# data[].attributes.body
How do you think privacy will become an issue with an interconnected eLearning standard?

From: Reg Surette

Internet security is an ever-growing discussion among large online corporations such as Facebook (who has recently been reported to be in negotiations to acquire a cyber-security firm!). With respect to the eLearning courseware itself, proprietary content will undoubtedly have encrypted access, which begs the question if this will be the norm, how will courseware ever be standardized?

With regard to course content and user privacy concerns, these will continue to be a concern when online. Going forward, I’m of the opinion that personal encrypted access to basically anything online will become the norm. Our students have personal logins to access the LMS course content, and how we log in to Google or Facebook. Perhaps the login features will also evolve to become increasingly secure as well. If eLearning standardization is adopted any capacity, I suspect there will be end-user encryption requirements and secure access for these, as well as server security.

Beyond this, I’m far from a privacy and security expert, so I’m eager to read what others have to say on this topic! Thanks!

# data[].attributes.body
Philip Barrington
It is possible but I do think that it is still 50 + years away at least. The technology is there but teachers and students still want the one on one interactions. That connection is not possible with eLearning scenarios just yet.
It is why developers need to provide that personal connection in terms of interaction, to truly see eLearning fully embraced by the educational fields.

# data[].attributes.headline
'Is the data from a user's elearning record enough information to make sound decisions?' (by Kate Quinn)

# data[].attributes.subject
'Is the data from a user's elearning record enough information to make sound decisions?' (by Kate Quinn)

# data[].attributes.body
Ingrained in this question and answer is the underlying question about data in general - how much is too much? How much is too little? How do we shape it through context or application? The data from an elearning record could be a ton of useless information, or could provide important information if conveyed properly. Is it enough to know that a candidate has a BComm in Finance? We don't have enough information about the candidate, or the position, to answer that question. One common pitfall of believing in the affordances of data is forgetting that all data must be interpreted. If LRSs are standardized, surely this will tell someone who knows little about an employee or candidate more about their skills, habits, or qualities - at least, in the digital realm. Would these same qualities be evident based on a quick face-to-face interview? Perhaps. I believe if LRSs are standardized and interpreted properly, we'll surely have a better picture of potential or unknown employees than we would based on their traditional credentials (diploma, degree, certificate ...), but that much of this data may be redundant for those working in close proximity to each other or in small businesses. At the end of the day, the performance of a learned skill should be more important than the time took / times clicked / sites accessed in order to be able to DO it. I believe ultimately companies will continue to focus on professional performance and output rather than tracking learning.

# data[].attributes.headline
Response to "Is this data from a user's elearning record..."

# data[].attributes.subject
Response to "Is this data from a user's elearning record..."

# data[].attributes.body
I think a really great point is made here (which supplements an xAPI caveat noted in the xAPI YouTube video/tutorial provided): Data is meaningless without proper interpretation. Data is easy to collect, and hard to interpret. Could LRS standardization help this? Maybe... but are all implementations of xAPI standardized? Do all eLearning scenarios require similar data, or specialized data? Suppose we collect "all data", and then the data is interpreted later through a filter of whatever is relevant for a future company. Would this be OK? Or would the suggestions provided by the data be skewed? I think here, like many situation, a balance is required. Data should not be a be-all end-all representation of a candidate's abilities or accomplishments, but should serve as another lens through which we can understand their background. Perhaps the data could be used in conjunction with some sort of performance/ability assessment?

# data[].attributes.headline
Possible in the distant future, not probable in the near.

# data[].attributes.subject
Possible in the distant future, not probable in the near.

# data[].attributes.body
Based on current technology standards I believe the full SDL version of what we just viewed is possible, but not for a longer period of time. I greatly appreciated the clear and concise feedback application that was presented as well as the algorithmic aspect that involved highlighting the text for submission. This sophistication of data recording, I believe is accessible in the near future.  The V/R aspect, however, is a different story.  Aside from technical hurdles, coming from a K-12 background there a number of other concerns to take into consideration.  Tanner Higgin provides a good insight into the other aspects that should be taken into consideration when implementing V/R into a classroom setting.
https://www.commonsense.org/education/blog/what-the-research-says-about-vr-in-classrooms

Higgin, T. (2018, April 17). What the Research Says About VR in Classrooms. Retrieved October 24, 2018, from https://www.commonsense.org/education/blog/what-the-research-says-about-vr-in-classrooms

# data[].attributes.body
Dustin Hyde: Check out Mel's website. She has a variety of different xAPI programs in her portfolio. Browsing through her portfolio helped me better understand xAPI initiatives in different fields.
http://melslearninglab.com/portfolio

# data[].attributes.attachment_link.description
Melissa Milloway is an instructional designer at Amazon in Seattle, WA. She specializes in designing and developing learning experiences and blogging about it.

# data[].attributes.headline
Espresso Matchmaker - a fun example of xAPI

# data[].attributes.subject
Espresso Matchmaker - a fun example of xAPI

# data[].attributes.body
Dustin Hyde: Who doesn't love a good coffee? The question is, what type of coffee is best tailored for you? Take this quick and fun xAPI created espresso matchmaker to find out what the best type of coffee is based on your preferences.  Link here:
https://s3-us-west-2.amazonaws.com/storylinexapiexample/Espresso-Matchmaker/story_html5.html?endpoint=https://melmilloway.waxlrs.com/TCAPI/&auth=Basic%20b0tJSU5GaTN4M1FZanJveUY5YXo6TUdxcTc1cGE3NTZMZGgyOXZaVTQ=&actor=%7B%22mbox%22:%5B%22mailto:user4692@test.com%22%5D%7D&activity_id=http://espressomatchmaker.com

# data[].attributes.body
Feel free to add any other comments or insights you might have to the conversation.

# data[].attributes.headline
Some questions to get a discussion going?

# data[].attributes.subject
Some questions to get a discussion going?

# data[].attributes.body
How do you think that privacy will become an issue with an interconnected eLearning standard?

# data[].attributes.body
Is the data from a user's elearning record enough information to make sound decisions?

# data[].attributes.body
How many years away do you think a e-training scenario such as this is?