This post is a quick reminder that, as always, during the summer months I will be toning back my frequency of posting on this blog. But don’t you worry! I’ll be picking up full steam with my regular publication schedule of posting every 2 weeks during the academic year.
This blog tends to get a lot of traffic during the summer with readers looking for assignments and syllabi as they work on updating courses for next academic year. So I’d like to point out a few resources below. But first…
A few Recommended Blog Posts, Content & Articles
My four part series detailing a social media analytics assignment I used in my Communication research class this past semester. Start here.
If you are looking for assignments and syllabi, you’ll see that I’ve written about many of my assignments and included the assignment documents themselves.
To access those select the green menu bar at the top titled “Blog topics” -> “Teaching Social Media” -> “Classes” and then select the class.
Syllabi can be accessed either via the “Syllabi” menu at the top of this blog and selecting the course, or by selecting the “Teaching Materials” menu and navigating to an external document repository to access all my uploaded syllabi.
If you have questions about any of the assignments or syllabi, please do not hesitate to send me a Tweet. I’d be happy to chat.
What’ll I be doing this summer?
Let’s just say it’s going to be a life-changing summer. Follow me on Instagram & Twitter to find out. 😉
This is post #4 in a four part series about a new assignment that I used this semester in my Communication research class (all posts on that class).
That assignment is a 3-part social media analytics project. Each part is related but unique, allowing students to pick up a new skill set. In this post we’ll discuss part 3 of the assignment. If you haven’t read the assignment overview post, and the earlier post about pivot tables in Excel or my other post on this assignment about Microsoft Social Engagement, I encourage you check those out. In the first post, you will see a copy of the assignment that is discussed below.
This last part, part 3 of the assignment, asks student teams to do basic network mapping of their client using Netlytic.org.
Why Teach the Basics of Social Network Analysis?
This semester, I wanted my students to get exposure to, and a basic understanding of, social network analysis. I am not a social network analysis. But it is something I find fascinating. And I think it is important that as professors we have at least a basic knowledge of this field and that our students do as well.
I feel this way in part because of the rise of professional tools that social media professionals have for visualizing social media data. While several of the questions that can be culled from the work students did in the portion of the project described below could also be answered through other means – such as Microsoft Social Engagement -, learning about social network analysis and having this experience offers a different and valuable way of understanding who is connected to whom within a network.
With the above said, the below-described project provides students a chance to visualize a social network and see how different actors relate to one another around a specific topic on Twitter or Instagram. Students explored the conversation around their client’s Twitter and/or Instagram account to see not only who was talking about their client but the connections among those people talking about their client, who was talking about the client the most, and who was talked about the most.
There are many ways to visualize a social network. It can take quite a bit of time to learn the software. For example, I spent a weekend working on a #hokies network map using Gephi (read that post for a step-by-step guide of how I created a basic Twitter social network visualization). As you can see in that post, there are a lot of steps involved in building that one network map. But the upside is that Gephi is pretty robust and in my weekend working on it, I only scratched the surface.
Fortunately, there is a much simpler way to do some social network mapping. Netlytic.org is described on its website as “a cloud-based text and social networks analyzer that can automatically summarize and discover social networks from online conversations on social media sites.”
I first began playing with Netlytic soon after realizing that, for the baseline knowledge I want my students to have, I could not afford enough class time during the semester to warrant the investment in time and effort that would be needed to teach students all the steps of getting Twitter data and analyzing it in Gephi.
The downside of Netlytic is that is not quite as powerful and the visualizations are not as visually stunning.
Despite those limitations, I found Netlytic to have many upsides. For one, it is very easy to use and learn. A basic account is free and Netlytic will pull down the social media data you want directly into its service. From there, you can begin analyzing the data with just a few clicks.
I provide resources for learning how to use Netlytic below.
Setting Up the Assignment
Weeks before the we analyzed Netlytic in class, students were to create their own free Netlytic account and program their client’s Instagram or Twitter account and any hashtags they wanted to track on Twitter or Instagram related to their client.
The free version of Netlytic only allows an account to track up to 3 different searches at a time. Thus, teams were limited to 3 different networks to map. Each team approached this slightly differently, depending on their client.
There are 2 days of the semester dedicated to social network analysis and working with Netlytic. Day 1 is primarily lecture based. I provide a lecture of what social network analysis is, why it is good to have a basic understanding of it, and basic concepts that we’d be exploring. Specifically, I introduced nodes (e.g., Twitter users) and directional and uni-directional edges (the connections between them, such as retweets), talked about degree centrality (e.g., in-degree and out-degree density) as well as reciprocity, centralization, diameter and density.
On day 2, we relate these concepts to social media via a 15 minute lecture. For example, we discuss how in-degrees (who is mentioned a lot) and out-degrees (who posts a lot) would relate to Twitter posts. I then show several examples of social network maps of Instagram and Twitter and how concepts discussed in the prior class relate to them. And the rest of class is dedicated to working on analyzing the students’ client network.
There is a third day that is dedicated to students finishing up their Netlytic as well as anything they didn’t get done related to their Excel pivot tables and Microsoft Social Engagement.
It walks you through all of the steps of doing the network analysis and provides a list of resources for further understanding basic social network analysis.
I provide a few different research questions to the students that they have to adapt from, based on whether they are analyzing hashtags or other search terms or if they are analyzing mentions of their client. I have provided the information below just as it is described in the assignment:
Depending on what your networks are, you’ll need to choose from the RQs below. Choose all that are appropriate. Feel free to create your own. Discard the rest.
For networks that analyze hashtags or search terms:
What Twitter accounts are popular in this network and how often is each popular account mentioned?
What accounts mention others or RT others a lot in this network?
What unique clusters exist in this network?
For networks analyzing mentions of your client
What Twitter accounts mention your client the most? How often does each mention your client?
What communities are talking about @USERNAME?
Reflections on the Project
This project has three parts to it. Part 1 teaches students about using Excel pivot tables to analyze Twitter data. Part 2 gets them using industry social media analytics software. Part 3 introduces students to social network analysis and mapping a social network. The project takes several weeks of hands-on learning during the semester. For the students, a lot of work goes into the final product.
Because there were many moving parts, it was a little difficult at times for students to grasp all of the details of what we were trying to accomplish. Some student groups lost sight of the fact that the data they were dealing with was from different time periods because it was not all collected at the same time (a weakness I discuss in post #1 on this project).
One area of weakness was that some of the groups struggled with interpreting what their data meant and offering actionable suggestions to their client on how to enhance their social media based on the data.
Next time, I am going to try and tighten the assignment up. For example, I want to slim down a few of the research questions students had to answer that seemed a little redundant across the 3 different parts. I also want to place more emphasis on helping students think about what their results mean and how they can use the knowledge they have discovered through this analysis to make meaningful recommendations for their clients.
In summary, this is the first time we’ve run the project, and overall I am pleased with the outcome. I feel that this project helped me further ‘modernize’ my communication research class by placing greater emphasis on getting students working with social media data and thinking about what that data means.
I hope you enjoyed this 4-part series on the new social media analytics assignment in my communication research class! If you haven’t yet, be sure to check out post 1, post 2 and post 3.
That social media analytics project assignment contains 3 parts. Each part is related but unique, allowing students to pick up a new skill set. In this post, post 2 of 4 in the series I’m writing about this assignment, we’ll discuss part 1 of the assignment. If you haven’t read the assignment overview post, I encourage you to do so before proceeding. There you will see a copy of the assignment discussed in the below post.
Part 1 of the assignment asks student teams to analyze the Twitter data provided by their clients by creating pivot tables in Microsoft Excel.
If you aren’t familiar with pivot tables, they enable you to filter and visualize spreadsheets. This allows you to focus in on specific data points and quickly extract insights from large data sets.
I got the inspiration to create this part of the assignment from a very helpful conversation I had with Professor Stefanie Moore at Kent State University. A big thank you to Stefanie for taking the time to chat with me and for providing me with insights to how she teaches analytics. I am really impressed and inspired by what Professor Moore is doing at Kent State.
Preparation: Getting Twitter Data
In order to analyze Twitter data using pivot tables in Excel, you need to first download Tweets from Twitter’s analytics (ads) page. If you’ve never done this before, it is really quite easy.
The reason we use Twitter is because Twitter enables you to extract a ton of valuable account data from your account in the form of a CSV spreadsheet. But, as an aside, you could analyze just about any data with pivot tables.
My students were required to get the Twitter data from a client. Therefore, I created a step-by-step guide that they could provide to the client so that the client could extract the appropriate data and supply it to me.
To ensure we had enough data, I instructed the students to ensure that their client was posting at least a few times per week. I asked students to get 6 months of Twitter data if possible. In short, I wanted to ensure that there were at least 50 Tweets from the client in the time period we collected. This number is somewhat arbitrary. And ideally you’d like to have more. But, 50 Tweets is enough to sort and play with.
Here are the steps for extracting Twitter data from an account:
Step 1: log into your organization’s Twitter account at http://twitter.com. Next, select your account profile picture (as shown below) and select “Analytics.”
Step 2: A new window will appear. Click “Tweets” from the menu at the top. Then, select the date range (see below). A menu will open. Please select a date range of at least 3 to 6 months back so that there are enough Tweets for the students to analyze.
Important: Click “Update” to change the selected date range.
In the below example, I selected Feb 1 through May 1 (3 months).
Step 3: Once the dates have been selected, click “export data.” A new window will appear. Click “save file” to save the file to your computer. Email that file (it should be a .CSV file named something starting with: “tweet_activity_metrics…”). You have your data. If someone else is downloading the data – such as a class client – , they will need to email the file to you or your student.
Using Pivot Tables to Analyze Twitter Data
A few days were set aside in class to work with the pivot tables and learn how to answer the questions students were asked to answer in the project. On day 1, I provided a brief lecture (about 10 minutes). And then I instructed students to begin working with the lab guide I had created. If you’re a longtime reader of this blog, you know I am big on creating lab guides to assist students in learning software.
While working with the lab guide, students were to have a copy of the assignment that contained the research questions they needed to answer using the pivot tables. Those research questions were:
Which Twitter posts received the most (Fill in the blank – you need to decide what variables are important engagement data for your client. You’ll need more than 1 variable. And, you’ll want to show more than just the top Tweet for that variable, but the top few)?
What is the client’s Twitter engagement by month? (again, you choose the appropriate engagement metrics)
Come up with 1 other RQs for important data points you extract from your pivot table analysis that you believe will be of value to your client.
For the above questions, students needed to pick what engagement metrics they wanted to analyze. There are several engagement metrics in the CSV file when you download it from Twitter. Examples include retweets and favorites.
For research question #3, most groups analyzed engagement by Tweet category. As you’ll see in the lab guide, students learned how to comb through their Tweets and identify common themes by which to categorize their Tweets. Examples may include promotional Tweets, humorous Tweets, Tweets that ask a question, etc.
The above 3 research questions are just a sampling of what you could do with the pivot tables.
In the next post, we will discuss part 2 of this assignment which gets students using Microsoft Social Engagement to answer some research questions about their client. I will be publishing that post in 2 weeks.
In the meantime, if you want to get your feet wet, I encourage you to download your own Twitter data and walk through the lab guide above. Or, check out some of the sources listed below to learn how to analyze Twitter data with pivot tables.
As you will see when you take a look at the lab guide, you must first clean the data so that Excel can analyze it. I then walk you through a number of different ways you can analyze your Twitter data.
The fact is that I was a bit of a newbie to pivot tables when I created this assignment. To build the above-discussed lab guide I provided students to help them through learning how to use pivot tables, I relied heavily on several key resources. Much of what is in the lab guide is built directly on what I learned from these sources. To learn directly from the sources I learned from, check out the sources below. A big thank you to all of them for sharing their knowledge publicly. I hope I was able to honor them in adapting their work for a classroom assignment.
Update: You can now read the follow up posts to this blog series.
We’ve all heard of six degrees of separation. The idea, proven through the research of Stanley Milgram, is that any one person is connected to another through 6 or less other individuals. (If you’d like to see this idea in action, play Six Degrees of Kevin Bacon where you can find if any actor is connected to Mr. Bacon through 6 degrees or less). But to how many degrees of separation does one person influence others? Here’s a hint. It’s not 6.
As educators in the social media space, we talk to our students about online influence and the great powers that thought leaders can have to diffuse ideas or realize the adoption of those ideas among social networks. But, while important, talking this way is in a sense, shortsighted.
We know that ideas spread not simply in a two-step flow, a la Paul Lazarsfeld’s groundbreaking research (way before Facebook!), but through a multi-step flow (or, later, diffusion of innovations) through a network of connected individuals.
But it is not simply ideas or diseases that spread. Who we are connected to has many subtle yet powerful influences on our lives: from who we marry, to how quickly we solve problems, to whether or not we’ll vote, to why we would act altruistically at the expense of ourselves, to why men benefit more from a marriage than women, to much, much more. And that is the central thesis to the book. While we like to think of ourselves as independent and autonomous, Christakis & Fowler take a sledgehammer to that notion. We are, as the authors put it, Homo dictyous (“network man”).
Interest in Social Network Analysis
Interest in social network analysis is on the rise in communication scholarship. Recent years have witnessed a growth in the analysis of large data sets of social media data (e.g., big data) to understand connections and the spread of ideas. As I’ve said before on this blog, this is an area I personally need to delve deeper into. And, I believe that’s true for all of us aiming to teach our students to thrive in the social media economy. Strategic insights can be gained by understanding social networks and we’re seeing a greater emphasis on that both in research and in professional applications.
Should You and Your students read Connected?
The book is a thorough and accessible look at social network theories and research. While this isn’t a ‘must read book’ like Made to Stick, I would suggest this book to anyone as we all live in a networked world. The book has given me a much greater appreciation for my place within the different social networks I’m apart of. It’s been one of my favorite reads of late. and I absolutely recommend it. Educators and scholars interested in a deeper appreciation for social networks would enjoy and truly benefit from reading this booth.
Should students read this book? This is a very readable, incredibly informative and sometimes humorous read that I believe students would enjoy. I would love to have my students read this book. However, I likely won’t use the book in my classes – at least for the classes I currently teach – simply because there are too many other books I want my students to read. But, this book would be great for any class specifically about social networks and more broadly for theory classes. It would be a great read to add to a data analytic course exploring online social networks.
Though the book is primarily about offline social networks with a chapter dedicated to online networks, Connected could be used as a suggested or supplementary reading in a social media class if the professor wants sufficient time or depth given to social networks (see my lecture and activity on social networks for my Social Media class).
Three Degrees of Influence
So back to our initial question. While we all may be connected by about three degrees of separation, through how many degrees does one have influence on another? The authors’ research indicates that influence generally travels three degrees. They state: “Everything we do or say tends to ripple through our network, having an impact on friends (one degree,” our friends’ friends (two degrees), and even our friends’ friends’ friends (three degrees)…. Likewise, we are influenced by friends within three degrees but generally not by those beyond” (p. 28).
Which begs the question: How are you influencing your friends’ friends’ friends?
It is hard to believe. But, I’ve just completed teaching at the university level for 10 academic years.
At the age of 24, I began teaching as a graduate student in 2006 at Washington State University where I independently taught 2 classes a semester for 4 years. I had no idea what I was doing. I was barely older than the seniors. With a textbook in hand and the summer to prepare, I jumped right in.
As of this past Friday, I have completed 6 years of teaching as an assistant professor. All of that has been working with undergraduates.
Here’s what I’ve learned in the 10 years since I began. I can boil it down into one concept:
The quality and effectiveness of the education you provide as an educator is a function of the culture you build.
So, if you want to succeed as an educator, you begin by building a pro-learning culture. And a pro-learning culture is a pro-student culture.
Yes, it is the student’s job to learn in a classroom. Just as it is your job to work at your job. But where would you rather work, in a positive, welcoming, enthusiastic environment, or a in drab office that has the inspiration and personality of a filing cabinet?
Believe in the students – My Ph.D. advisor taught me that, as educators, we all must decide whether we believe students are inherently good or bad. That sounds dramatic. Let me explain. You can believe that your students want to learn, are talented and capable person and are honest with good intentions. Or, you can assume that they are lazy, cynical, unmotivated, etc. Your attitude on this will affect how you perceive them and how you treat them. Believing in your students is the foundation that enables everything else I talk about below to work. Which brings me to…
Set the tone – Students are extremely bright and perceptive. If the culture of the classroom is disengaged or the professor seems disinterested or “going through the motions” then students quickly pick up on this. The tone of the classroom starts with the professor. I’ve had classes where I didn’t succeed in setting the right tone and while the tendency is to start thinking “it’s the students,” I always remind myself to look at the energy and performance that I’m bringing into the classroom. While some groups of students are more difficult than others to energize, we can all make efforts to set the tone and remember that we’re seen as the person who is in charge. Students mirror. If we’re mentally somewhere else, are students will be too. Which brings me to…
You’re The Role Model – All the talent in the world doesn’t necessarily produce results. Many talented, under-performing sports teams prove this rule. Just as a great coach extracts great performance from talented players, a great educator extracts great performance from talented students. Students are looking for a leader. They are looking for inspiration. They are looking for someone they can believe in and trust. I see it as my job to inspire my team – the students – to go out and win the game (that is, do great work). That’s not something you do in 1 day. It is a semester-long push, just the way a coach must push a team not for 1 game but for a season. Being a role model is a marathon effort and it is communicated to students through your actions, words, and attitude in all facets of the class. Which brings me to…
Infect your students with enthusiasm – How? For me, I bring the enthusiasm for what I do each day. I love what I teach. I love teaching. Mood is infectious. Energy, excitement, passion, and inquisitiveness are infectious. I learned this the hard way. When I was first teaching as a graduate student, I pushed for and got the opportunity to teach a 400-level new media course. There were 40 students in the class. I designed the entire class myself and this was my first time doing so. I began teaching social media to these students at a time when I’d never heard of another class teaching social media. There was no textbook, there were no resources, nothing. It took a ton of work to build the class. I was overwhelmed and I didn’t feel like the class was going well. Some students began to show up late or leave early. They’d just get up and walk out. My confidence was shattered and this was a vicious cycle. As I performed worse, the students seemed more disengaged, which caused me to perform worse. After that semester, I read through my evaluations. A few students commented that I “complained about the weather.” I didn’t realize that I’d even done that – I’d left Miami Florida for the long, bleak winters of Pullman, WA and hadn’t quite acclimated. 🙂 I reflected on this and realized it wasn’t necessarily the material that the students didn’t appreciate. It was my attitude. It was my style of delivery. I quickly realized these were things I was in complete control over. I’d spent so much time worrying whether I was providing the best possible education, material-wise, that I hadn’t focused on how I delivered it. I was passionate about the topic – after all, I’d sought out this opportunity and built an entire class. What little that meant to the students. They had no idea how I felt inside. For me, that was an epiphany that changed my entire approach to education. Which leads me to…
It’s not what you say, it’s how you say it -Delivery is important. Find creative ways to relay information. Beyond the passion of your delivery, is the manner of making content compelling. We’re all familiar with hands-on learning, flipped classrooms, and other ways to bring our classrooms to life with activities and not just lecture. But, moving beyond this, when we do lecture we can relay that information in memorable ways. I think each of us has our own talents and ways of telling the story of what we’re teaching. But, there are some great common tips we all can use from books like Made to Stick (I discussed how this book could be used in an earlier post). I’ve found that my favorite tactics are 1) to create mystery or suspense at the start of a lecture by withholding some piece of information or alluding to a funny anecdote or joke that I’ll reveal later in the class, 2) to make a big deal out of little things because, really, the little things are what matters. For example, I like to talk up activities we are going to in class, why they matter and how fun they are going to be. I emphasize how valuable activities and lecture materials are going to be in helping students not only complete an assignment but succeed in other realms of their life or career. Which leads me to…
Make education an experience – I’ve never taken an acting class. But I look at education ‘as performance.’ Every time you’re in the classroom you’re putting on a performance. But the difference is that the audience can be actively engaged and participate in the story – they have roles. And that’s a pretty cool play. I try to do this in a lot of ways. Let me focus on one. I celebrate my students’ victories. I reward them for their success. I create awards and accolades. I show appreciation for them. I help them feel important. Here’s an example. For the last 6 academic years, I have given out “High-5 awards.” The idea is simple. As the syllabus in all of my classes reads, “High-fives will be given to students who miss no more than 2 classes at the end of the semester; two-handed high fives for students who miss no classes.” It is important to note that there is absolutely no grade associated with this high-5. You don’t get a better grade for having stellar attendance. On the last day of class, I play Rocky music and give out the high-5s. Double high-fives come with a little certificate that I sign. I nervously tried this the first semester that I taught at Utah Valley University. I expected the students to laugh it off and not want to participate. How wrong I was. They loved it. It quickly caught on and the word spread. I’ve had students tell me they came back to take a class from me simply because they wanted to get another high-5. I’ve had students tell me they came to class when they were sick, tired, or otherwise didn’t’ feel like, just so they wouldn’t miss out on getting the high-5 at the end of the semester. How powerful is that?
This year, I gave out a very special high-5. I had a student who took 6 different classes from me and never missed a single day. Not once. To reward this student, I created a new award in his name. I made a special certificate that I framed and gave to him. I also created a sort of plaque with his picture and name and hung it in my office. The idea is that if another student repeats this difficult task, he or she would be the recipient of this special award have their name added to the plaque that hangs in my office.
I’ve thought a lot about why the students like the high-5 awards so much. Yes, it’s corny. Yes, they get a laugh out if it. But I think the answer is simple. It shows I appreciate and recognize them. That I’m not just there to ‘download’ information to them. But, that I’m there to root for them.
All people respond to their environment. That environment can be motivating or demotivating. Educators have the power to be leaders. It seems that sometimes that is forgotten in our society.
But I know so many passionate and dedicated educators. I’ve seen the great things they’ve accomplished and the impact they have on lives. These people have inspired me in my 10 years of teaching. And it’s because of the educators I know and the wonderful students I’ve had the opportunity to teach that I’m excited about the future.
I love what I do. And this is what’s worked for me: putting my energy into creating a welcoming, rigorous, tolerant, and energetic culture in the classroom.
I can’t believe it is mid-June! It has been a busy summer. The highlight so far has been 2 weeks in Spain. While the first few days I helped run a booth at an international meeting, the majority of the trip was spent backpacking via train. I saw Gijon, Bilboa, Seville, Cordoba, Ronda, Toledo, and (for a few hours before catching a flight) Malaga. It was absolutely amazing!
With all that said, a blog post is well overdue!
One thing I’ve spent a bit of time this summer doing is preparing a new class I am hoping to teach in the spring or the following fall semester. The course is a persuasion course. It aims to enhance exposure to theories and research of influence and persuasion among students in the (still new) Strategic Communication concentration, and our department generally.
As the coordinator of the Strategic Communication concentration, I believe the students would greatly benefit from a focused look at how theories of persuasion and research findings in persuasion can be applied ethically in professional communication settings to improve message effectiveness. Of course, we talk about such concepts here and there in other classes. But, I am excited about having an entire course aimed at getting students to learn these concepts, evaluate their use in real-world examples, and work on a project aimed specifically at applying theoretical concepts to the design of a persuasive campaign (In this assignment, my students will pick a cause they want to advocate for).
I’ve been thinking about this class for the past few semesters. But what truly motivated and solidified my going forward with planning this summer is the very interesting series on the Institute for Public Relations website on behavioral communication. This great series highlights the importance of understanding social scientific research from various fields and its implications for communication professionals.
In his opening post on the series, Christopher Graves states: “When we approach public relations challenges such as changing perceptions, changing people’s minds on an issue, building engagement in climate change or changing behavior related to health, or restoring trust, we tend to gravitate toward intuitive solutions based on creative concepts. Yet we may be working on a false premise from the beginning (“doing the wrong thing righter”). Increasingly, behavioral and neuroscience research related to communications and decision making can better guide us into communications solutions that have a better chance of working.”
While the series focuses primarily on behavioral and brain-related studies, it makes a wider point for the importance of looking to applying research and theoretically-tested assumptions over intuitive assumptions. I always joke with my students that their fear and loathing in the college classroom centers on two words: Theory and Research.
I’ve heard my students express disgust and fear when it comes to theory. I’ve heard discussions among professors that students simply hate theories and research which leads to the question, what should professors do about it? Do we stop teaching theory and focus on more practical things? Do we use a tough love approach and teach students theory, paining both ourselves and our students through dry, intense lectures?
I believe this is a false dilemma. And I believe it stems from not seeing (or showing to our students) the applications of theory and research to practical settings. In a class such as the one I’m designing,emphasis should be given to bridging this gap.
A major goal I have is to help students overcome their aversion to theory and research and to help them see its practical value and importance. We can do so by highlighting examples where theory and research have helped inform effective message design, or by deconstructing an existing message to analyze what theoretical concepts or present or lacking. But we can also do it by taking the time in our classes to demonstrate how a theoretical concept or findings can be applied to a practical situation to better achieve communication goals, thus leading to desired outcomes. In my persuasion class, I plan to have sections of lecture called “Theory into Practice” where, after presenting a theory, I explain how that theory could be applied in a given scenario. I’ll also use mock scenarios students have to work through in class to apply concepts and solve a communication problem – such as through in-class simultaneous response prompts.
Ultimately, it is my goal to have students leaving the class not only more aware of persuasive strategies that can be used, but motivated and adept at using them in their coursework across the concentration (and of course, in their careers once they leave Shepherd). This, in turn, will help them become more cognizant communicators with an empirical mindset towards the choices they make as communication strategists.
It is more important than ever for our students to understand why certain approaches work and others don’t and be able to make informed, research-driven recommendations.
I know this is something we all work towards. I would love your thoughts and suggestions on how you help students see the value in theory and research and bridge the gap between “Oh, this is just stuff I learn in class” to “Oh! This scenario calls for me to apply what I’ve learned to be more effective.”
I’ve been thinking a lot about how to improve teaching social media metrics and monitoring. This is something that I have never quite been satisfied with in my classes. I think a big reason for this is because we don’t have access to a lot of real-world metrics for students to learn on. I’ve tried to overcome this limitation in a few ways. But none of them have been completely satisfactory. Here’s what I’ve tried:
I’ve pulled down stats from webpages or Facebook pages for events I’ve developed or helped run. But all have been fairly small scale.
Last academic year, I implemented a blog assignment in my social media class and one of the main goals was for students to learn how to use Google Analytics. However, to do so, we used Tumblr because that enabled us to install GA for free. Students didn’t like Tumblr. This year, we moved to WordPress for our department blog. The free version doesn’t support GA and the WordPress stats are limiting.
But I haven’t found something that really makes me feel like I can teach students analytics in an engaging way.
No matter how I present it, I have found that students tend to fear metrics. This morning I started thinking that what we need is a module-based, hands-on teaching system.
Ideally, this would have to partner with a social media analytics company. The company would provide real-world data (they may have to mask identifying information). In a perfect world, students would have access to the company’s software and would be able to play with the data in a safe environment (where they couldn’t take any action on the data, such as send a Tweet, but could interact and create reports). And there would be a series of modules that students use to learn analytics. At the end of it, students would be put into a simulation environment where a problem is presented to the class and students would work in groups during class time to solve the scenario.
I’d love to do this. But I’m not yet sure how to get started. More than that, I think it is a project that has utility at multiple universities. If you are interested in exploring this idea with me, please contact me. I’d love to chat. I believe in the power of conversation.
I think this could be a cross-university effort of professors where we all could create and use the modules. I believe we could approach a metrics software company as a team and have a greater likelihood of success. What do you think about this idea?