Why “I Taught It” Does Not Mean “They Learned It”: What the Evidence Actually Shows

One of the most common frustrations I hear teachers express is, “I have taught them this already.” This observation is valid and deeply felt, but it requires a shift in perspective. Cognitive psychology and brain-based learning research offer a clear explanation: students filter out far more than they filter in, and teaching does not automatically lead to learning.

The opening chapters of Learning That Sticks (Goodwin, 2020) outline the scale of this filtering problem. Our sensory systems relay 11 million bits of information per second, yet the brain can consciously process only around 120 bits per second. This means that “our brains simply cannot squeeze 180 bits of information into a 120-bit mental pipe (Levitin, 2015).” Much of what is said in a classroom, therefore, never makes it past the sensory register. In a world where students receive “the equivalent of 174 newspapers of information every day,” the brain is constantly working to “separate the trivial from the important”, and often fails to do so effectively.

The implication is important: students are not ignoring us; their brains are overwhelmed. When teachers say, “I have told them this,” the science responds, “Yes, but their memory system has not yet encoded it.” Learning only begins when attention is secured, and attention depends on emotional safety, novelty, curiosity, and relevance. Emotional salience comes first in the brain’s “pecking order” for filtering stimuli: students attend to what feels urgent, meaningful, or emotionally loaded long before they notice content-heavy explanations.

Agarwal and Roediger (2018) demonstrate that learning strengthens not through exposure, but through retrieval, spacing, feedback, and interleaving. Simply hearing something, or even hearing it twice, does little for consolidation. Hattie and Donoghue (2016) likewise argue that the effectiveness of any strategy “depends on where in the learning cycle the student is located,” distinguishing between surface learning (initial knowledge), deep learning (connections and meaning-making), and transfer (application in new contexts). When teachers feel that students “should know this by now,” the evidence suggests that students are still in the acquisition or early consolidation phase, long before knowledge is stabilised in long-term memory.

Goodwin’s work helps explain why this consolidation phase is so fragile. Students arrive with cluttered “streams of consciousness,” often filled with anxiety, social pressures, and internal distractions. Emotional turbulence, including the effects of adverse experiences, directly affects the hippocampus, reducing the brain’s ability to convert short-term memories into long-term learning. Students dealing with high levels of stress “may struggle to retain new knowledge” and can appear disengaged, even when they want to learn. This does not mean lowering expectations; it means designing for learning, not assuming it. Saqr et al. (2023) show that high-performing learners are those who can transfer strategies across contexts, not simply remember what they were told in the original lesson. 

Transfer is not a by-product; it is the outcome of intentionally designed opportunities for students to monitor, adapt, question, and apply what they are learning. Hajian (2019) similarly distinguishes between “ordinary learning” and “desired transfer,” highlighting that understanding becomes meaningful only when students can use knowledge in dissimilar, unfamiliar contexts. Cherukunnath and Singh (2022) add that conceptual learning depends on cognitive development, motivation, and opportunities for deeper processing. Students do not simply absorb ideas; they must reorganise knowledge, integrate new information with prior understandings, and engage in metacognition to refine their thinking.

Taken together, these insights explain the teacher frustration in a new light: Students are not “forgetting what was taught”; they are revealing where learning has not yet been encoded, connected, or consolidated. The path forward is not repetition, but intentional design. To support students in “filtering in” what matters, we need to:

• capture attention through emotional safety, novelty, and curiosity
• sequence learning deliberately from surface to deep to transfer
• use cues and organisers that activate prior knowledge
• embed retrieval throughout units, not sporadically
• use errors productively as part of consolidation
• help students see clearly what they know and do not yet know
• teach strategies in context, not generically
• create opportunities for transfer across varied contexts
• provide feedback that guides adjustment rather than merely evaluates performance

The challenge is not that students are unmotivated or inattentive, but that the cognitive system is selective, overloaded, emotional, and developmentally primed to filter before it encodes. When we shift from “I said it” to “I designed for it,” we see learning in a different light: as a process requiring time, structure, safety, repetition, and meaning-making.

This understanding enhances teachers' professionalism. It gives us a scientific basis for designing lessons that work with the brain rather than against it, helping students move from fleeting exposure to lasting, transferable understanding.

References

Agarwal, P. K., & Roediger, H. L. (2018). Lessons for learning: How cognitive psychology informs classroom practice. Phi Delta Kappan, 100(4), 8–12. https://doi.org/10.1177/0031721718815666

Cherukunnath, D., & Singh, A. P. (2022). Exploring cognitive processes of knowledge acquisition to upgrade academic practices. Frontiers in Psychology, 13, Article 682628. https://doi.org/10.3389/fpsyg.2022.682628

Goodwin, B., & Ton, B. (2020). Learning that sticks: A brain-based model for K–12 instructional design [Chapters provided]. ASCD.

Hajian, S. (2019). Transfer of learning and teaching: A review of transfer theories and effective instructional practices. IAFOR Journal of Education, 7(1), 93–111. https://doi.org/10.22492/ije.7.1.06

Hattie, J. A. C., & Donoghue, G. M. (2016). Learning strategies: A synthesis and conceptual model. npj Science of Learning, 1(1), Article 16013. https://doi.org/10.1038/npjscilearn.2016.13

Saqr, M., Matcha, W., Uzir, N. A., Jovanović, J., Gašević, D., & López-Pernas, S. (2023). Transferring effective learning strategies across learning contexts matters: A study in problem-based learning. Australasian Journal of Educational Technology, 39(3), 35–57. https://doi.org/10.14742/ajet.8303