Nine Tips to Help Your Students Build Effective LinkedIn Profiles

LinkedIn is the most important website for students to incorporate in their job search efforts. Employment recruiters search LinkedIn for candidates far more than any other social network, many employers now want to see LinkedIn profiles rather than conventional résumés, and companies doing background checks are almost certain to look for candidates’ LinkedIn profiles.

Encourage students to think of LinkedIn as a “socially networked multimedia résumé.” An effective LinkedIn profile includes all the information from a conventional résumé plus some additional features that help candidates present themselves in compelling ways to potential employers.

Here are nine tips to share with your students for building an effective profile:

  1. Photo. Add a photo that says “professional” without being overly formal. You don’t need to hire a professional photographer, but the photo needs to be clear and lit well enough so that your face isn’t in shadow. Stand against a visually “quiet” background that won’t distract viewers, dress appropriately for the jobs you are pursuing, and remember to smile.
  2. Headline. Write a headline that expresses who you are or aspire to be as a professional, such as “Data science major ready to make data come alive through leading-edge techniques in data mining, visualization, and AI.” Include keywords that target employers are likely to be searching for. As with other text fields on LinkedIn, you have a limited number of characters to work with here, so focus on your most valuable attributes.
  3. Summary. Write a summary that captures where you are and where you are going. Imagine that you are talking to a hiring manager in a personal and conversational tone, telling the story of where you’ve been and where you would like to go—but expressed in terms of meeting an employer’s business needs. Highlight your job experience, education, skills, accomplishments, target industry, and career direction. Unlike the introductory statement on your conventional résumé, which you can fine-tune for every job opportunity, your LinkedIn summary offers a more general picture of who you are as a professional. Be sure to work in as many of the keywords from your research as you can, while keeping the style natural. Employers can use a variety of search tools to find candidates, and they’ll look for these keywords.
  4. Experience. Fill out the experience section using the material from your conventional résumé. Make sure the details of your employment match your résumé, as employers are likely to cross-check. However, you can expand beyond those basics, such as by including links to photos and videos of work-related accomplishments.
  5. Recommendations. Ask for recommendations from people you know on LinkedIn. You may have a limited number of connections as you start out, but as your network expands, you’ll have more people to ask. A great way to get recommendations is to give them to the people in your network.
  6. Featured skills. List your top skills and areas of expertise. As you expand your network, endorse the skills of people you know; many users will endorse your skills in return.
  7. Education. Make sure your educational listing is complete and matches the information on your conventional résumé.
  8. Accomplishments. LinkedIn offers a variety of categories that let you highlight academic achievements, special projects, publications, professional certifications, important coursework, honors, patents, and more. If you don’t have an extensive work history, use this section to feature academic projects and other accomplishments that demonstrate your skills.
  9. Volunteer experience and causes. Add volunteering activities and charitable organizations that you support.

For the most current instructions on performing these tasks, students can visit the LinkedIn Help center at www.linkedin.com/help/linkedin. Remind them that the more robust they make their profiles, the better their chances are of catching the eye of company recruiters.

All three titles in the Bovée-Thill Business Communication Series offer in-depth advice on the full range of job-search communication, from researching job opportunities to crafting effective LinkedIn profiles. This coverage includes unique perspectives on personal branding, writing "the story of you," and the Build Your Career activities that guide students through the entire process of developing employment-related messaging. (Build Your Career is available in Excellence in Business Communication 13th Edition and Business Communication Today 15th Edition.)

 

Adapted from Courtland L. Bovée and John V. Thill, Business Communication Today, 15th Edition, 2021, pp. 540–541.

Encouraging Students to Apply Their Skills Now: Make QA a Routine Part of the Writing Process

When manufacturers produce something, an essential step in the process is quality assurance (QA), a methodical evaluation of the product’s quality relative to its design goals. This is the last chance before the product ships out to customers to make sure it is something the company can be proud of.

Encourage students to make QA an essential part of their communication efforts, whether they’re writing reports, crafting presentations, or completing any other type of assignment. By practicing now on assignments in all their classes, QA will be second nature when they’re writing and presenting on the job.

Just as in manufacturing, QA in writing is more effective if it follows an explicit, step-by-step process, rather than randomly looking for mistakes. If you haven’t already given your students a proofreading checklist, they can use the following tools:

  • In Business Communication Essentials, 8th ed: Table 5.4: Proofreading Tips, page 126
  • In Excellence in Business Communication, 13th ed: Checklist: Proofing Business Messages, page 206, and Five-Minute Guide to Revising and Proofreading, page 215
  • In Business Communication Today, 14th ed: Checklist: Proofing Business Messages, page 170

With each assignment, remind students to give themselves enough time to evaluate their first drafts, revise to improve readability, edit for clarity and conciseness, and then produce professional-quality output. Once they get in the habit, producing high-quality documents and presentations won’t take much more time and energy than producing mediocre work.

Self-Coaching Ideas for Your Students

  1. Do you ever feel the temptation to say, “Eh, that’s good enough” on an assignment when you know you could do better? What can you do to reset your priorities so that quality work is a matter of habit?
  2. Do you need to examine your work methods to make sure you leave enough time to do an effective QA check on every assignment?

 

Image credit: Stuart Whitmore

Intelligent Communication Technology: The Ethics of Artificial Intelligence

As one of the most powerful technologies ever developed, artificial intelligence (AI) is already influencing human life in multiple ways and promises to do so even more in the future. AI is now used in a variety of business communication applications, from message testing to employee recruiting and evaluation.

Although many of these developments are positive, AI shares the two-sided nature of every major technology: The power that enables it to be a positive force can also gives it the potential to become a negative force. Moreover, even with good intentions, it is impossible to foresee and control all the consequences that AI could unleash.

Two issues of particular concern from an ethical perspective are embedded biases and a lack of transparency and accountability.

Human Biases Embedded in AI Systems

Like all human creations, AI reflects the intentions and beliefs of its creators—sometimes consciously and sometimes subconsciously. Simplifying greatly, AI systems incorporate algorithms, or instructions, and data that those instructions operate upon. If either the algorithms or the data reflect human biases, the AI system will likely exhibit those same biases.

For instance, facial recognition systems, which are increasingly being used for security and identification purposes, are “trained” using large collections of photographs. What they learn depends to a large degree on the photos in those collections. When African American AI researcher Joy Buolamwini (see photo) discovered that some of the most widely used facial recognition systems had much higher error rates on female and nonwhite faces, she traced the problem to the photo sets they were trained on, which were composed of mostly white, male faces. The only way she could get some of the systems to recognize her face as a face at all was to wear a white mask.

The developers of these systems are making improvements, but the fact that the problems existed in the first place could reflect a lack of diversity in AI research. As Buolamwini put it, “You can’t have ethical AI that’s not inclusive. And whoever is creating the technology is setting the standards.”

Another area in which AI systems can exhibit bias is language processing, because they learn from human language usage, which can have patterns of bias that range from overt to deeply buried. For instance, in a test where otherwise identical résumés were presented to some employers displaying a European American name and to other employers displaying an African American name, the résumé with the European American name drew 50 percent more interview invitations. If AI systems take on biased behaviors from language usage, their ability to automate decision-making at lightning speed can propagate biases throughout business and society as a whole.

Other areas where AI systems can potentially exhibit bias include risk-assessment systems that purport to predict an individual’s likelihood of committing a crime and automated applicant-evaluation systems used to make lending and hiring decisions. However, these automated approaches have the potential to be less biased than human decision makers if they are programmed to focus on objective factors. In an important sense, we don’t want AI that can think like humans; we want AI that can think better than humans do.

Lack of Transparency and Accountability

One of the most unnerving aspects of some advanced decision-making systems is the inability of even their creators—much less the general public—to understand why the systems make some of the decisions they do. For example, an AI system called Deep Patient is uncannily effective at predicting diseases by studying patients’ medical data. In some instances, doctors don’t know how it reached its decisions, and the system can’t tell them, either.

This lack of insight has troubling implications for law enforcement, medicine, hiring, and just about any other field where AI might be used. For instance, if a risk-assessment system says that a prisoner is likely to reoffend and therefore shouldn’t be paroled, should the prisoner’s lawyers be able to cross-examine the AI? What if even the AI system can’t explain how it reached that decision?

The Efforts to Make AI a Force for Good

AI unquestionably has the potential to benefit humankind in many ways, but only if it is directed toward beneficial applications and applied in ethical ways. How can society make sure that the decisions made and the actions taken by AI systems reflect the values and priorities of the people who are affected? How can we ensure that people retain individual dignity and autonomy even as intelligent systems take over many tasks and decisions? And how can we make sure that the benefits of AI aren’t limited to those who have access to the science and technology behind it? For example, a high percentage of the available AI talent is currently concentrated in a handful of huge tech companies that have the money necessary to buy up promising AI start-ups. While this benefits Google, Amazon, and Facebook in their business pursuits, potential applications in other industries, agriculture, medicine, and other fields might be lagging behind for want of talent.

Recognizing how important it is to get out in front of these questions before the technology outpaces our ability to control it, a number of organizations are wrestling with these issues. One of the largest is the Partnership on AI, whose membership includes many of the major corporate players in AI and dozens of smaller companies, research centers, and advocacy organizations. Its areas of focus include ensuring the integrity of safety-critical AI in transportation and health care; making AI fair, transparent, and accountable; minimizing the disruptive effect of AI on the workforce; and collaborating with a wide range of organizations to maximize the social benefits of AI.

Individual companies are also helping in significant ways. Microsoft, for instance, is directing millions of dollars and some of its considerable AI talent to AI for Earth, a program that uses AI to improve outcomes in agriculture, water resources, education, and other important areas.

The spread of AI throughout business highlights the importance of ethical awareness and ethical decision-making. Only by building ethical principles into these systems can we expect them to generate ethically acceptable outputs.

 

Adapted from Courtland L. Bovée and John V. Thill, Business in Action, 9th ed (Pearson: 2020), 110–112.

Encouraging Students to Apply Their Skills Now: Think Now, Write Later

When students get a new assignment, they can be tempted to either dive in immediately so they don’t get into a schedule crunch later or put it off until the last minute—when they will definitely be in a schedule crunch.

Not surprisingly, the do-it-later approach isn’t always a successful way to work. Writing under a tight deadline can sometimes be invigorating, and time limits can help the mind stay focused, but mostly it’s just stressful and exhausting. Plus, there’s the potential problem of getting bogged down in complex issues at the last minute and not having enough time left to think through them or do additional research.

Somewhat more surprisingly, the do-it-right-now approach isn’t always the most productive way to write, either. When you sit down and command yourself to write something now, the mind has a funny way of rebelling and giving you nothing but a blank stare. Instead of figuring out what you need to say, you’ll start worrying about how to say it, and your inner editor will get in the way with criticism and self-doubt.

Encourage your students to try this modified approach instead. As soon as they get an assignment, dig into it but tell themselves they don’t need to do any writing right now. Just explore the topic, do some research, and start to fill their minds with nuggets of information—without worrying about how they’re going to say anything yet. Let these thoughts rumble around while they go off and do other things. Their minds will keep busy in the background, searching for connections between the bits of information they have collected, trying out ideas for organizing the piece, and generating useful phrases and other bits of text. The piece will gradually take shape somewhere between their conscious and subconscious mind before they begin to write, and when they do sit down to write, the words should flow faster and easier than trying to force them on command.

Self-Coaching Ideas for Your Students

  1. Do you ever find yourself in a panic when you try to start a writing project? If so, don’t get down on yourself; this can happen to everybody, including professional writers who have been honing their craft for decades. Try this trick: Tell yourself you need to write just one sentence. As you fine-tune that sentence, you’ll probably feel yourself settling into a groove, and the rest of the work will go easier from there.
  2. If you’re in the habit of putting writing projects off to the last minute, what are some changes you could make to get yourself into a more-controlled and less-stressful mode of work?

 

Photo: Yudis Asnar

CC BY

Encouraging Students to Apply Their Skills Now: Preparing for Difficult Conversations

No one welcomes the prospect of a difficult conversation, whether it’s with a professor, a parent, a spouse, a teammate, or anyone else. Remind students that while they may not be able to change the information that needs to be shared, they can take steps to make the conversation itself less upsetting—and to keep emotions from spiraling out of control. Encourage students to make these conversations as trauma-free as possible with these tactics:

  • Don’t put it off. Although it’s natural to want to avoid an unpleasant confrontation, waiting usually makes things worse because you have to live with the anxiety for that much longer.
  • Don’t go in angry. While you don’t want to put off a difficult conversation, don’t jump into it if you’re still angry about something that happened, even if your anger is justified. Anger can cloud your perception and spur you to make bad decisions or say things you’ll regret. Find a way to cool off first.
  • Don’t make excuses. If you made a mistake or failed to meet a commitment, own up to it. You’ll feel better about yourself and earn respect from the other person.
  • See things from the other side. Regardless of who is at fault—if anyone—take a moment to consider what the other person is going through.
  • Ask for help if you need it. Admitting you need help can be a difficult step. However, if you’re in trouble, the bravest course is often to ask for help.
  • Be the boss of your own emotions. Be conscious of your emotions and actively control them; don’t let them control you. This is not easy, but it can be done.
  • Be kind. Unless you’re being taken advantage of, you’ll never regret being kind to someone, regardless of the circumstances.

Self-Coaching Ideas for Your Students

  1. Do you ever find your emotions getting out of control when you’re having a difficult conversation? What steps could you take to keep them under control?
  2. Is there a difficult conversation that you’re putting off right now? If so, imagine the relief you’ll feel once you get it over with. Even if it’s likely to be a painful experience, it could be the start of repairing a damaged relationship or getting your life back on track.

Intelligent Communication Technology: Finding Meaning in Text Mining

You’ve probably experienced both these frustrations with search engines: You’re not quite sure which terms to use, so you poke around hoping you’ll find something relevant, or you get lots of irrelevant results that happen to include your search terms but have nothing to do with what you are looking for.

Text mining, also known as text analytics, promises the ability to find meaning and patterns in mountains of textual material by going far beyond conventional search capabilities. Unlike simple word and phrase searches that require exact or near-exact matches, text mining systems can find relevant material even if you don’t know the specific terminology the sources use, or if they use different words to express the same concepts. By applying linguistic principles through natural language processing, text mining systems can recognize meaning in context. This capability also helps text mining tools filter out irrelevant material that uses the same terms, such as excluding material about biological reproduction if you are searching for material about document or file reproduction.

Another major benefit of text mining is the ability to copy all the searched material and reorganize it into consistent records, even if it came from a variety of sources in different formats. For example, a system could be instructed to pull in social media posts, emails, and text messages and “clean” and merge them into a single data set for easier analysis.

Text mining is a potential solution whenever a business needs to analyze hundreds, thousands, or even millions of text records. Examples of current applications include product research and development (such as searching patent records for similar designs), sentiment analysis (finding trends of satisfaction or dissatisfaction in public tweets, customer emails, and other sources), competitive intelligence (finding out what competitors are up to by analyzing their document and social media output), and risk management (such as analyzing financial news and reports in search of potential risks).

Class activity ideas

  1. Natural language processing applies the same linguistic rules and concepts that humans use to encode and decode language. Ask students if they think computers will ever be able to understand text the way that humans can. Why or why not?
  2. How do students feel about their public social media posts being available for companies and other organizations to analyze?

 

Sources: “About Text Mining,” IBM Knowledge Center, accessed 7 April 2018, www.ibm.com; “What Is NLP Text Mining?” Linguamatics, accessed 7 April 2018, www.linguamatics.com; Text Mining Applications: 10 Examples Today,” Expert System, 18 April 2016, www.expertsystem.com.

The Next Wave of Innovation in Business Communication

The last few decades have been marked by waves of technology-driven innovation in business communication, starting with digital’s disruption of print communication, then social media giving a voice to everyone in the marketplace, followed by the way mobile is freeing communicators from their desks.

We’re well into the next wave, and this one could be the most intriguing and far-reaching of all: the application of artificial intelligence to enhance the communication experience. Starting with the upcoming 13th Edition of Excellence in Business Communication (releasing in January 2019) we are covering communication uses of AI that students are likely to encounter on the job or in their job-search efforts.

The Recent Explosion of Business AI

Although “artificial intelligence” still has a science fiction ring to it, forms of AI are now used extensively in business and business communication. It’s a virtual guarantee that your students are already experiencing AI as consumers—Amazon, Apple, Facebook, Google, Microsoft, Netflix, and Spotify are just a few of the companies that rely on AI to deliver their services.

Research in AI has been going on for more than a half century, but the practical outcomes never really lived up to hopes until recently, when several developments converged within the space of a few years. First, the primary focus of the research shifted from pursuing the generalized, humanlike intelligence of science fiction (sometimes called general AI or strong AI) to developing specialized systems aimed at handling specific tasks such as reading text or recognizing images (called narrow AI or weak AI). Second, an AI method involving neural networks, which emulate the function of neurons in the brain, was refined in a way that made it much more powerful. And third, several critical computer capabilities became available around the same time: massive sets of data that AI systems could learn from, low-cost storage to handle all that data, and fast processors capable of handling the number-crunching that the most-common AI approaches require.

Communication Applications of AI

Thanks to these developments, AI is now being applied in virtually every functional area of business. Many of these applications involve business communication, including augmented writing, automated writing, emotion recognition, job applicant evaluation systems, chatbots and taskbots, robotic process automation, cognitive automation, voice recognition, real-time voice translation, and augmented ability systems. Here are a few specific examples:

  • Businesses use text mining for social listening—identifying themes (such as prevailing customer sentiment or threats to a company’s reputation) hidden in mountains of written information, from Twitter and Facebook posts to customer emails and surveys. The Clarabridge image shown above (click on the thumbnail for a larger version) illustrates the use of social listening in the hospitality industry.
  • The Textio augmented-writing system gives company recruiters real-time writing feedback while they draft job postings. By analyzing hundreds of millions of postings and comparing the candidate pools they attracted, the system is figuring out the most compelling way to describe job opportunities. Plus, the system can help writers avoid biased or exclusionary language by showing how various demographic groups respond to different word choices.
  • Any of your students who play fantasy football on Yahoo! Sports might be intrigued to know that the game summaries they receive each week are written by an AI system.

From a user’s perspective, AI-enhanced communication isn’t skills-based to the same degree as social media and mobile communication, but we believe it has become a vital topic to address in any well-rounded business communication course. In future posts, we’ll explore many of these applications and discuss how they are giving professionals powerful new tools to improve communication efficiency and effectiveness.

 

Adapted from Excellence in Business Communication, 13th Edition, Pearson, 2020.

Image: Courtesy Clarabridge

Free Video for Classroom Use: Communication Ethics: How to Make Good Choices When Your Choices Aren’t Clear

BT VideosHere is the sixth video in our new series that addresses a variety of specific communication challenges and offers practical advice that students can apply now in their coursework and take with them on the job.

This video gives students a four-step decision model to guide them in making ethical communication choices.

Instructor version (concludes with information about the Bovée & Thill business communication series, including links to order examination copies)

Student version (identical to the instructor version, except for the textbook information)

Free Video for Classroom Use: The Five Zones of Professional Etiquette

BT VideosHere is the fifth video in our new series that addresses a variety of specific communication challenges and offers practical advice that students can apply now in their coursework and take with them on the job.

This video helps students adapt their behavior to the five zones of professional etiquette: in the workplace, online, on the phone, in social settings, and while using mobile devices.

Instructor version (concludes with information about the Bovée & Thill business communication series, including links to order examination copies)

Student version (identical to the instructor version, except for the textbook information)

Free Video for Classroom Use: Balancing Emotional and Logical Appeals for Persuasive Messages

BT VideosHere is the fourth video in our new series that addresses a variety of specific communication challenges and offers practical advice that students can apply now in their coursework and take with them on the job.

This video helps students understand how to find the optimum balance of emotional and logical appeals when crafting persuasive messages. Few message appeals are entirely emotional or entirely logical, so knowing enough about the audience to mix the right blend of appeals is essential to creating effective persuasive messages for both internal and external audiences.

Instructor version (concludes with information about the Bovée & Thill business communication series, including links to order examination copies)

Student version (identical to the instructor version, except for the textbook information)

1.6k