Google recently announced that you can now add comments to images in your Google Drive. This simple addition offers many creative possibilities.
In the example below, I've taken an photo of a bulletin board and turned it into a virtual bulletin board. Clicking on different items in the images brings up videos, documents (Pdfs), or allows you to vote.
The next example shows how you might use an image to create a virtual board game. Links and instructions can be inserted into the comments. Links can be of videos, map locations, dice rolling tool, etc.
Add comments to visual work like drawings/paintings for both formative and summative assessment
Give feedback to math work (Hint: have students use smart phones to easily grab "scans" of their work) Remember, viewers can interact using comment threads.
Give feedback to students using photos of them performing (e.g. PE, music, drama...) Improve quality of feedback by selecting specific areas of the image (e.g. select wrist with comment tool to comment on how student hits ball with racquet)
Use an image of a map to create a multimedia guide linking to videos, other images, sites...
Create a Prezi-like presentation using large images (students could draw these, Photoshop them, etc.), linking to multimedia files, sites, etc. in comments. Hint use View-->Show Image Navigator for large images. This allows users to zoom in and navigate large images.
Starting Feb 28, Bill Farren will be offering mini-lessons about a variety of tech subjects to those in the middle school who are interested. In order to try to accommodate people's schedules, each lesson will be offered at three different times (8:00-8:20 a.m., 12:05-12:25 p.m., 3:40-4:00 p.m.) every Thursday from Feb. 28 to May 9. Materials for each lesson will be posted on the AISB Tech Blog. This will allow, in the comments section of each lesson blog post, for people to join in on the conversation. Lessons can be found quickly by clicking on the tech_thursdays label (tag) on the right of the blog where Labels are located. Participants may be asked to watch videos posted on the blog prior to each lesson. Learners will also be encouraged to make their own posts to the blog, deepening their own learning as well as that of others.
Staff who participate will be recognized publicly so that 1) we can appreciate their efforts, and 2) so others can ask them for assistance and guidance when needed. Any staff member who believes they are proficient in any of the lesson areas and would like to be recognized for their skills, can post some tips, ideas, reflections, samples, etc. which can be of help to other learners and which show significant understanding of the subject. Their abilities and skills will be visible to others through their engagement in the blog. Clearly, people have different levels and areas of expertise. We want to honor these differences by providing individuals with different learning opportunities and ways to express what they know and can do.
Lessons Schedule:
Week 1 - Feb 28 - Social or Networked Learning
Week 2 - Mar 7 - Using an Electronic Portfolio
Week 3 - Mar 14 - Tools for Capturing, Annotating and Sharing Information Found Online
Week 4 - Mar 21 - Using Google Forms for a Variety of Purposes
Week 5 - March 28 - Sharing / Borrowing / Remixing: Copyright in the 21st Century Week 6 - April 11 - Evaluating information found Online (Wikipedia: What’s its role?)
Week 7 - April 18 - Using Google Spreadsheets and Charts
Week 8 - April 25 - Using Smartphones and Tablets as Quick and Easy Recorders/Scanners for Images, Audio, and Video.
Week 9 - May 2 - Google Drive Fundamentals
Week 10 - May 9 - YouTube as a Learning Tool
*Week 11 - Bonus, if Desired - May 16 - Google Docs (text docs): Become a Power User
I recently read a book by Ray Kurzweil where he states that today's artificial intelligence (AI), like that found in Watson, is not artificial. Today's AI recognizes patterns and analyzes them hierarchically, just as it is argued, the human brain does. Machines can learn on their own after being set up with some learning algorithms (just like the human mind which is set up to learn following instructions it acquires from DNA). Systems like Watson have read huge volumes of information that are available online such as all of Wikipedia, using natural language to teach itself.
What used to be thought of as off limits for machines--knowledge work--is now squarely within its capabilities. How does this change what we teach and how we teach? Does it matter?
AI and machine learning are finding their way into a variety of applications. It can be found in cars that learn to drive (safely), in speech recognition software, in facial recognition, search and recommendations, and many others. While these are amazing technologies, they are also very disruptive. Many jobs that we take for granted right now may not be around for too much longer. Some examples are drivers (taxi, mail delivery, truckers...), displaced by autonomous vehicles. Or translators, displaced by machine translation. Or paralegals sifting through documents for discovery. How will a system like Watson change medicine? Who will have the better medical diagnosis: Watson, who has read every medical journal available, every newsfeed published online, calculated millions of possibilities using advanced statistical analyses (unhindered by emotion), looked at the most recent disease patterns using geographic information systems... or your doctor? Who will make better financial decisions, Watson, or your financial consultant? My guess it's that it will be those who can skillfully use machines to extend their capabilities--what's been called the cyborg advantage. At least for now.
"...our assumptions about what machines can and cannot do are urgently in need of updating." source
Machine learning:
The Google brain assembled a dreamlike digital image of a cat by employing a hierarchy of memory locations to successively cull out general features after being exposed to millions of images. The scientists said, however, that it appeared they had developed a cybernetic cousin to what takes place in the brain’s visual cortex. source
"Never before in the history of computing has a machine been able to so precisely answer such a wide breadth of questions in such a short time." (from video below) "Watson knows what it knows, and knows what it doesn't know." [self awareness?] (from video below)
