Get Started for FREE
Sign up with Facebook Sign up with X
I don't have a Facebook or a X account
 Your new post is loading...
Your new post is loading...
Scoop.it!
A majority worries that the evolution of artificial intelligence by 2030 will continue to be primarily focused on optimizing profits and social control. They also cite the difficulty of achieving consensus about ethics. Many who expect progress say it is not likely within the next decade. Still, a portion celebrate coming AI breakthroughs that will improve life 
No comment yet.
Sign up to comment
Scoop.it!
Back in May, my university - like many Canadian institutions - announced we’d be going online for fall. It was the right decision: students, faculty, and staff have remained safe, in terms of the coronavirus. But as campuses across the continent and around the world have shifted to online learning, it’s become clear that institutions - and many of us who work within them - may be oblivious to a very different safety risk, one that’s amplified in recent months. The pandemic has fast-forwarded higher education’s entanglement in proprietary, datafied systems, but the sector has failed entirely to grapple with how data impacts what we do. Sure, most of us know at some level that we are fish swimming in increasingly datafied waters. Our devices track our searches and our locations and even our casual offline conversations, pitching products we’ve just spoken of back to us on social platforms.
Scoop.it!
The growth and development of learning analytics has placed a range of new capacities into the hands of educational institutions. At the same time, this increased capacity has raised a range of ethical issues. A common approach to address these issues is to develop an ethical code of conduct for practitioners. Such codes of conduct are drawn from similar codes in other disciplines. Some authors assert that there are fundamental tenets common to all such codes. This paper consists of an analysis of ethical codes from other disciplines. It argues that while there is some overlap, there is no set of principles common to all disciplines. The ethics of learning analytics will therefore need to be developed on criteria specific to education. We conclude with some ideas about how this ethic will be determined and what it may look like. Via Ana Cristina Pratas
Scoop.it!
Students do know what is wrong and right for themselves in their own contexts, but very often they also need guidance to think critically through situations which may or not affect them directly., yet are present in our world. Reflecting and thinking critically through contemporary issues related in ethical behaviours helps learners explore their own values more clearly and perhaps, even open their eyes to other ways of perceiving the world.
Scoop.it!
"Learning analytics provides tremendous opportunities to assist learners - but they also pose ethical implications you shouldn’t ignore." Via EDTECH@UTRGV
Scoop.it!
This paper discusses plagiarism origins, and the ethical solutions to prevent it. It also reviews some unethical approaches, which may be used to decrease the p
Scoop.it!
Christoph Meier's curator insight,
December 5, 2014 2:14 AM
Ein umfangreicher Bericht (ca. 60 Seiten) zu rechtlichen bzw. Datenschutz-Aspekten im Zusammenhang mit Learning Analytics
Scoop.it!
Massive open online courses (MOOCs) are still pretty new but more and more universities, platform providers and publishers are beginning to create MOOCs to raise their profile and showcase high-quality materials. But there is a risk that reputations can take a serious hit if materials and data are being used incorrectly, or without permission. The time to make sure your institution is squeaky clean is NOW, says David Kernohan, Jisc programme manager, e-learning.
Scoop.it!
Ethical decision-making should be included as a 21st century skill (overused term but don't know of an alternative). Some would profess that ethical decision-making has always been a needed skill....
|
Scoop.it!
Equity and privacy problems with online proctoring reflect a larger issue: Students look to universities to set an example of integrity.
Scoop.it!
It has been a few weeks since we issued our #DigCiz call for thoughts on the question “What do we owe students when we collect their data?” and there have been a few responses. The call is in conjunction with the interactive presentation at the EDUCAUSE Annual Conference that I’ll be helping to facilitate with Michael Berman, Sundi Richard, and George Station. The session will be focused around breakout discussions both onground and online during the session. We don’t necessarily have “answers” here – the session (and the call) are more about asking the questions and having discussion. The questions are too big for one session and often there are not easy answers; so we released the call early hoping that people would respond before (or after) the session. I’ve yet to respond to it myself so I’m going to attempt to do that in this post.
Scoop.it!
The 2020 list of EDUCAUSE’s Top 10 IT Issues provides evidence that the higher education IT community is increasingly focused on using technology to better understand students and rethink systems, culture and process to improve student success. This focus is especially critical when it comes to using student data to improve retention and completion rates. To develop the capabilities and systems that can provide students with personalized, timely support, institutions need to understand how data technology, such as predictive analytics, can address the factors that lead to student success. They also must know how to use information from institutional data to introduce changes that promote sustainable, effective and efficient practices, while considering students’ experiences and needs as their starting point.
Scoop.it!
In this paper, the authors address learning analytics and the ways academic libraries are beginning to participate in wider institutional learning analytics initiatives. Since there are moral issues associated with learning analytics, the authors consider how data mining practices run counter to ethical principles in the American Library Association’s “Code of Ethics.” Specifically, the authors address how learning analytics implicates professional commitments to promote intellectual freedom; protect patron privacy and confidentiality; and balance intellectual property interests between library users, their institution, and content creators and vendors. The authors recommend that librarians should embed their ethical positions in technological designs, practices, and governance mechanisms.
Scoop.it!
I’m growing increasingly uneasy over and frightened by the escalating pervasiveness of academic dishonesty. Statistics fluctuate and are difficult to come by, but according to one 1998 study, conducted by the Ad Council and The Educational Testing Service, upward of 98% of college students report having cheated in high school.
Scoop.it!
tThis policy aims to set out how the University will use student data in an ethical way in order to shape the student support provided. The policy is based around eight key principles, each of which is linked to particular aspects of learning analytics.
Scoop.it!
Library ethnography is a relatively low-risk field. We are, as researchers, observing public behavior in public spaces, and asking people about what they do in the pursuit of their academic goals. ...
Scoop.it!
This interactive tutorial is aimed at all students and describes what plagiarism is and how to avoid to it. The importance of academic integrity is also highlighted and users are also introduced to plagiarism detection software, Turnitin. The tutorial contains quizzes and interactions and the user in given the opportunity to work through the tutorial in a self paced manner.
|
