Engagement is a big word in education. It combines both objective participation and subjective emotion. It’s one of the few psychological terms in education that links students, teachers and content. So it’s not surprising that in promoting the iPad as a tool for education, Apple touted the device’s ability to engage students.

Because they’re so engaging: okay, let’s just drop the bull and say it, because they’re cool

Tim understands what Apple and most reporters don’t know or like to gloss over: That there is nothing engaging about iTextbooks in relation to the important interpersonal engagement that we’re striving for in order to increase student motivation, participation, and academic outcomes (here is a great article reviewing student engagement and related research).

There’s no doubt that iTextbooks are intrapersonally engaging or put another way, interactive. However, just because something is interactive does not mean that it is engaging. Although I’m not endorsing them either, at least Inkling has the “social learning network” feature that allows students and instructors to carry on a conversation about book content. Certainly, a step in the right engagement direction.

Some of my research on Facebook and Twitter illustrates the idea of “engaging” tech vs. actual engagement: using an “engaging” system like Facebook doesn’t predict much of the variance in real-world engagement; however, using it in certain ways does. Learning outcomes come about not because of the particular technology being used, but because of how that technology is used to support sound pedagogy. Certainly, some technologies will be better suited for certain activities than others (for instance, Twitter lends itself better to ongoing synchronous and asynchronous conversations than email).

Educators will often become enamored by new technologies and adopt them with the underlying assumption that technology in and of itself must be good for learning (for a great review, see the Outcomes section of this paper). We see this type of hype with almost every new educational technology tool that is released. Take for example iPad initiatives at a growing number of universities: there’s no data to show that having students adopt iPads leads to better learning outcomes. So why adopt them on such a widespread scale? The only reason that I can tell is because they are cool.

Now, there is nothing wrong with the “cool factor.” Doing traditional educational activities with a shiny new toy can improve student motivation, a phenomenon I liken to Jedi mind tricks (“these are not the boring lectures you are looking for”). Unfortunately, the effect of the cool factor is short-lived when it comes to promoting positive educational outcomes. When all students have iPads (which is presumptuous to assume- I’ll save my rant about how iTextbooks will widen digital inequalities for another time), reading iTextbooks will be just like any other boring non-engaging assignment that students have to complete in isolation. In other words, the coolness wears off and the interactivity becomes a routine part of the process.

Of course we’ll never know how well new technologies work unless we try them. But in addition to trying them, we must integrate them in educationally-purposeful ways and also assess how integrating them in these ways affects student outcomes in comparison to other tools (in the case of iTextbooks, reasonable comparisons would be regular textbooks, other forms of digital books, and interactive websites). Put another way, we can (and should) be excited about the possibility of how new technologies might enhance learning; however, we must be mindful of evaluating what works and more importantly, what doesn’t.

These data are from a follow-up to a Twitter study we conducted a few years ago using first-year students. We interviewed these students a year after the original study. While we found some interesting things about their preferences for technology use including their use of learning management systems, I don’t want to spoil the surprise as we’re writing those results up for an upcoming paper. When we asked students what they thought about using Twitter or Ning in their courses, they overwhelmingly responded with the ideas exemplified in these quotes:

I think [using Facebook] would’ve been easier and a little more comfortable for people because I think pretty much everyone in my class had a Facebook and nobody had either one of these things.

I think that [Facebook] is a lot easier for people to use and since people generally get on there every day they are going to see the stuff and invites a lot quicker than others.

Many of them went on to say how they independently used Facebook to organize study groups, to ask questions of fellow classmates, and to catch up on missed work.

Why do students prefer Facebook over other technologies? 

Almost every student in our sample gave us a variant of the same answer: all their friends/classmates are on Facebook, and it’s easy to use. In other words, Facebook has the user base in order to make academic conversations useful. Plus, since students are “always” on Facebook, it’s easy to see when new comments are made to a post from a class. Some of my research has shown that how students use Facebook is sometimes more important than time spent on the site in terms of grades and student engagement. Therefore, college faculty have an opportunity to engage students using Facebook and to help them use the site for educational good.

One way to use Facebook as part of a course.

I encourage faculty members who want to integrate Facebook into their courses to set up a Facebook group and use the group to continue class discussions, allow students to ask questions, and encourage students to post and comment on class-related links (news articles, etc.). In a paper that will be published shortly, we make the case for faculty to actively participate in such groups to increase student involvement and improve course performance.

Last year at SxSWi, Seth Priebatsch from SCVNGR gave a keynote (video) about adding a game layer on top of the world. If you don’t have much time, I’d recommend skipping to the part about game mechanics and engagement in education which starts at 10:30. Seth’s talk sparked a number of ideas for me, one of which grew to be our proposal Game Dynamics in the Classroom: Badges to Improve Student Engagement and Learning in Large Lecture Courses for the Digital Media + Learning Research Competition.

The gist (straight from our proposal):

The goal of this project is to create and evaluate a badging system for learning in order to increase college student academic engagement and improve class attendance and academic performance. We hypothesize that we can improve college student academic outcomes by combining Location Based Services (LBS) with a badging system employing game dynamics and integrating it in an educationally-relevant way in a large-lecture course at The University of Florida.

I’m really excited that we were able to partner with SCVNGR to develop a badging system for this project. If the project gets funded, we’ll use an experimental design to evaluate the impact of integrating our badging system and related game dynamics into large lecture courses. As outcomes, we’ll measure differences in student engagement, attendance, and academic performance between the experimental group and the control group. Here are our methods:

Research design
Before the semester begins, university students registered for a large-lecture introductory course will be randomly assigned to either a control section or an experimental section. Both the control and experimental sections will be taught by the same instructor and will follow the same schedule in the presentation of course material. Each section will contain at least 200 students for a total of 400 participants. The Institutional Review Board for the Protection of Human Subjects will approve research procedures

Experimental Section
Students in the experimental section will use their Android or iOS devices to engage in academic challenges in order to earn badges. Students will check in to the classroom after indicated class sessions. Once they check in, they will be presented with a challenge that involves answering five questions about that day’s lecture, developed in consultation with the course instructor. Students will receive a point for each question they answer correctly. They will also receive points for checking in to the class location, posting pictures of their notes, and posting questions about the day’s lecture. Additionally, students will receive points towards badges by participating in relevant challenges outside of class, including “social check-ins” with a study group, visiting a professor/TA’s office or supplementary instruction session, or checking into the tutoring center.

When a student accumulates a pre-determined amount of points, she or he will receive a badge. Students may earn one badge for each week of the course. At the end of the semester, students will receive course extra credit based on the number of badges they have earned.

Control Section
Students in the control section will have the opportunity to answer the same questions as the experimental group; however, these questions will be presented as quizzes using TurningTechnologies ResponseWare. ResponseWare allows students to submit answers by using either their mobile phones or their laptop computers. The quizzes will include the same content and be administered at the same time as the experimental group. Control group students will also be able to complete the other challenges, but they will be presented as extra credit opportunities accompanied by manual tracking methods and a traditional scoring rubric equivalent to the badge system.

You can read the entire proposal here. I’d love to hear your thoughts on this project. Please feel free to leave a comment below or on the proposal page at the DML site.

I really would love to see this become a trend– infographics that are as much info as they are graphics. Elsewhere, I picked apart an infographic reporting some of my research on Facebook. I also lamented how it would be nice to see an infographic that included a more balanced approach to research findings (including limitations). Lucky for me, graphic designers read my blog. The first infographic based on my research did a great job summarizing the findings of my recent Facebook and student engagement paper.

I’ve got some ideas for infographics based on recent data that I’ll be working on in the near future. What data would you like to see represented in an infographic? Please leave your suggestions in the comments below.

Results
1. Time spent on Facebook was negatively related to overall college GPA. The average time students spent on Facebook was 106 minutes per day. Each increase of 93 minutes beyond the mean decreased GPA by .12 points in the model. Therefore, I conclude that although this was a significant finding, the real-world impact of the relationship between time spent on Facebook and grades is negligible at best.

2. Frequency of engaging in some Facebook activities such as sharing links and checking up on friends was positively related to GPA while posting status updates was negatively related.

3. The number of times students checked Facebook was only weakly related to GPA.

4. There was not a strong link between time spent on Facebook and time spent studying.

Discussion
Specific uses of Facebook are related to positive outcomes while others are related to negative ones. Therefore, Facebook use in and of itself is not detrimental to academic outcomes, it depends on how it is used. Using Facebook for socializing is negatively related to GPA while using Facebook for collecting and sharing information is positively related. As the interest in using social media, like Facebook, in educational settings increases, educators must be aware of how to integrate these sites and services in educationally relevant ways.

Limitations
This study was cross sectional and correlational and while it would be intriguing to be able to say that Facebook use may be causing lower grades, it is equally likely that students who have lower grades happen to use Facebook more. It’s likely that there is a third (or fourth, fifth, etc.) variable that explains and/or mediates the relationship between Facebook use and grades. Likely candidates include student motivation, personality characteristics, and academic attitudes/values.

[Edit 10/5/11]: A number of people have been asking if they can use this graphic. The answer is– of course you can! This infographic is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License which means that you can post it to your own site, share, or adapt the graphic as long as you’re not using it for commercial purposes and as long as you reference the source. You may also be interested in a higher resolution jpeg [6.2M] or a PDF version suitable for printing [~1M]

[Edit 10/12/11]: Thanks to Sandra Cortesi and Kristi Grande who noticed that the graphic representing the mean number of times students checked Facebook was missing one student at the computer. I have linked to the revised infographic (the updated version is also available as a higher resolution jpeg [6.2M] or a PDF version suitable for printing [~1M]).

This week, Shelia Cotten and I will present a paper on multitasking at the Oxford Internet Institute’s A Decade in Internet Time Symposium on the Dynamics of the Internet and Society.

We have posted the draft of the paper here. Please note that the paper is in draft form and it has yet to be peer reviewed. Therefore, we’d love it if those of you reading this would act as peer reviewers and provide us feedback about the paper. We’ll incorporate any feedback before we submit the paper for publication in an academic journal. We are particular interested in your thoughts about our interpretation of the results. Please feel free to share your feedback in the comments below or to email me directly at rey (period) junco at gmail. We’ll acknowledge any feedback we use in the paper.

Using hierarchical linear regression (N = 1,839) with gender, ethnicity, parental education level, high school GPA, and Internet skills as control variables, we found that frequency of sending text messages and using Facebook while doing schoolwork were negatively related to overall GPA. However, frequency of using email while doing schoolwork was positively related to GPA.

The finding that using Facebook and texting while doing schoolwork was negatively related to GPA was congruent with previous research on multitasking however, the finding that using email while doing schoolwork wasn’t. We theorize that the reason for this discrepancy is because of how the technologies are used– students use Facebook and texting socially with their peers while they use email to communicate with faculty and university staff. Therefore, we propose that social activities will lead to more negative outcomes while academic activities will lead to more positive ones.

As with my recent study of Facebook use and engagement, these data are cross sectional and correlational and while it’s intriguing to think that multitasking causes students to have lower grades, it is equally likely that students who have lower GPAs happen to spend more time multitasking. There is more than likely an extraneous causal variable related to both multitasking and student academic achievement that we have yet to measure. We’ll examine this more in future research.

For next year, I’ve proposed a solo talk entitled #NoFailWhale: Tweet More, Drop Out Less. I’ll present brand new data on how Twitter can be used to improve understanding of course content and to reduce college dropout rates. Since I’ve just finished collecting some of the data, there’s still more neat stuff to be analyzed. For instance, I’m going to evaluate how compliance with a Twitter intervention affects retention of course content (you might think it’s a straightforward relationship, but I’ve got some preliminary data to show that it isn’t).

I’m also going to be pulling together data across studies to come up with the beginnings of best practices in using Twitter in higher education.

If you think this is a cool idea, please vote for my panel by clicking here (you’ll need to sign up for an account – it’s quick and painless and SxSW won’t spam you). I’d love to hear your thoughts about the talk – please leave comments on the proposal page and I’ll make sure to address those comments during my talk.

While you’re at it, please vote for the core conversation being proposed by my friends and colleagues, Liz Gross and Ed Cabellon. See you at SxSWi 2012!

On to the results– using hierarchical linear regression (N = 2,368) with gender, ethnicity, and parental education level as control variables, I found that time spent on Facebook was a significant positive predictor of time spent in campus activities.

Although time spent on Facebook was a significant positive predictor, it wasn’t the strongest predictor of time spent in campus activities. In fact, it was the weakest predictor. The strongest positive predictors, in order of strength (with strongest first), were:

1. Creating or RSVPing to events on Facebook
2. Commenting
3. Viewing Photos
4. Average time spent on Facebook per day

I ran an analysis of covariance (ANCOVA) with student class rank as the independent variable, self-reported average minutes per day spent on Facebook as the dependent variable, and gender, ethnicity, and highest parental education level as covariates (N=2,346). For post hoc tests, I used the least significant difference (LSD) correction. The reason I chose to control for gender, ethnicity, and parental education level is because there’s plenty of research to show that these background variables are quantitatively and qualitatively related to technology use. If you’re not familiar with research on the digital divide, I highly recommend you read this paper on variation in Internet skills among youth.

Here’s what I found:

1. First semester students (FF) spent as much time as sophomores (SO) on Facebook.
2. First semester students (FF) and sophomores (SO) spent more time on Facebook than Juniors (JR).
3. Juniors (JR) spent more time on Facebook than both Seniors (SR) and first year students not in their first semester (FR).

These results can be summarized by the following equation:

FF = SO > JR > SR =FR

So, first semester students and sophomores spent more time on Facebook than any other group. I’ve got my own thoughts about why this might be, but I’d love to hear what you think. Please share your ideas in the comments below.