knowledte - bunch of unconnected dots

experience - the same dots as before but connected with lines.
Image adapted from the artwork of gapingvoid, (Source)

By Toni DiMella

Higher education is a key factor in creating economic mobility as the majority of “good jobs”, as defined by the Georgetown University Center on Education and the Workforce, require at least a bachelor’s degree (Carnevale et al., 2017; Carnevale et al., 2018). This economic impact is most noticeable for those in the lowest quintile. As a result of the higher-earning potential afforded by a college degree (Torpey, 2019), nearly two-thirds of individuals born into the lowest income quintile who complete a degree reach the middle class or above, and 20 percent of them reach the top income quintile (Chetty et al., 2017).  

While career preparation is certainly not the only benefit of college, it is largely the one that gets students in the door. It’s also that increase of earnings that helps to create an environment for other benefits to occur, like homeownership or living a healthier lifestyle. Ultimately, you want your students to go out into the world and do something with all the knowledge you have helped them gather. We’re just not always clear about what those things are or how one would use that knowledge.

When we talk about transparency in teaching and learning (TILT) we’re usually focused on what students are going to do, when, and where. Things that largely only focus on the course. But we can add transparency to what we are doing in the course and why. It’s wonderful that the directions and grading criteria for your final project are crystal clear, that is important, but why are students doing that project? What is it preparing them for? What skills/knowledge/tools do they gain by completing it? That’s probably clear to you, but it rarely is to the students.

Using the Skills Extractor from Emsi can help you draw attention to what skills your course is helping students develop and even help you identify ones that you may not have thought of. Copy and paste your outcomes (or syllabus or case study) into the text field and the program will associate them with skills employers identify in job postings. I entered the course outcomes from one of my previous courses. This was the output:

screenshot of multiple outcomes with probability, sampling, random variable and confidence interval hyperlinked to skills.
The first output from the Skill Extractor

While the importance of the content is clear to me, seeing the job skills and postings that included the terms and information about related skills was powerful. Perhaps students who are not excited to learn about confidence intervals may find some, um, inspiration in the live job postings (and their salary ranges!).

Something else that caught my eye on the Emsi report—hypothesis test wasn’t highlighted. Read a statistical study about anything and it’s likely you see read results of a hypothesis test. Yet, that did not trigger as a skill. When I updated my outcome to be “Conduct statistical analysis, such as hypothesis tests for the mean” another skill was recognized. If it wasn’t clear to an AI that was designed to look for patterns in job skills that hypothesis testing is statistical analysis, then it’s likely the students didn’t make that connection either. It made me wonder what other marketable skills my students didn’t realize they were learning.

screenshot of multiple outcomes with probability, sampling, random variable, statistical analysis, and confidence interval hyperlinked to skills.
The second output from the Skill Extractor

Certainly, I thought, all my wonderful discussion and test questions that use real-world data and ask students to make inferences would make up for my underwhelming outcomes. Surely, students can see the direct relevance of those questions in the potential careers they may pursue. I entered three application questions that I asked that semester. The questions looked at bias and the jury selection process, comparing customer rating data for various drive-thrus, and examining median income and the number of COVID-19 cases by state. The Skills Extractor output was devastating. The drive-thru one was tagged as ‘restaurant operation.’ For the other two, ‘calculation’ was highlighted on one and ‘probability’ on the other. Ouch. These were great application problems that used real-world data. COVID was literally happening during the course! I was quite pleased with the questions; Emsi was not.

While computer programs are not particularly good at uncovering nuances, neither are 18- to 22-year-olds. It’s hard for an experience to be transformative you don’t realize you’re transforming course information and tasks into knowledge, skills, and expertise.  I’m sure some students made the connection between the questions and their real-world relevance, but EMSI suggests that it may be fewer than I thought. I want my students to be able to say in a job interview that they do have this experience because they performed statistical analysis in a class by looking at live COVID case data and presenting their findings. If I don’t let them know that employers might care, will they remember this experience during their interview?

The USC Upstate Moving UP QEP focuses on preparing career-ready students who can identify and articulate their knowledge, skills, abilities, experiences, and other characteristics as relevant to desired career goals; and explore identify, and address areas necessary for professional growth and success.” Expanding the focus of TILT from policy and procedure to include the “what and why” helps more students realize what skills they are learning and what they are good for. This can be accomplished by adding a purpose statement to the activity and including the objectives in the document. Additionally, referring to and/or linking to career pathways and skills would help students realize how to add the skills they are learning to their resumes. Your course activity could build one of those skills that helps them get a “good job.”