Leverages the long-term retention benefits of personalised and adaptive, spaced retrieval practice with feedback and concurrent metacognition.
Reports learner metrics and presents learning insights.
Removes the need for marking, releasing time for educators to use RememberMore's learning metrics and insights to inform their teaching practice.
Enables content curation and collaboration and deck management.
Unsupervised study, personalised study is as effective as supervised study.
If you need more evidence, our ResearchEd National Conference 2021 slides are here: ResearchEd
Introducing Year 10 and 11 English pupils to RememberMore saw an incredible investment of 1246 hours in the first half term.
There is more to retrieval practice than just retrieving
You may well be familiar with the "wealth of evidence" for the 'Testing Effect' or 'Retrieval Practice.'
Evidence outlining the benefits of the 'Testing Effect' or 'Retrieval Practice' is "unequivocal," Agarwal et al., (2021). In March 2021, Agarwal et al., (2021) and Yang et al., (2021) both published significant, systematic and meta-analytic reviews outlining extensive and convincing evidence for retrieval practice and also underlining the importance of "spacing" for effective long-term retention.
In a paper summarising the impact of testing on 48,478 students’ data, extracted from 222 independent studies, 573 effects, Yang et al., (2021) reported that testing yields a variety of learning benefits, "a reliable advantage" over other strategies, consolidating and potentiates learning. Furthermore, that Successive Relearning leads to "larger learning gains still."
Critically, Agarwal et al., (2021) compared classroom studies only. After screening 2000 abstracts, 50 real world educational settings papers made the cut, 49 effect sizes and a total 5,374 students data. Agarwal et al., (2021) found "a wealth of evidence," that retrieval practice "improved learning for a variety of education levels."
Latimer, Peyre and Ramus (2021) indicated a large advantage of spaced retrieval practice over massed retrieval practice (g = 1.01, 95% CI [0.68, 1.34]).
To conclude, retrieval practice seems to be a learning technique that is not moderated by individual differences or with working memory capacity, thus possibly beneficial for all students, Bertilsson et al., (2021).
"The three techniques we discussed here - practice testing, spaced practice, and successive relearning — are powerful and proven." Dunlosky and Rawson (2015).
Evidence for Successive Relearning
RememberMore draws heavily on the research of Dr Katherine Rawson and looks to leverage the "substantial" advantage of Successive Relearning over single-session learning and retrieval.
Vaughn, Dunlosky and Rawson (2016) demonstrated that Successive Relearning is extremely efficient. Just 7 mins was required to relearn 70 prelearned word pairs. More importantly that Successive Relearning throughout the semester markedly improve performance on a cumulative final exam.
Successive Relearning has been shown to dramatically boost students’ retention of simple verbal materials. Items correctly recalled three times during initial learning yielded 26% retention 1 week later. By comparison, items correctly recalled a total of three times across initial learning plus two relearning sessions yielded 68% retention 1 week later, a 262% increase in retention test performance," Rawson et al., (2018).
In two experiments, Janes et al., (2020) reported that Successive Relearning boosted students' learning of course content by at least 10% (d=0.54 to 1.10).
Most recently, Higham et al., (2021) reported that recall of course material at the end of the semester was better for relearning compared to restudying. Perhaps more importantly, that increased recall during relearning sessions was associated with further learning benefits including improved metacognition, increased self-reported sense of mastery, increased attentional control, and reduced anxiety. Furthermore, that students found successive relearning to be enjoyable and valuable.
"Human memory is fragile. The initial acquisition of knowledge is slow and effortful. And once mastery is achieved, the knowledge must be exercised periodically to mitigate forgetting," Lindsey et al., (2014).
Evidence for personalised review
"Personalized spaced" practice improved retention by 12.4% over massed practice, 8.3% over generic spaced practice. 1 month later, 16.5% over massed practice, 10.0% over generic spaced practice, Lindsey et al., (2014).
"Regular testing maximises long-term learning. The mere act of putting your memory to the test makes it stronger. It is a direct reflection of the principles of active engagement and error feedback. Taking a test forces you to face reality head-on, to strengthen what you know, and to realize what you don’t know," (Dehaene, 2020).
Evidence for confidence based assessment and concurrent metacognition
Couchman et al., (2016) investigated real-time metacognitive monitoring, or concurrent metacognition. Researchers found that confidence ratings for each individual question accurately predicted performance and were a much better decisional guide than retrospective judgements (post exam performance judgements). Furthermore, the metacognitive aspect of the task could heighten awareness and help participants self-regulate. Researchers reported that the average proportion correct for questions rated on a 5 points scale was 0.757 (SE=0.02) (where 0.6 is very high or very accurate) and furthermore that the correlation between confidence ratings and performance was significant. Couchman et al., (2016) goes as far as to suggest that the best strategy for learning is to "record confidence, as a decision is being made, and use that information when reviewing."
Courtinho et al., (2020) showed that when exam performance was compared between students with low and high monitoring accuracy, confidence rating accuracy predicted performance. The students who scored higher in monitoring accuracy performed better on the exam than those who scored lower. Why? "It prompted the students to engage in an analysis of knowledge. They evaluated their knowledge." Coutinho et al., (2020) confidence judgments were accurate indicators of performance with a significant benefit for students who rated their confidence compared to those that did not.
Confidence is the hall-mark of metacognitive judgements and the most commonly used for investigating metacognition. These predictions are usually made on a numeric confidence scale expressed as percentages, scale or binary rating.
Siedlecka et al., (2016) reported confidence accuracy percentages above 70%, "response accuracy always correlated with confidence."
Finally (Chen et al., 2019) reported improved coefficients r=.655 between judgements post testing, significantly higher than the correlation for re-study trials, r=.338, t=8.773, p<.001. With cured recall, superior to multiple choice or recognition recall.
On self assessment, the two meta-analyses, Graham et al., (2015) and Sanchez et al., (2017) demonstrated a positive association between self-assessment and learning, on average, “students who engaged in self-grading performed better (g = 0.34) on subsequent tests than did students who did not.”
Evidence for the interaction of Success and Motivation
Barenberg and Dutke (2019) examined the potential of retrieval practise during learning to improve the accuracy of confidence judgements in future retrieval. Pekrun et al., (2017) presented a reciprocal effects model linking emotion and achievement over time. Both lines of research enquiry underline the importance of educating "confidently correct" learners. RememberMore makes sure this happens.
"You can get a good deal from rehearsal,
If it just has the proper dispersal.
You would just be an ass,
To do it en masse,
Your remembering would turn out much worsal.”