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"Buchem, I., Attwell, G. & Torres, R. (2011). Understanding Personal Learning Environments: Literature Review and Syntheis Through Activity Theory Lense. In: Proceedings on the PLE Conference 2011. List of References used for the literature Review in alphabetical order:" Note: this is a wiki, so watch for updates (CA)

"In the summer of 2010, Peter Mosinskis from CSU Channel Islands assembled a team of approximately fifteen volunteers from seven different CSU campuses and one from the UC system to evaluate the accessibility of Google Apps. The team also recruited student volunteers and screen reader users to assist with the testing. Automated, manual, and screen reader testing began the first week of January 2011 and was completed February 4th. The report has been completed and posted here for your review. The CSU Accessible Technology Initiative (ATI) Staff, ATI Leadership Council, and Google have reviewed the Google Apps Accessibility Evaluation report. We discovered a number of accessibility issues during our testing. These issues are outlined in the report as well as "workarounds" that can be used to improve the user experience for persons with disabilities. When campuses choose to use Google Apps, they are required to provide an equally effective service for people with disabilities and it is critical for campuses to ensure that the "workarounds" meet the educational needs of the student and/or faculty. The March 15, 2011 USA TODAY online news article "Complaint: Google programs hard for blind students" illustrates possible legal problems that may result from adopting the Google Apps for Education suite. Questions or Comments about this report may be directed to CSU ATI Staff"

Table of Contents Print Complete BookPrint This Chapter Next ATI Google Apps Accessibility Evaluation Section 1. Executive Summary Section 2. About the Project Section 3. Findings Section 4. Workarounds, Accommodations and Best Practices Summary and Conclusions Authors Note Appendices A - E

Liz B. Davis 5:22 "Titled, In Classroom of the Future, Stagnant Scores , the article describes a school in Arizona where, despite a huge investment in technology, there hasn't been an increase in test scores. The article is based on one school in one town in Arizona, hardly a statistically significant sample. Larry Cuban, an outspoken critic of technology in schools since the early 1990s, is quoted multiple times. Not one of the many experts in the field of educational technology, whom we know and love, was interviewed (or at least quoted) in the article. The only reason given for the failure of technology is a lack of increase in test scores in a district that already had high test scores. Finally, there was no test comparing the technology skills of students in this school to any other school in the state. "

This post is about the same http://www.nytimes.com/2011/09/04/technology/technology-in-schools-faces-questions-on-value.html article by Matt Richtel, of which Jim Shimabukuro reviewed a shorter version http://www.bendbulletin.com/article/20110905/NEWS0107/109050315/ in http://etcjournal.com/2011/09/05/a-lesson-from-the-kyrene-school-district-technology-alone-is-not-the-answer/

About the same NYT article by Matt Richtel, a shorter and later version of which Jim Shimabukuro reviewed in http://etcjournal.com/2011/09/05/a-lesson-from-the-kyrene-school-district-technology-alone-is-not-the-answer/

At ACL Digital Life Sciences, our clinical data managers are well-experienced in hosting EDCs or providing vendor oversight. Our clinical data managers have years of experience in multiple therapeutic areas across all Phase I-IV studies. We are highly qualified in CDISC compliance and SME-level expertise to produce results with the speed and accuracy you need. Clinical data management supports the conduct, management, and analysis of studies throughout the entire period of clinical research. CDM comprises legacy paper and contemporary electronic case report form designing, clinical trials database design and programming, data standards implementation, data acquisition, data integration into the clinical trials database, data review, validation, coding, and database finalization.