Author: grabe

What can be done to reduce the time spent on our devices has become a very public question. The issue has resulted in K12 schools being legislated in many areas to prevent students from bringing their phones to class and concerns are common that the rest of us should also cut back. I have written previously about the issue when present in young phone users and whether heavy use should be characterized as a physical addiction or a bad habit. 

The present post originated from my continued reading on this topic and an article I read related to the bad habit perspective proposing that adolescent screen time could be reduced if adolescents became more aware of their screen time and begin to think of it in terms of time not spent on other activities they value. This article described a program called Project Reboot and the Clearspace app. The app allows a user to set specific limits and informs the user when limits are being exceeded. The notion of improving mindfulness and the exertion of personal control seemed related to the bad habit perspective. Is awareness enough or should use simply be prevented?

Research on apps that intervene

It seemed likely that researchers would have investigated digital strategies to address a problem that originates with digital devices and I located a meta-analysis of such strategies (Tahmillah and colleagues, 2023). I recommend anyone interested in this topic take a look at this article because it does a great job of categorizing apps and the approaches taken to impact screen time. Just the list of apps was informative (Clearspace was not included) if for no other reasons than many may be unaware that such interventions exist and because the costs vary greatly. Identifying the apps proven to have an impact on behavior in combination with the mechanisms employed by such apps was informative. Simply blocking the use of an app or taking phones away limits screen time, but technology in general and most apps specifically have both opportunities and limitations so most of us in the long run would be better off making decisions about when and for how long to use our apps. 

The classification system

Rahmillah and colleagues proposed the following categories:

1. Block
2. Self-tracking
3. Goal advancement
4. Reward/punishment

Categories were further differentiated by underlying processes. For example, goal advancement, the approach that most interested me, included among the processes the opportunity to set a goal and a goal warning that the limit was approaching. 

The idea of the meta-analysis was to identify the apps that had demonstrated success in reducing screen time and then consider the underlying processes used by the more successful apps. In reviewing the studies found to impact screen time, I discovered the built-in screen time capabilities of iOS were listed (example of iOS screentime study available online). Given the costs I had found associated with other apps, this seemed important to me as users might be reluctant to consider costly apps this seemed important. 

Description of iOS Screen Time Controls

iOS Screen Time offers capabilities that seem examples of the goal-setting and goal-warning processes of a Goal Advancement approach. The following describes how to set up an iOS device to provide these functions.

The following image shows important iOS settings for limiting use. These features are available from the System settings. The Screen Time button (left-hand panel) provides access to multiple settings in the right-hand panel. Goals can often be accomplished in multiple ways and I am describing just one sequence here.

From the following image, note the following. The settings you can implement can be protected by a password (red box near bottom of image). If you wanted to set controls on a child’s phone to prevent access or limit the time on an app, you might want to protect the setting with a password. For your own use, you might not want to use a password offering you a way to ignore the notice that you had reached the limit you had established. You can set limits in several ways – individually or by category. If you decide to set limits by category, you might want to exclude some apps from that category. Always allowed provides a way to do this. 

The approach I am taking here makes use of the See All Apps and Website Activity option (Green box). 

The Apps activity option shows time spent by app or by category. You can toggle between the two presentations by selecting the button shown in the smaller green box (this would take you to the app view from the category view). Toward the right end of a category, you should see the > symbol. Selecting this symbol will reveal the apps associated with that category. 

You can now select the category or individual apps to set limits. I have selected Instagram. 

I can then set the maximum time per day and customize the time during a week should I want to do something more complex such as extend the limit for the weekend. 

What happens when you exceed your goal? You will encounter the following Time Limit Screen. If you have a password set, you (or someone with the password) would have to enter the password to provide you more time. If no password has been set, you see the following options and can make an informed selection to continue.

Summary

Apps are available to help individuals manage their screen time and research indicates some apps do produce improvement. Of course, research studies do not claim every individual will respond in this manner. Some techniques allow individuals to set goals and inform the user when they have spent the maximum time they intended to spend. This approach is based on the assumption that the lack of awareness is a reason many exceed the amount of time individuals intend to spend and behavior will change when a method of improving awareness is provided. iOS has screen time controls built in that allow for goal setting and goal awareness to be provided. Because these functions come with the operating system on Apple devices a user does not have to spend money on additional capabilities. This post explains how to set goals in iOS. 

Reference

Rahmillah, F. I., Tariq, A., King, M., & Oviedo-Trespalacios, O. (2023). Evaluating the effectiveness of apps designed to reduce mobile phone use and prevent maladaptive mobile phone use: multimethod study. Journal of Medical Internet Research, 25, e42541.

I have resisted the complaints that reading from a screen leads to poorer comprehension for some time. Much of my own research and writing have promoted the educational benefits of technology and the multiple studies and meta-analyses reporting that comprehension is adversely impacted when reading on a computer or tablet seemed a challenge to my message. A recent post on Reading Rockets by Timothy Shanahan identified several new studies I had not read and encouraged another look and another post.

When I first wrote about educational applications of technology, my approach was strongly influenced by David Jonassen’s mid-1990s book Mindtools. Rather than focusing on programming, computer literacy, or drill software, Jonassen proposed that educators consider how using productivity tools (e.g., word processing) could change how learners explored ideas. Again using word processing as an example, how writing to learn with a computer might expand the cognitive benefits of the writing experience beyond that allowed by pencil and paper.

A more recent version of the “tool perspective” (e.g., Etchells, 2024) offers a more nuanced view and notes that tools are in many ways neutral and users determine whether tools will be used effectively or detrimentally. The ills associated with technology are challenging because technology offers opportunities and challenges. However, Etchells proposes that the challenges are not due to addictions or biological triggers. The challenges are often best described as bad habits. This creates a difficult situation for some with the tendency to promote but also allows others to blame the tool as bad and ignore the control and responsibility of the user. With a specific focus on reading from digital devices which of these perspectives makes the most sense? If I maintain a position of advocacy, can I focus on the responsibility of the learner in a way that offers potential solutions rather than blaming the victim?

My “out”

First, I have no concerns about my own nearly total reliance on reading from digital devices. Even if there is a minor hit to my comprehension, my digital reading is part of a process of getting from a review of the ideas of others to my own written output. Digital reading allows me to efficiently highlight and annotate and export these personalizations of my understanding into external storage that I have accumulated over the years and use months and sometimes years later as background for what I write. This is one of those situations in which I cannot direct others to research evaluating the relative effectiveness of this approach to knowledge work, but trying to approximate my process on paper seems pointless. Put another way, reading comprehension is just one component in combination with long-term storage, multi-document processing, organization, retrieval, the flexible connection of stored elements, etc. that are involved in the writing and teaching I do.

Shallow Comprehension

I am starting to find the redundancy of the basic research studies and meta-analyses that have filled journal space in recent years to be mildly irritating. Replication is important in science, but at some point, it is time to move on to replication and extension. The studies that are attempting to study the process of comprehension when reading from a screen or paper are an example of what I mean by extension. Because it is not obvious why reading text on paper or on a screen involves the cognitive processes involved in reading, repetition of differences in the product (answers to test questions) has a decreasing value.

It would seem that the existing research demonstrates an issue, but not an explanation. Reading from a screen and paper would seem to involve the same cognitive subtasks, but the results are not equivalent. The explanation that seems to have gained the widest acceptance (my judgment) is commonly called the “shallowing hypothesis. I attribute this claim originally to Nicholas Carr who wrote a popular book titled “The Shallows”. As I understand the argument, the reading we tend to do online mostly involves what we might commonly describe as skimming. This experience leads to a bad habit that is activated when we read material from a screen even with content we might read more carefully under other circumstances. The reading habits of doomscrolling are proposed to generalize to reading books.

Eye movement research offers a way to watch the process of reading. We know that reading on a screen moves faster and readers overestimate their understanding level. Speed to complete the reading of a passage and requests to estimate the level of understanding by asking for prediction of performance areas variables that are easy enough to collect. I studied the phenomenon of failed reader understanding of their level of understanding and recognized the issue as a problem of comprehension monitoring resulting in poorer calibration. Calibration is simply the accuracy with which you can estimate the quality of a future performance. I always explained it as the decision that a student makes the night before an examination. Can they stop studying now and go out with friends or should they keep working to get the exam score they want? I was interested in calibration as a challenge for less capable readers reasoning that simple fix-up problems such as stopping and rereading sections that were poorly understood was the basic adjustment less capable readers were unable to make. In reflecting on the challenge in the context of college student study behavior, I tended to think of the problem as a matter of efficiency. Students used to tell me they had read chapters several times in preparation for an exam. Rereading is a common strategy among the motivated, but less capable learner. It would be far better to recognize the topics you did not understand and focus on these topics. It would be even better to notice this immediately while reading and while being more aware of the context of the material being read. This would be the ideal time to reread a paragraph or two.

When I was actively involved in this research, this challenge was sometimes studied by inserting different types of errors in text and determining if readers could identify the problems. Create circumstances that should result in a failure of comprehension and see if a reader would recognize the problem. For example, a statement that existing knowledge should indicate was inaccurate or a conflict between two sentences in the same sentence. Better readers were better at identifying these inserted errors. The technique was criticized because it placed readers in the role of proofreaders which is not the way we actually read. At the time, I tried to investigate the issue of monitoring skills by using a similar technique without informing the participants in my research and using eye-movement recordings to determine what happened when readers encountered what should have been confusing sentences. At the time the technique was tricky to use and intrusive as readers had to maintain their heads in a fixed position by bracing their chin on a bar. My research traded one form of artificiality for another.

The sophistication of the equipment has drastically improved and eye movement techniques are being used to compare participants reading from printed material and from a screen. For example, a recent study compared 8th graders in Norway (Jensen and colleagues, 2024) reading items from the national reading assessment exam from paper and screen while recording eye movements. As part of the preparation for the actual experiment, the researchers asked about their experience with reading from paper and screen and determined that many students proposed they comprehended better when reading from screens.

The reading examination itself involved passages of text each followed by several questions. Readers could refer to the written material when answering the questions. The eye movements indicated that readers referred back and forth between text and questions more times while reading from the screen to answer the questions. The researcher found that the readers had greater difficulty understanding when reading from a screen. This makes sense, but the readers still performed more poorly on the questions which would seem to indicate they were aware that they did not understand and could not completely remedy the difficulty.

Solutions

I don’t see online reading as a behavior that will disappear or diminish in frequency. I wonder about the hypothesis that poor habits are developed from heavy exposure to the scanning behaviors that many apply in texting and scrolling through social media feeds such as Twitter, Mastodon, and Blue Sky. I admit my perspective differs because I am a reader of books and journal articles on digital devices. I try to remember that my age means this style of reading (long form) predated any exposure to reading on a device. So my habits could be different allowing strategies of reading to differ between long-form and the types of text more suited a superficial approach.

Shanahan proposes that if technology environments encourage maladaptive behaviors why couldn’t they be engineered to encourage more effective behaviors? I think there are already such opportunities with longer-form content, but the opportunities are both ignored by most readers and not taught in educational settings. The exporting of annotations and highlights I rely on is seldom a part of the reading process of most learners. Here is another example of the transfer of a habit. Younger students are not allowed to highlight or write in their print books and the highlighting behavior of college students has frequently been criticized. I have written extensively about a variety of ways in which educators and learners can increase their active engagement with digital content. I call this collection of techniques layering because the strategies are external to the text itself and yet provide opportunities for processing text (and video) in more cognitively active ways.

Maybe improved awareness is also important. If skimming can be understood as a habit sometimes applied inappropriately in some settings, greater metacognitive awareness of goals and content would seem to be important. Concepts such as deep reading versus recreational reading are not new and the concern for shallow reading on devices is just another version of this older way of thinking about what learning from reading requires.

Sources

Carr, N. (2020). The shallows: What the Internet is doing to our brains. WW Norton & Company.

Etchells, P. (2024). Unlocked: the real science of screen time (and how to spend it better). Hachette UK

Jensen, R. E., Roe, A., & Blikstad-Balas, M. (2024). The smell of paper or the shine of a screen? Students’ reading comprehension, text processing, and attitudes when reading on paper and screen. Computers & Education, 219, 105107.

Jonassen, D. H., & Carr, C. S. (2020). Mindtools: Affording multiple knowledge representations for learning. In Computers as cognitive tools (pp. 165–196). Routledge.

Singer, L. M., & Alexander, P. A. (2017). Reading on paper and digitally: What the past decades of empirical research reveal. Review of Educational Research, 87(6), 1007–1041. https://doi.org/10.3102/0034654317722961.