Brain-training news is promising, but the study choice is still evidence first
Recent brain-training coverage has revived a familiar learning question: if a game improves working memory, should students spend scarce study time on it? A February 2025 report from Northeastern Global News described research in which 568 undergraduates used working-memory games from the university’s Brain Game Center. The researchers found that students could improve on the training tasks, and that machine-learning models could predict different learning trajectories from factors such as prior working-memory ability, motivation-related traits, video game experience, and other learner characteristics.
That is interesting because it moves the conversation beyond a simple yes-or-no claim. The useful finding is not that one app automatically raises grades. It is that working-memory practice can produce measurable gains, learners differ in how they respond, and training data may help personalize practice. For classrooms, tutoring, and self-study, the harder question is whether those gains transfer to the academic work that matters: reading a difficult passage, solving multi-step problems, writing an argument, or studying for a cumulative exam.
A 2026 meta-analysis in npj Digital Medicine adds a cautious reason to take the topic seriously. The authors reported that computerized working-memory training produced behavioral gains on both trained and untrained tasks, but gains were larger for trained tasks than untrained tasks. That distinction matters. Near transfer means getting better at tasks similar to the practice. Far transfer means improvement reaches different, meaningful outcomes. Many flashy brain-training claims sound like far transfer, but much of the strongest evidence is still closer to near transfer.
There are also school-focused findings that deserve attention. A CESifo working paper from the ifo Institute on working-memory training in first graders reported immediate and lasting gains in working-memory capacity, positive spillovers to geometry, fluid intelligence, and inhibition, and a higher probability of entering the academic track three years later. A 2025 systematic review and meta-analysis in Frontiers in Education also concluded that working-memory training can improve reading, mathematics, and writing performance among Iranian students, while noting major heterogeneity and publication-bias concerns.
Why it matters for learners
Working memory is central to learning because it holds information in mind while a learner does something with it. A student uses it when comparing two fractions, following a teacher’s explanation, keeping track of a paragraph’s argument, or planning the next sentence in an essay. Weak working memory can make learning feel like losing the thread every few seconds.
But that does not mean the best response is to replace subject practice with generic memory games. If a learner needs to improve algebra, vocabulary, history writing, or biology problem solving, the most reliable study action is still practice that uses the target knowledge. Brain-training metrics can be motivating, but a rising game score is not the same as better transfer to classwork. The practical standard should be simple: keep any training only if it helps the learner perform better on untrained, meaningful tasks.
This is where recent evidence is most useful. It suggests that working-memory training may help some learners, especially when the practice is adaptive, sustained, and matched to the learner. It also suggests that educators and parents should ask sharper questions before buying a program or giving it a large share of study time.
Practical conclusion
The best learning choice is not to reject all brain training or accept every claim. Treat working-memory tools as possible support, not as the main study plan. Learners need routines that reduce unnecessary cognitive load and practice the real skills they are trying to improve.
- Ask what outcome the program proves. Improvement on the game is not enough; look for evidence on reading, math, writing, attention in class, or another meaningful goal.
- Use short trials with transfer checks. After two to four weeks, test whether the learner does better on fresh school-like tasks, not only on the app dashboard.
- Protect core study time. Retrieval practice, spaced review, worked examples, feedback, and targeted subject practice should not be crowded out by generic drills.
- Reduce working-memory load during real study. Break multi-step tasks into visible steps, write intermediate results down, use checklists, and remove avoidable distractions.
- Connect memory practice to content. If a student struggles with word problems, practice holding the problem structure in mind while solving actual word problems.
- Watch motivation honestly. A game that keeps a learner practicing may have value, but motivation should lead to stronger learning behavior, not just more screen time.
- Be skeptical of universal promises. Effects can vary by age, baseline skill, task type, training design, and how carefully the study measured transfer.
The practical learning conclusion is clear: working memory matters, and some training claims are becoming more sophisticated. Still, students should choose evidence-based study actions over flashy practice metrics. A useful tool earns its place when it improves the learner’s next real reading, problem, explanation, or exam performance.