One-to-many teaching works best for the prepared student; leaves too many behind

Nov 09, 2025 Features / Columnists, News

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By Karen Abrams, MBA, AA Doctoral Candidate

(Kaieteur News) – Walk into any classroom and you see the silent triage. A handful of prepared students move with the teacher’s pace. Others stumble on a Tuesday, miss a Wednesday, and by Friday the gaps have begun to harden. Even the strong ones fall off when a lesson is rushed, a class is missed, or a concept goes unpracticed. Those gaps follow them term after term until the sentence appears that breaks a teacher’s heart: I hate math.

Bloom’s Taxonomy gives us language for what goes wrong. Picture it as a learning ladder that students climb, sometimes stepping back to steady their footing. The lower rungs are Remembering and Understanding, where learners recall facts and explain ideas; the middle rungs are Applying and Analyzing, where they use procedures in new situations and break problems into parts; the top rungs are Evaluating and Creating, where they judge quality and produce original work. Whole-class lessons often stay on the lower rungs. Too few students get the supported practice that moves them into Apply and Analyze, and fewer still reach Evaluate and Create. Learning should be a deliberate climb with checks at each rung. A single pace for thirty children skips rungs for many of them, and the ladder never quite holds.

There is a better way and the evidence is not minor. Benjamin Bloom’s famous “2-sigma” finding showed that one-to-one tutoring with mastery learning can move an average student two standard deviations above a typical class. In practical terms, that is the difference between middle of the pack and near the very top. Bloom framed a challenge that still stands; find ways for group instruction to borrow the power of individual tutoring.

A quick pause on what those research numbers mean. Education studies often report results in standard deviations. Think of the bell curve on a national exam. A gain of 0.2 to 0.3 standard deviations can shift a typical student from the 50th percentile to somewhere around the upper 50s or low 60s. A full 1.0 standard deviation is roughly the jump from average to about the 84th percentile.
Modern tutoring research backs Bloom with scale and nuance. The best meta-analyses of randomized experiments find consistent, substantial gains, with average effects around one third of a standard deviation, and larger gains when programs are structured and staffed by trained adults. That is a meaningful shift in real classrooms.

Crucially, personalization does not have to be expensive or flashy. During school closures in Botswana, a team tested low-tech phone calls paired with SMS math problems to parents. Students learned more, with gains around 0.12 standard deviations, and the program ranked among the most cost-effective interventions measured. The lesson was simple. If you meet a child precisely where they are and give timely feedback, learning moves, even over a basic handset.

Motivation sits beside cognition. Self-Determination Theory reminds us that students lean into hard work when three needs are met; competence, autonomy, and relatedness. Technology can help with the first two by sizing the next problem correctly and letting students control pace and pathways. But relatedness matters just as much. A weekly check-in, a short conference, a message to a parent about a small win. Students persist when they feel seen by an adult who knows their goals and notices their effort. Any “AI solution” that ignores that human bond will underperform.  

Guyana’s numbers should focus the mind. For example, CSEC Mathematics pass rates rose from 27 percent in 2024 to 32 percent in 2025. Progress is welcome, yet the share of students who fall off the math ladder remains far too high for an oil-rich country with aspirations to lead. The one-to-many model in a crowded room cannot erase cumulative skill gaps that begin in primary school and widen each term. We need instruction that starts from what each student knows right now and verifies mastery before moving on.

What does that look like on Monday mornings? Individualized lessons that diagnose the next missing skill and teach it with stepwise hint or second tries quick teacher-led mini-lessons for students, who share a misconception. Mastery gates that require a modest threshold before new content unlocks. A dashboard that tells the adult who needs a nudge, who needs praise, and who needs a harder set.

The classroom keeps its community and discussion. The practice layer becomes personal and accountable.

This is exactly the niche our Pathway Online lessons are built to fill as a support to schools and pods. Students get AI-assisted practice in Math and English with instant feedback and text-to-speech for learners who need it. Facilitators and teachers see where each child is stuck and intervene quickly. In early cohorts we are seeing roughly a 30 percent improvement on internal assessments. These results are preliminary and we will report fuller data as samples grow, but the pattern lines up with what the global evidence says should happen when practice is targeted and feedback is fast.

The one-to-many lesson will always have a place. Children deserve the shared joy of a great explanation and a lively discussion. But equity in a fast-growing Guyana requires more than a good lecture. It requires many on-ramps, frequent checks, real practice, and a steady adult hand on the shoulder. When we match the right task to the right learner and protect the human bond that keeps a child coming back, the gaps close. The sentence changes; not I hate math. I can do this.

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• Karen Abrams, teaching

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