Google’s sites in London, Madrid, Tel Aviv, Seoul, São Paulo and Warsaw (in a converted former vodka distillery) are hubs for entrepreneurs, providing workspace for startup founders as well as networking and educational events.
the recent offer from Sidewalk Labs – a company owned by Alphabet, Google’s parent company – to redevelop Toronto’s waterfront as a reason to be concerned about the company’s interests in potentially extracting data from cities.
Google’s history of tax evasion and mass surveillance as examples of actions that make it incompatible with the progressive values of the local area.
A large global change in data protection law is about to hit the tech industry, thanks to the EU’s General Data Protection Regulations (GDPR). GDPR affects any company, wherever they are in the world, that handles data about European citizens. It becomes law on 25 May 2018, and as such includes UK citizens, since it precedes Brexit. It’s no surprise the EU has chosen to tighten the data protection belt: Europe has long opposed the tech industry’s expansionist tendencies, particularly through antitrust suits, and is perhaps the only regulatory body with the inclination and power to challenge Silicon Valley in the coming years.
So, no more harvesting data for unplanned analytics, future experimentation, or unspecified research. Teams must have specific uses for specific data.
Augmented reality can be described as experiencing the real world with an overlay of additional computer generated content. In contrast, virtual reality immerses a user in an entirely simulated environment, while mixed or merged reality blends real and virtual worlds in ways through which the physical and the digital can interact. AR, VR, and MR offer new opportunities to create a psychological sense of immersive presence in an environment that feels real enough to be viewed, experienced, explored, and manipulated. These technologies have the potential to democratize learning by giving everyone access to immersive experiences that were once restricted to relatively few learners.
In Grinnell College’s Immersive Experiences Lab http://gciel.sites.grinnell.edu/, teams of faculty, staff, and students collaborate on research projects, then use 3D, VR, and MR technologies as a platform to synthesize and present their findings.
In terms of equity, AR, VR, and MR have the potential to democratize learning by giving all learners access to immersive experiences
relatively little research about the most effective ways to use these technologies as instructional tools. Combined, these factors can be disincentives for institutions to invest in the equipment, facilities, and staffing that can be required to support these systems. AR, VR, and MR technologies raise concerns about personal privacy and data security. Further, at least some of these tools and applications currently fail to meet accessibility standards. The user experience in some AR, VR, and MR applications can be intensely emotional and even disturbing (my note: but can be also used for empathy literacy),
immersing users in recreated, remote, or even hypothetical environments as small as a molecule or as large as a universe, allowing learners to experience “reality” from multiple perspectives.
over the last four years, 49 states and the District of Columbia have introduced 410 bills related to student data privacy, and 36 states have passed 85 new education data privacy laws. Also, since 2014, 19 states have passed laws that in some way address the work done by researchers.
researchers need to get better at communicating about their projects, especially with non-researchers.
One approach to follow in gaining trust “from parents, advocates and teachers” uses the acronym CUPS:
Collection: What data is collected by whom and from whom;
Use: How the data will be used and what the purpose of the research is;
Protection: What forms of data security protection are in place and how access will be limited; and
Sharing: How and with whom the results of the data work will be shared.
Second, researchers must pin down how to share data without making it vulnerable to theft.
Third, researchers should build partnerships of trust and “mutual interest” pertaining to their work with data. Those alliances may involve education technology developers, education agencies both local and state, and data privacy stakeholders.
The 188-page “Challenging Government Hacking In Criminal Cases” report, released by the American Civil Liberties Union on March 30, addresses new amendments to Rule 41 of the Federal Rules of Criminal Procedure, which took effect last December.
Under the changes to criminal procedure rules, feds can remotely search computers in multiple jurisdictions with a single warrant. The rules are touted by law enforcement agencies as a way to streamline 100-year-old rules of criminal procedure
ACRL e-Learning webcast series: Learning Analytics – Strategies for Optimizing Student Data on Your Campus
This three-part webinar series, co-sponsored by the ACRL Value of Academic Libraries Committee, the Student Learning and Information Committee, and the ACRL Instruction Section, will explore the advantages and opportunities of learning analytics as a tool which uses student data to demonstrate library impact and to identify learning weaknesses. How can librarians initiate learning analytics initiatives on their campuses and contribute to existing collaborations? The first webinar will provide an introduction to learning analytics and an overview of important issues. The second will focus on privacy issues and other ethical considerations as well as responsible practice, and the third will include a panel of librarians who are successfully using learning analytics on their campuses.
Webcast One: Learning Analytics and the Academic Library: The State of the Art and the Art of Connecting the Library with Campus Initiatives
March 29, 2016
Learning analytics are used nationwide to augment student success initiatives as well as bolster other institutional priorities. As a key aspect of educational reform and institutional improvement, learning analytics are essential to defining the value of higher education, and academic librarians can be both of great service to and well served by institutional learning analytics teams. In addition, librarians who seek to demonstrate, articulate, and grow the value of academic libraries should become more aware of how they can dovetail their efforts with institutional learning analytics projects. However, all too often, academic librarians are not asked to be part of initial learning analytics teams on their campuses, despite the benefits of library inclusion in these efforts. Librarians can counteract this trend by being conversant in learning analytics goals, advantages/disadvantages, and challenges as well as aware of existing examples of library successes in learning analytics projects.
Learn about the state of the art in learning analytics in higher education with an emphasis on 1) current models, 2) best practices, 3) ethics, privacy, and other difficult issues. The webcast will also focus on current academic library projects and successes in gaining access to and inclusion in learning analytics initiatives on their campus. Benefit from the inclusion of a “short list” of must-read resources as well as a clearly defined list of ways in which librarians can leverage their skills to be both contributing members of learning analytics teams, suitable for use in advocating on their campuses.
student’s opinion of this process
benefits: self-assessment, personal learning, empwerment
analytics and data privacy – students are OK with harvesting the data (only 6% not happy)
8 in 10 are interested in personal dashboard, which will help them perform
Big Mother vs Big Brother: creepy vs helpful. tracking classes, helpful, out of class (where on campus, social media etc) is creepy. 87% see that having access to their data is positive
recognize metrics, assessment, analytics, data. visualization, data literacy, data science, interpretation
INSTRUCTION DEPARTMENT – N.B.
determine who is the key leader: director of institutional research, president, CIO
who does analyics services: institutional research, information technology, dedicated center
analytic maturity: data drivin, decision making culture; senior leadership commitment,; policy supporting (data ollection, accsess, use): data efficacy; investment and resourcefs; staffing; technical infrastrcture; information technology interaction
student success maturity: senior leader commited; fudning of student success efforts; mechanism for making student success decisions; interdepart collaboration; undrestanding of students success goals; advising and student support ability; policies; information systems
developing learning analytics strategy
understand institutional challenges; identify stakeholders; identify inhibitors/challenges; consider tools; scan the environment and see what other done; develop a plan; communicate the plan to stakeholders; start small and build
ways librarians can help
idenfify institu partners; be the partners; hone relevant learning analytics; participate in institutional analytics; identify questions and problems; access and work to improve institu culture; volunteer to be early adopters;
questions to ask: environmental scanning
do we have a learning analytics system? does our culture support? leaders present? stakeholders need to know?
questions to ask: Data
questions to ask: Library role
learning analytics & the academic library: the state of the art of connecting the library with campus initiatives
7 Things You Should Know About First-Generation Learning Analytics. Published:
causation versus correlation studies. speakers claims that it is difficult to establish causation argument. institutions try to predict as accurately as possible via correlation, versus “if you do that it will happen what.”
Our expert panelists weigh in on education technology to give us their verdict on which approaches to tech-enabled learning will have a major impact, which ones are stagnating and which ones might be better forgotten entirely.
Social Media for Teaching and Learning: Lukewarm to Hot
Digital Badges: Mostly Lukewarm
Open Educational Resources (OERs): Mostly Hot
E-Portfolios: Losing Steam
Learning Management Systems (LMS): Lukewarm to Hot
Flipped Learning: Mostly Hot (but Equitability a Question)
Blended Learning: Unanimously Hot
Student Data Privacy Concerns: Unanimously Hot
Apps for Learning: A Mostly Lukewarm Mixed Bag
Games for Learning: Hot
What are the hot devices?
Cameras like the Canon VIXIA, the Sony HDR-MV1 or the Zoom Q4 or Q8 range from $200 to $400. The secret of these small devices is a tradeoff between video flexibility and audio power. With digital-only zoom, these cameras still deliver full HD video (or better) but with limited distance capabilities. In return, the audio quality is unsurpassed by anything short of a professional boom or wireless microphone setup; most of these cameras feature high-end condenser microphone capsules that will make music or interview recordings shine.
The Chromebook is hot. Seventy-two percent of Chromebook sales were education-related purchases in 2014.
The smartphone is hot. Every day, the smartphone becomes less of a “phone” and more of a device for connecting with others via social media, researching information on the Internet, learning with apps and games and recording experiences with photos and videos.