Teachers and managers share not only similar goals and tasks, but also similar failures.
In a recent consultation meeting of my training organization and a vice president in a large multinational firm who was giving us recommendations about preparing our students for the 2020s workforce, I had an epiphany. For the first time in my 20+ years of experience in corporate language and communication skill training, I was struck by the close parallel in the job descriptions of teachers and managers.
How are teachers and managers similar?
Professional teachers and trainers strive to build knowledge and competencies in their students. Professional Managers aim to heighten employee performance and productivity. And there is crossover: teachers manage learning, managers teach staff to achieve Key Performance Indicators, or KPIs.
Teaching and managing are both crafts, combining elements of both art and science. The art side involves creative ways to make the learning/working experience motivating and meaningful, while the science side involves measurement practices to verify how much learning/work was done. This approach in management is often summed up using the acronym SMART (Doran, 1981) objectives or goals, which are Specific, Measurable, Achievable, Relevant, and Time-bound.
Both teachers and managers start with the same question: What are my course’s goals for my students or quarterly goals for my team? These are typically a limited number of objectives, such as teaching students common email functions and useful phrases, or leading my sales team to achieve certain quotas for leads and sales.
Once objectives are fixed, timelines are set to achieve them. The plans are then executed with tasks, assignments, quizzes or regular update meetings to push the students/workers along the timeline towards achieving expected targets.
How do teachers and managers similarly fail?
When the end of the course or quarter arrives, grades and sales figures are tallied, and a pass/fail is usually assigned. But how do we really know if our students developed their understanding of course material, or whether our sales team used/developed their skills to their fullest potential. What evidence do we have for this?
Where is the evidence?
After more than 7 years of teaching in the early 2000’s, it finally dawned on me that the real art and science of teaching lies in assessment. In the commercial language schools, public colleges, corporate training environments I worked at, teachers were given full rein on assessment, but many teachers or trainers assumed that getting the students to do some practice (including tests) was enough for them to learn. Undoubtedly, practice of any sort will induce some sort of learning, but how effective or efficient is it?
Strangely, corporate training programs tend to be even less focused on assessment. It always amazes me in corporate training environments how relaxed HR officials are about this, at least about language or communication skill training — you would think they would demand clearer KPI measures and ROI given the company’s investment in upskilling or reskilling staff. But herein lies the mysterious and largely unknown and unchallenged realm of assessment in teaching and management.
But this is where the professional teacher’s/manager’s art and science come into play.
How can we know with any confidence to what extent our students have really learned the knowledge and developed the skills in our objectives, or assumed in the objectives?
For me, this question was an existential awakening.
I finally realized that goals need to be articulated and operationalized in terms of measurable tasks or quantifiable performances, i.e., with assessment in mind. Assessment is not an add-on at the middle or end of the course. It should drive the course planning and very architecture of the course. The real professionalism of the teacher lies in her understanding, planning, implementation and evaluation of assessment practices – only then can the teacher get a sense of how much something has been learned.
Managing with OKRs: helping employees set and achieve meaningful objectives
For managers, it is slightly different. John Doerr’s Measure What Matters (2018) is about as clear a guideline as you can get on heightening employee performance using OKRs (Objectives & Key Results). Hyper-achieving companies like Google, Intel, and Adobe are instructive in their institutionalized use of OKRs for all employees and departments: the Heads of the company clearly articulate their 3-4 quarterly Objectives and clear ways to measure their key results, which in turn cascade down to subsequent managers and all their employees, with each person making their own objectives with measurable key results to see if the objectives were attained. Employees are encouraged to not only align their objectives with the company’s but also add one or two of their own. All of these OKRs are often displayed in an app accessible to all employees, which makes them transparent and open to feedback, advice and assistance throughout the organization. Towards the end of the quarter, each staff self-evaluates their key results in a numbered score, and then sets new objectives for the next quarter to start a new OKR cycle.
To help manage and coach their staffs’ OKRs, managers use CFRs: regular Conversations to drive performance, Feedback on progress, and Recognition for achievements. To encourage bold Objective-setting, both compensation and blame are divorced from the (non-)achievement of OKRs; Google, for example, only uses OKRs for less than 33% of a staff’s performance rating. OKRs therefore help an organization in 4 ways:
- To make sure the organization and all of its employees focus on and commit to priorities,
- To align and connect objectives throughout the organization to enhance teamwork
- To track results for accountability, and
- Motivate employees to push themselves to achieve satisfying success and growth.
Teaching as engineering learning results: going from short- to long-term memory
Although teaching is quite similar to managing, it is also quite different. Managing is a long term, continuous game from one quarter to the next, while teaching is often episodic, often confined to a course duration of a few months. Students are also much more reliant and dependent on the teacher to achieve learning objectives; in this way, the teacher is more like an engineer of learning.
Teachers have a wide range of tools at their disposal to instill knowledge and help students develop their skills, which can range from physical to artistic, from cognitive to linguistic, or a combination of these depending on the course. The traditional skill teaching model is often labelled the 3P approach: the teacher Presents the material, gets the students to do structured Practice, and then guides the students to Produce the skills in their own creative way. As logical as this approach sounds, it assumes a much faster rate of learning and skill development than is possible for most learners. Traditional approaches, such as employed in many Asian countries and education systems, often eschew the 3rd P in favor of focusing on Teacher Presenting then student Practicing or testing, wrongly assuming rote-learning is sufficient for learning and long-term retention.
The problem in either the 2P or 3P approach is the transition — or lack thereof — going from the Practice to Produce. The 2P approach assumes long-term memory effects will happen with enough super-human rote learning effort, while the latter assumes moving from Practice to Produce is sufficient or simply the best that can be done given learning constraints. However, casual attempts to get learners to Produce and create their own learning products often fail since targeted new skills are naturally eschewed in favor of older, more familiar skills that are used as a crutch to complete the productive task; or if the Produce part elicits the right skills in the classroom context, they vanish outside the scaffolded classroom setting. In cognitive terms, the problem is simply how to move from short- to long-term memory (either physical or cognitive). This is the real challenge and obstacle that teachers need to address if they want to induce quality learning.
This is also where the “teaching as engineering” metaphor crumbles and learning psychology and statistics come into play. In other words, what types of learning tasks can probabilistically lead to higher quality and deeper learning outcomes and longer-term retention? Current educational trends are leaning in on collaborative problem- and project-based learning to activate a wider range of skills, commonly labelled 21st Century Skills (collaboration, critical thinking, creativity, communication), and tap into more meaningful engagement. Working together to analyze a problem and present its solution activates a wide range of social, cognitive and communicative skills — it also creates a clear product that is in itself fulfilling as a creative act.
However, I also see a temptation to let the pendulum swing to the collaborative extreme, thereby obscuring individual efforts that may never emerge or overly dominate depending on team dynamics. Measuring the Individual’s skills or knowledge is a challenge because they are shrouded by group dynamics. This is why a balanced view is needed: individuals should be tested on content, but they should also be evaluated in the application of multiple 21st Century skills in collaborative project- or problem-based learning. This can optimize the two types of learning potential. Take a course in sales skills to second language learners as an example. The strategies, psychological concepts and bits-and-pieces of knowledge, such as vocabulary and phrases needed in international sales, can be broadly tested in tests given to individual learners, whereas they can be more narrowly and deeply deployed and demonstrated more creatively and collaboratively in a video-based project of a sales role play based on investigating a specific buyer’s problems and needs for a specific product and then offering an appropriate tailored product presentation.
Teaching OKRs and Teaching CFRs
For teaching, the concept of OKRs can also be applied. Objectives here refers to the course goals. Using the example above, the sales skills course may have the following objectives:
- Learn psychological concepts and strategies in sales
- Learn the vocabulary and phrases appropriate for communicating those concepts and strategies
- Produce and perform a role-play solving a customer problem.
The Key Results for 1-2 may be to reach an 80% or higher score on a series of cumulative or repeated tests to provide evidence of mastery learning; and for 3, perhaps 2 or more collaborative tasks to design and perform a role play according to a rubric, tempered with a peer evaluation program like Teammates to encourage collaboration and shared effort.
In problem- and project-based learning, the teacher should be acting more like a facilitator, or manager, seeking out opportunities to engage in Conversations, offer Feedback, and distribute Recognition and praise. In this approach, learning can be demonstrated in a SMART (Specific, Measurable, Achievable, Relevant, and Time-bound) way.
Future: what will it take to fully implement OKRs in language and communication skills training?
To realize OKRs in communication training, what is required is a hierarchical knowledge and skills map to focus the relevant objectives in a time sequenced way. Sal Khan’s Khan Academy (n.d.) has already developed such a map for disciplines such as math. However, even though math can be seen as a language, it is a formal language, not a natural language like English or Japanese, which is a lot fuzzier and more difficult to establish a fine grained developmental sequence. Still, there are currently ongoing international efforts to set up international standards to develop such a language and skills map. The CEFR, or Common European Framework of Reference for languages, is a set of can-do statements spanning 6 levels of language proficiency, and Cambridge is using its extensive learner corpora of language test-takers to compile a more fine-grained Vocabulary Profile and Grammar Profile for English learners according to the 6 levels of the CEFR.
With these advances in knowledge mapping research and learning analytic technologies, language and communication teachers and trainers will soon be able to fully appreciate, absorb, and implement more effective SMART learning goals and specific OKRs to flesh out the science aspect of learning and become effective managers of learning.
References
Doerr, J. (2018). Measure what matters: How Google, Bono, and the Gates Foundation rock the world with OKRs. Penguin.
Doran, G. T. (1981). “There’s a S.M.A.R.T. way to write management’s goals and objectives”. Management Review. 70(11): 35–36.
Khan Academy. (n.d.) Khan Academy https://www.khanacademy.org/
