What predicts academic achievement?
A large body of research has shown that executive functions like working memory, attention and self-regulation shape a person’s capacity to learn. However, few studies have assessed whether such functions can predict learning outcomes over a protracted period of time and development, such as the 10 years between early childhood and adolescence. Similarly, few have controlled for social and demographic variables.
Addressing these shortcomings, the authors of this study find that only working memory (but not attention or self-regulation) at age four and a half predicts academic achievement at age 15. The study also shows that a child’s working memory capacity predicts their adolescent working memory capacity, whereas the same could not be said for attention or self-regulation.
Ahmed et al. (2019). Executive function and academic achievement: longitudinal relations from early childhood to adolescence. Journal of Educational Psychology 111(3): 446-458. https://dx.doi.org/10.1037/edu0000296
Learning where rewards are warps internal maps
Our memory systems are intimately linked with location. The hippocampus, which is important for autobiographical memories as well as memories for facts and events, has cells (place cells) that signal location. Similarly, cells in the entorhinal cortex encode position by being active in a. These so-called grid cells have been termed “the brain’s GPS”.
In this study, researchers show that your brain’s GPS is flexible, re-mapping to account for cognitive factors like reward. As rats learned the location of rewards in an arena, both place cells and grid cells shifted their preferred firing locations towards where the rewards were found. This indicates that animals do not have an absolute representation of space, but instead one influenced by important features like memory of reward.
Boccara et al. (2019) The entorhinal cognitive map is attracted to goals. Science 363(6434): 1443-1447. DOI:
What forms of teacher-student dialog best promote learning?
Teachers don’t just communicate information and concepts to students. They also strive to engage students in dialog that promotes deeper thought, encouraging comments and ideas to be questioned and challenged.
In this study, researchers sought to identify the most effective forms of teacher-student dialog. Their results suggested three positive predictors of student performance: elaboration, in which students build on or clarify a statement of their own or one of their peers (potentially at the teacher’s direction); querying, in which the student is encouraged to question or challenge statements made in the classroom; and student participation, or the degree to which students are given the chance to engage in dialog. The authors recommend that teachers ask open-ended questions and encourage students to challenge and elaborate on content as it arises.
Howe et al. (2019) Teacher-student dialogue during classroom teaching: does it really impact on student outcomes? Journal of the Learning Sciences DOI:
Remote memory retrieval
Our memories are not stable. With time they are modified and, at a biological level, become redistributed throughout the brain. In this study, researchers show in mice that the neural substrate of a memory – the set of neurons active during memory formation and retrieval – is dynamic, rather than stable.
Specifically, the study revealed that the population of neurons active during recall of remote memories (in this case, 28 days after learning) is different to (but overlaps with) the population needed during learning or shortly after learning. The authors also show that the set of brain regions involved in memory recall evolves with time, becoming more dependent on cortical rather than subcortical structures. In all, this work provides further evidence for dynamic memories, both at cellular and systems levels.
DeNardo et al. (2019) Temporal evolution of cortical ensembles promoting remote memory retrieval. Nature Neuroscience 22: 460-469. DOI: https://doi.org/10.1038/s41593-018-0318-7