Category: Digital literacy

Helping learners contemplate the truthfulness of information is becoming an important objective for educators. The focus has frequently been on evaluating the value of a single source. A different perspective might target knowledge of the orientation taken by sources. The reality is that sources may align themselves with different political perspectives – liberal or conservative – and slant their messaging accordingly. This is often described as spin and concerns not so much the factual accuracy of what is reported, but what is emphasized or ignored and how the facts offered are explained.

Attempts to identify how different news sources exist and one of the most useful in my opinion comes from adfontsmedia. This organization categorizes sources along multiple axes – reliability and bias (spin). Within this two dimensional space the organization positions sources you likely know (e.g., CBS, Fox News, CNN) and some you don’t (e.g., Alternet, Info Wars). The methodology used to position news outlets is based on expert analysis of a sample of multiple articles from sources. The organization offers educators both free and paid resources for classrooms.

Nowhere News is a recent news service attempting to use artificial intelligence to identify bias in news. The service accesses a large number of news services and identifies popular stories of the day. The service than uses the content from multiple services to create a neutral account and also generates a right-wing and a left-wing version (or positive and negative view if more appropriate). The developers have weighted the sites they access by reputation for accuracy and do review and edit the generated summaries before publishing. 

I read multiple descriptions of Nowhere News to try to understand more about what the AI is doing [ TechCrunch, Singularity Hub, Vice]. Services that summarize web content have been around for several years. One approach might involve summarizing multiple accounts from news services known to have right, left, and neutral biases. This does not seem to be what is happening here. As I understand AI, you input many signals and identify a characteristic of the source (in this case, right, neutral, and left) and the system learns how to use the signals to more and more accurately predict the designated category. I am not certain this appropriately summarizes what has been done here.

However generated, the three versions of a story generalized from multiple sources would seem to have some educational value. Just reading the three summaries offers readers insight into what bias means. [see Common Sense Media comment on educational potential].

At present the Knowhere News site is free and I would assume would eventually need to find some way to monetize. If you enroll as a user, you receive emails with story summarizes. You can also just visit the site and read the stories summarized for a given day.

This service is interesting and useful. I doubt it could be regarded as a solution to the fake news crisis.  First, I don’t see brief summaries the equivalent of reading long-form news stories. Knowhere does provide links to multiple sources, but often not to sources I would read. I am not clear how major news sources with some version of a pay to read model regard content being used in this way. Second and as acknowledged by Knowhere, there is a difference between bias (spin) and quality. See my previous post.

I was working on the revision of our textbook today and focused the cyberbullying content. This topic has been a favorite since a student with this interest got me into doing research in this area. There are some issues that make decisions as to how teachers should address this problem kind of interesting. First, cyberbullying very seldom happens when teachers have responsibility for monitoring student behavior. The bully and the victim know each other through school, but cyberbullying most often happens when students are not in school. This can make it a tough call to take action that involves reprimands as part of school because parents may take the position that such action oversteps the appropriate authority of the school. As I remember some of the legal positions that allow action, the school can argue that there are consequences that affect the victim’s behavior while at school. Of course, this has to be the case.

Today I encountered a second issue while trying to argue a second challenge. Victims can be targets of some form of bullying as a consequence of religion, sexual orientation, or politics. Educators probably recognize that these are issues that they can be expected to avoid or at least be very careful with in their classrooms.

The inclusion of politics on my list of topics to treat with care probably does not surprise educators, but how is this relevant to cyberbullying? I decided to include it in the comments I was adding to my material on cyberbullying after reading a study by Huang and colleagues. Here is the section I wrote.

Topics and differences of opinion that can trigger bullying may be difficult for educators to address without stepping over what others see as boundaries. Such topics would include religion, politics, and sexuality. For example, after the election of 2016, researchers published findings (Huang & Cornell, 2019) relating differences in teasing and bullying among adolescents to the favored candidate in the district within which students attended school. It is easy to imagine how students could be disappointed when their teachers seemed to ignore what the students perceived as hurtful taunts. Efforts at intervention, no matter how carefully expressed, could easily be misconstrued by others emotionally involved in a position. How would parents react if bullies claimed teachers were being critical of student use of the same behaviors everyone was witnessing on television? You are living in this same world and can imagine or have witnessed students picking up on the name-calling politicians employed. What to say when this language is used in your classroom and perhaps to mock students who have strong opinions?

Here is what I avoided saying. The study contrasted bullying behaviors following several elections as a function of the political party most commonly represented in school districts. The election of 2016 was unique for an increase in bullying behavior. Guess the political party affiliated with this differential increase in bullying.

I considered a heading for this section that read – The President is a Jerk. Don’t be like him. Despite his wife’s puzzling anti-bullying #bebest campaign which I admit really annoys me, I gave in to my professionalism and wrote something that was much more neutral. I keep trying to decide if this was the appropriate “educational” thing to do. The data are right there and aren’t we supposed to be scientifically accurate in how we educate? Maybe I will use a neutral title and report the party affiliation as identified by the researchers.

Huang, F. L., & Cornell, D. G. (2019). School teasing and bullying after the presidential election. Educational Researcher, 48(2), 69-83.