With much ado surrounding workforce skills gaps, retention challenges, and desire for learning and development opportunities, corporate training programs are more relevant than ever. However, while training offerings abound, achieving these varied workforce objectives requires expertly crafted course curricula and deftly guided training sessions, both of which rely upon professionals dedicated to educational excellence. This article, the first in a two-part series exploring the instructional design and delivery efforts that help workforce learners reach their goals, will explore the work instructors do to cultivate and maintain their instructional fitness.
Workforce training imparts emerging technology skills and knowledge most relevant to current organizational demands. Therefore, instructors must be perpetually dialed into these emerging technologies and the associated ethical implications that workers may encounter. Especially for training in dynamic technical areas, which can evolve rapidly, corporate training instructors must maintain their conditioning, just as Olympic athletes must train themselves constantly to avoid atrophy.
Successful course delivery is a measure of the new skills and information it relays and the degree to which it helps learners absorb, retain, and apply the tools they’ve acquired. Accomplishing these classroom feats requires instructors with numerous credentials and qualities, including:
Instructors nurture these attributes and keep their skills in top form through a variety of ongoing practices, including:
Acquiring new certifications. Even for seasoned data science professionals, delivering relevant data science skills to diverse cohorts often requires expanding and updating areas of expertise to keep pace with evolving enterprise technology. For example, two Data Society instructors, both data scientists who teach courses for NVIDIA’s Deep Learning Institute (DLI), have undergone extensive training to receive certifications in new skill areas and to become certified to teach these skills. As a result, one of these instructors has received eight certifications in the past year alone.
Taking the initiative to broaden skills independently. In addition to taking courses for required certifications, these instructors independently pursue coursework and projects that satisfy their appetites for continuous learning. For example, one instructor—who holds a Ph.D. in applied mathematics—plans to participate in a consulting project that will allow them to gain hands-on experience using the skills they acquired through recent certification courses. Another instructor—currently applying for Ph.D. programs in education data science—is taking a data structures course, routinely practices coding, and refreshes his subject knowledge each time he teaches a cohort. “Just by virtue of being an instructor, you’re constantly learning,” he points out, explaining that the ongoing learning that teaching demands is one of the reasons he wanted to become an instructor.
Closely following technology trends and their social implications. Beyond the hard skills and technical training instructors must master to guide their students effectively, high-quality instruction also demands awareness of the social impact and bias surrounding emerging technologies. This cognizance is vital in fields with significant community impact, such as data science. Therefore, with expanded access to applications come healthy concerns about how they relate to broader issues—including the importance of using diverse, ethically sourced data sets—that learners should understand as they incorporate these tools into their everyday work.
Instructors track the social and ethical discussions surrounding technology trends by reading extensively and participating in communities that share their interests. One Data Society instructor has subscriptions to multiple data science blogs, reading 10 to 15 articles each week, and follows social media conversations about current debates to maintain awareness and help nascent data scientists avoid pitfalls. “Keeping up with ethical issues in tech is important for all data scientists, but especially educators,” they note, explaining that nurturing upcoming data scientists carries responsibility for helping learners prevent the same mistakes that have led to damaging repercussions in the past. They add, “Data scientists hold a great power to affect the world, and we want to be sure that it’s positive.
Learning alongside learners. Effective instruction also demands awareness in other areas, such as individual learners’ and cohorts’ unique challenges and needs. Instructors strive to develop this understanding by asking learners about their workplace roles, interests, why they are taking the course, and what they hope to get out of it. Then, with their adaptability skills, instructors can apply these insights and their professional experience in various domains to provide instruction relevant to each learner’s field and function. For example, one Data Society instructor with experience in government, healthcare, politics, and social benefit projects says understanding their cohorts’ goals and industries helps them tailor examples and activities to maximize their learners’ engagement and investment in course subjects. Another Data Society instructor highlights a different angle of learning alongside students, observing that students ask questions that make instructors think about things in another way. In addition, he explains that he often works through problems in class so students can benefit from observing his problem-solving process live.
Responding in the moment. Also essential to adaptability is instructors’ capacity to respond readily to variations across and within learner groups. This instructional asset enriches learner experience and is supported effectively by live, instructor-led course delivery. “Different cohorts will have different needs, challenges, and strengths and work differently in terms of preferences,” a Data Society instructor points out, adding that some groups will need more time for exercises, ask questions in different ways, and approach courses from diverse backgrounds. These variables will help determine his time on various topics and activities.
Live, instructor-led training drives engaging, impactful learning experiences through instructor-learner synchronicity, which he explains fosters the “praxis” that makes course subjects applicable and accessible to all cohort participants. Another Data Society instructor notes that the immediacy of live, instructor-led training helps them adjust class pacing, provide examples that will resonate with learners in a given cohort, and even offer instruction appropriate to a range of skill levels within one cohort. In this learning environment, “The instructor can pivot quickly to the learning styles and levels of the students in the classroom.” For example, currently teaching a class that spans four levels, the instructor shares,
Corporate training instructors must continuously hone their subject matter expertise and be aware of the implications of ethical and social issues. In addition, soft skills such as adaptability consistently provide the highest quality educational experiences. In this article, we’ve seen that endless curiosity and a desire to continue learning about the subjects they teach and the learners they impact are essential to keeping them in top condition as instructors. Next week, in part two, we will explore the instructional design approaches that help learners absorb, retain, and apply their new skills.
Data Society provides customized, industry-tailored data science training solutions—partnering with organizations to educate, equip, and empower their workforce with the skills to achieve their goals and expand their impact.
