS, CREATE AUTOMATED TEST BANK PRODUCTION, AND SUPPLEMENT EDUCATIONAL BACKUP AND RECOVERY PLANS
SN - 978-84-695-3491-5/2340-1117
PY - 2012
Y1 - 2-4 July, 2012
CI - Barcelona, Spain
JO - 4th International Conference on Education and New Learning Technologies
JA - EDULEARN12 Proceedings
SP - 3013
EP - 3013
ER -
A. Rushinek, S. Rushinek (2012) AUTOMATED TRADING STRATEGY, SELF-FUNDING LECTURE CAPTURE SYSTEMS METHODOLOGY TO ENHANCE INSTANT AUTHORSHIPS, CREATE AUTOMATED TEST BANK PRODUCTION, AND SUPPLEMENT EDUCATIONAL BACKUP AND RECOVERY PLANS, EDULEARN12 Proceedings, p. 3013.
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