Category: Digital literacy

Skill in locating, evaluating, and applying information obtained from the Internet.

AI writing is here – teachers be aware

I intend this post as a public service announcement of a sort for educators at all levels. If you have not personally explored AI assisted writing, you need to do so. I will explain how. I say this because your students will soon explore AI services that will generate written products for them and you will have to adjust how you think about writing assignments as a consequence.

My suggestion is that you give a service called ChatGPT a try. Sign up and get a free account. The service is very easy to use. Once you have an account, you simply enter a description of what you want into a text box and wait for a reply. I think the sophistication of what is generated is likely to shock most and this reaction should cause you to consider what access to a service like this means for the tasks you describe in your classroom.

Here are a couple of examples. These examples relate to topics I might raise in a graduate educational technology course. My point is these are challenges I might offer students first to see if they understood a topic we had covered and then if they could connect this topic to other cognitive phenomena.

Me: What is a semantic network?

ChatGPT: A semantic network is a graph-based representation of a knowledge domain. It is a way of representing structured knowledge by modeling the relationships between concepts. In a semantic network, concepts are represented as nodes in the graph, and the relationships between concepts are represented as edges that connect the nodes. This allows for the representation of complex ideas and their relationships in a clear and intuitive manner. For example, a semantic network could be used to represent the relationships between different types of animals, their characteristics, and the ways in which they interact with each other.

Me: How can a semantic network explain the tip of the tongue phenomenon?

ChatGPT: The tip of the tongue phenomenon, also known as “TOT,” is a common experience in which a person knows that they know a word or a piece of information, but they cannot recall it at the moment. One possible explanation for this phenomenon is that the information is present in the person’s semantic network, but it is not easily accessible at the moment. In a semantic network, information is typically represented as nodes in the graph, and the connections between these nodes encode the relationships between different pieces of information. When a person experiences the tip of the tongue phenomenon, it may be because the information they are trying to recall is present in the network, but the path to access it is not easily accessible. In other words, the person knows that the information is there, but they cannot retrieve it easily because the connections between the relevant nodes in the network are not strong enough.

Me: Can the semantic network explain the testing effect?

ChatGPT: Yes, the semantic network can help explain the testing effect, which is the phenomenon whereby taking a test on material improves subsequent recall of that material compared to simply studying the material. The testing effect is thought to occur because taking a test forces a person to retrieve information from their memory, which strengthens the connections between the relevant nodes in their semantic network. This makes it easier to access the information in the future.

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Just so you appreciate what you are reading try this. Take the final question “Me: Can the semantic network explain the testing effect?” and enter it as a Google search. You will generate plenty of hits, but the hits are not really answers to the question. The hits at the top of the list I received were explanations of what a semantic network is and represented content I would have to read to generate an understanding. I did find an explanation of what the testing effect is in another hit further down the list. I did not find a resource near the top of the list that would cover a possible connection between the two. Educators may be familiar with the testing effect, but why it works so successfully is fairly speculative. I explain it by connecting the concepts of a networked associative model of memory and the cognitive mechanisms of the retrieval process which is kind of what I would be looking for if I had asked the question of students who have discussed these concepts with me. I was impressed AI put it together in a similar way.

So, AI writing is not simply retrieving what someone else has written (search), but is building from a huge collection of content at a more abstract level.

So? Well, students can “write” impressive products by giving an AI bot instructions. They may do this because they want to read how the AI bot generates a response they would find informative (Note: Search may soon be replaced by this type of AI process because it answers questions rather than just providing resources you can use to answer them yourself). AI can be your teacher.

However, if you are teacher using writing to evaluate learning or writing skill or if you are a teacher using writing as a way to encourage student learning (writing across the curriculum), the “writing” generated by AI is a challenge for you. It does not require much from the student in terms of content review, application of writing skills, or personal understanding. Like math teachers who figured out students could take a picture of a problem the students were assigned and have an online service solve it and show a solution process, you are now dealing with a new reality. Writing extended content is also a process that is much more difficult to monitor. You can watch students write a theme in class, but a research paper is a different beast.

Let’s start with this. Take some time to explore ChatGPT. You really need this personal experience to understand present capabilities. Don’t start by thinking how you might ban access. This will not be realistic AND it ignores the positive opportunities this type of tool offers. Are there opportunities you can think of? Now, what about limitations? What about citations? This service strikes me as a very intelligent colleague who can spout off on nearly any topic, but leaves me with little I can read and consider myself. How could I as a writer even use content a service like this might generate in something I would write? How would I justify the statements made? My first reaction is that educators review what they know about the Flower and Hayes writing process and consider what tangibles they might ask students provide at each stage of the process. For example, what are the notes they generated from the sources they intend to cite in their final product. How did they put these notes together in getting to this final product?

One more thing. I wrote a previous post about ChatGPT for Medium and in this post I included the response to a question about how AI writing might limit what students learn from writing themselves I asked of ChatGPT. I thought the response was quite useful and honest (now I am anthropomorphizing). Honesty is not always something you get with human authors.

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Twitter Manipulation

We are now in the heat of election season and social media sources are constantly feeding us ads attempting to encourage our vote for one candidate or another. In general, I don’t find short-form ads very useful. There is a statement intended to impact me in some way or another and little in the way of justification or evidence. Twitter must fall into this approach because of the length of messages that are allowed.

I think political season offers a great opportunity to explore social media and consider how the algorithms and our own choices may mislead us. I have two explorations to suggest.

Twitter with and without the algorithm

The default in Twitter makes use of an algorithm to prioritize what we see in our feed. In other words, the algorithm decides what will appear at the top of the feed and content assumed to be less interesting based on our past behavior will appear further down as we scroll.

It turns out we can turn this algorithm off and if we decide to do so the content in the feed will be arranged chronologically. In other words, the feed is arranged based on when our friends generated tweets.

It is interesting to compare these feeds. Here is how.

At the top of the Twitter display, you should see what I describe as stars. If you hover over this icon you will see your current setting. In the image below, you can see I have my feed set to the chronological option.

If you click on the “star” icon, you will find a way to activate the other display option. In this case, it would be the algorithmically driven alternative. Toggling back and forth gives you a feel for how you have been categorized by the algorithm.

What are the other folks posting to Twitter.

The Polarization Lab at Duke University has been investigating how social media exposure increases or decreases existing political extremism. I review some of the tools they make available and some of the research they have conducted in an earlier post.

One of their more interesting experiments involves the use of bots they have created to forward the input from moderate liberals and conservatives. They propose that exposure to extremists of either orientation leads to greater polarization, but exposure to moderate positions taken by those with a different position than your own may lead to a lessening of polarization.

I have been following both Twitter bots for several months now. You can participate as well. If you don’t want to participate, you call always search for one of the bots just to see how the feeds from moderates of both perspectives differ.

@Polly4Conserv – for liberals to learn about moderate conservatives

@Polly4Liberals – for conservatives to learn about moderate conservatives

Educators looking for an interesting project might ask students to come up with a system for studying political orientation and apply this system to the two different sets of tweets.

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Depolarization

I became interested in the work of the Polarization Lab after reading “Breaking the social media prism”. They propose that social media tools like other tech tools are potentially neutral, but do have great power for negative outcomes. It depends on how tools are used.

The lab is interested in studying social media polarization and testing ways to fight the trend toward polarization. How might more moderate positions be viewed and considered and how to fight the tendency to spiral toward extremism. One of the experiments involves the use of Twitter bots relaying tweets from moderate “opinion leaders” of different orientations toward participants identified as having an opposing perspective. The logic is that such content may moderate disagreements.

It is easy enough to follow these bots yourself. I thought that signing up for both bots and analyzing the content of what is shared could make a great student project or start a classroom conversation. The Twitter “handles” are @Polly4Liberals and @Poly4Conserv. I identify as a liberal so Polly for Liberals sends me “messages from prominent conservatives or right-leaning organizations”. The research body followed me back because I registered and I assume is attempting to see if the Twitter behavior I exhibit becomes more moderate.

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Learners need to learn to read from both paper and the screen

Cohn (2021) argues that we read in different circumstances for different purposes and yet we tend to teach reading as if reading is a single skill. Learners would be better served if they were to be guided to explore the different types of reading they do and what tools and tactics would be best suited to these different circumstances.

This idea is important. We read for many different purposes. Do we think about which approach best serves a given purpose? As an adult thinking about my own reading behavior, I can see this complexity. I very seldom purchase a paper product for reading. There are still a wide variety of ways in which I read digital content. I read some online content and by that fact that are reading this post, so do you. How about books? I read digital books when I read to acquire information especially when I intend to store specific information for later use. I listen (audiobooks) when I read for pleasure. The read to learn versus read for pleasure is a common distinction many recognize, but college study skill experts suggest that students often struggle with acting upon this distinction in their efforts to learn from their textbooks.

If we are educators, do we consider factors as basic as the physical circumstances that impact how and when their students or themselves read. Do we want to read in a coffee shop, a library, or at our desk? When do we want absolute quiet and when is some music or coffee shop banter in the background welcomed? Perhaps the noise in a coffee shop distracts us from time to time and these interruptions provide the signal to reflect on what we are reading rather than continuing to plow ahead. We may ignore the physical realities of reading that some students must consider. Perhaps some must read on their phones on the bus or train because this is when they have the opportunity to work on class assignments. Perhaps their phone is the only device they have that can be applied in these circumstances. 

How we understand what reading involves matters. Cohn (2021) offers a set of reading goals that may or may not be accepted by the reader. The final purpose she describes is creativity. Her definition is a little different than the way I tend to think of the concept, but she proposes creativity involves the understanding that reading should result in the building of new knowledge. She argues that when we read we may not see the benefit of creating something after we read as if reading should be enough. My take on this expectation brings to mind distinction between reading for understanding and retention and pleasure. Extra effort is obviously involved when the goal is creating something even when this is not a written product. Do others not think in this way?

Chon argues that most readers and writers understand that reading and writing are knowledge transmission acts, but proposes that they should be understood as knowledge construction. This difference encourages additional processing and the utilization of additional tools. This is where instruction in the use of such tools comes in. Do teachers teach the application of such tools? Which teachers and in which subject areas? Note-taking is one activity that recognizes the connection of ideas across sources and with existing knowledge. Note-taking is another of those practices that can involve either paper or digital technology. The skills involved in these activities offer a great deal of overlap, but digital tools offers some unique advantages in storage, organization, and search aid retrieval. 

Chon proposes that educators make inaccurate assumptions about learning skills such as highlighting, annotation, and note preparation and use. She offers an example in which she  began asking her students if they had experience using pdf tools to highlight and annotate assigned content. She had been assigning pdfs and had begun to wonder how students processed these resources. She reports that 30% responded that they were highlighting and annotating the assigned material and many were unaware such tactics were possible. Her point was that educators (she teaches at a university) should not assume that computer experienced students have skills appropriate to making use of digital tools with such assignments. It struck me that this question should be asked for more educators assigning digital content.

After reviewing several sources proposing how educators might help students develop annotation/note-taking skills (also sometimes labelled as deep reading), I have begun interpreting the instructional tactics as a variant of reciprocal teaching. As instructional strategy, reciprocal teaching begins with the teacher modeling a specific skill accompanied by “thinking aloud”.  Individual components or subskils are then assigned to individual students and applied to a common reading assignment. Student experiences and any products produced are shared and discussed. Finally, students move on to the application of the combination of practiced skills and seek assistance when necessary.

With highlighting and note-taking, the skills are a bit different from those emphasized in the original focus on reading comprehension. However, the general process of teaching/learning is very similar. For example, with note-taking, the components might include the identification of essential information, the summarization of these key ideas, and efforts to cross-reference these ideas to existing knowledge and other inputs (ideas presented in class, other reading assignments). When learning these skills, some educators recommend the use of printed material before moving to digital content. Sharing individual student efforts perhaps as displayed on a classroom white board allows for discussion and analysis. 

The sources I provide below provide multiple examples of how this generalized strategy can be implemented. I understand that many may not want to purchase this material. I was able to find an alternate source for “Beyond the Yellow Highlighter”. Searching for this title should also reveal discussion and examples of implementation shared by other educators. 

Cohn, J. (2021). _Skim, dive, surface: Teaching digital reading_. West Virginia University Press.

McIntosh, J. (2019). Clip, Tag, Annotate: Active Reading Practices for Digital Texts. In _Digital Reading and Writing in Composition Studies_ (pp. 176-188). Routledge

Porter-O’Donnell, C. (2004). Beyond the yellow highlighter: Teaching annotation skills to improve reading comprehension. _English Journal_, 82-89.

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The advantages of digital reading

In the past year or so, I am guessing educators have become aware of a controversy related to whether learners are best able to learn from content presented on paper or a screen.  I am certain some researchers will continue to compare the comprehension of content appearing in a book versus on a screen, but whether or not such research reaches a conclusion one way or the other (see reference from recent meta-analysis), we have already switched to heavily relying on information we can access from our devices. It makes more sense to accept that learning with a phone, tablet, or computer will be involved in a significant proportion of our learning experience and consider how best to use the unique capabilities of these devices. What does digital reading look like and what presently neglected skills are being ignored that educators can help learners acquire? 

I do many different kinds of reading and I think this is true of many learners. I read for pleasure and I read to learn. Those who study reading probably can come up with many more meaningful categories, but these two are sufficient for my argument. I like to describe these reading activities as associated with shallow and deep goals. Some who study different reading activities seem to describe deep reading a little differently than I do. My use of the term implies the intent to learn, retain, and apply information gleaned from reading. I also see an opportunity for digital reading when retention and application follow initial exposure to text by longer periods of time than would be involved in the delay until the next examination. A unique advantage of digital reading is the opportunity to externalize immediate insights and personal interpretations in ways that take advantage of storage, organization, and search capabilities of technology. Some describe this as using technology as a second brain. Accept that human memory is far from perfect. If we think about reading a little differently and consider that reading could also involve efforts at external storage, the time invested in reading to learn may have a bigger return on investment in the future.

What follows are four books (linked to the Kindle version from Amazon) that take on the notion of digital reading. Yes, I have included one of my books among them although this book is focused more on how educators can take advantage of technology to facilitate how students learn when they read. All of these sources explain what I mean by the externalization opportunities technology make available. If you want a single recommendation, it would be “How to Take Smart Notes: One Simple Technique to Boost Writing, Learning and Thinking”. I find the title a bit misleading as the text is concerned with far more than taking notes. The author considers learning from reading and learning more generally. I make this recommendation because offers both solid theory and concrete suggestions for practice. 

Grabe – Designing Instruction Using Layering Services: Educators and students guiding learning

Cohn – Skim, Dive, Surface: Teaching Digital Reading

Kalir & Garcia – Annotation

Ahrens – How to Take Smart Notes: One Simple Technique to Boost Writing, Learning and Thinking – for Students, Academics and Nonfiction Book Writers

My Diigo account should provide me notes on all of these books.

Reference:

Furenes, M. I., Kucirkova, N., & Bus, A. G. (2021). A comparison of children’s reading on paper versus screen: A meta-analysis. Review of Educational Research, 0034654321998074.

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Online Privacy Demonstration

I have been reading a book on privacy (System Error) with a story and recommendation of a demonstration site I thought others might find interesting. The issue considered is how information we think to be shareable can still be used to identify us.

Latanya Sweeney, then an MIT graduate student, and anyone else who wanted, had access to the record of Massachusetts hospital visits by all state employees. These data contained no information assumed to identify individuals – name, address, social security, etc. The governor of Massachusetts contended that the privacy of those associated with these records was secure. Sweeney did not agree. She purchased a list of all registered voters in Cambridge that contained the names of voters as well as their birth date and gender. There were six people in Cambridge with the same birthday as the governor, three of these were male, and one lived in the same zip code as Weld. Sweeney cross referenced the medical records by birthday, zip code, and gender, located the governor’s records and sent him a copy.

Sweeney contends that 87% of Americans can be identified based on zip code, birth date and gender. These are variables we commonly provide without concern.

Sweeney now works at Harvard’s Data Privacy Lab. The lab offers an interesting demonstration. You enter your birthdate, zip code, and gender. I tried the demonstration and found that I could be identified as unique. This may seem amazing, but work through the math. There are likely at least three gender categories and 365 days in the year. I am 73 years old. Even though there are 35,375 individuals in my zip code, the combination of my age, gender, and birthdate identifies one person.

These data do not offer up my name. I suppose this could be determined from voting records as Sweeney demonstrated. For other purposes, this is demonstration of just how easily we can be targeted with ads or information.

Reich, R., Sahami, M. & Weinstein, J. (2021). System error: Where big tech went wrong and how we can reboot. HarperCollins.

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Check yourself

The Polarization Lab (Duke University) has conducted some interesting research on political polarization. They have developed tools you can use to estimate the orientation of your Twitter feed and bots you can use to expose yourself to positions taken with the opposite orientation. The premise of their work is that exposure to different perspectives can reduce bias.

Check my echo is a tool that compares the orientation of the politically oriented Twitter accounts you follow to prominent politicians, journalists, and advocates to generate a score on the polarization of those you follow.

The Lab offers bots to expand your perspective. The bots pass on tweets liked by prominent liberals and conservatives. The idea being liberals should friend the bot forwarding tweets liked by conservatives to gain insight into the positions taken by those unlikely to show up in their feeds.

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