The Evidence

Most all practice is good, but not all practice is equal.

Learning science has identified 10 techniques that build durable skills. AI simulation tools typically draw on up to three. Prism is built around all of them. All these practice tools are good; we have designed Prism to be optimized.

What other tools do

technique present

not present

Second Nature

Retrieval practice

Corrective feedback

Quantified AI

Retrieval practice

Corrective feedback

Spaced practice (claimed)

Hyperbound

Retrieval practice

Corrective feedback

Some component targeting

Yoodli

Retrieval practice

Corrective feedback

Component practice (self-directed)

The 10 techniques and what each one does for your reps

Spaced practice

~10% more recalled vs. same-time massed sessions (Cepeda et al., 2006)

Retrieval practice

g = 0.51 vs. re-reading; g = 0.93 vs. no practice (Adesope et al., 2017)

Interleaved practice

g = 0.42; forces reps to choose the right move, not just repeat one (Brunmair & Richter, 2019)

Component skill isolation

d = 0.79 for part-to-whole design vs. whole-task practice from day one (Costa et al., 2022)

Variability of practice

d = 0.38-0.57 for transfer; varied conditions build skills that hold under pressure (Brady, 2004)

Self-explanation

d = 0.54; reps who explain their reasoning retain skills longer (Dunlosky et al., 2013)

Corrective feedback

d = 0.41-0.55 for task-level feedback; near-zero for praise without correction (Hattie & Timperley, 2007)

Pre-practice priming

10-15% gain; attempting before instruction primes deep encoding (Richland et al., 2009)

Transfer-appropriate practice

Practice must match real call conditions. Flashcards don't transfer to live negotiations (Morris et al., 1977)

Individualized design

3x higher effect size when practice is expert-designed for the individual (Debatin et al., 2023)

Prism does all 10
You could read every paper and build this yourself. (The links are below.) Most sales enablement vendors haven't. This is the scientific basis for why all practice, and all AI practice systems, are not created equal. We have.

References

Adesope, O. O., Trevisan, D. A., & Sundararajan, N. (2017). Rethinking the use of tests: A meta-analysis of practice testing. Review of Educational Research, 87(3), 659-701. https://doi.org/10.3102/0034654316689306

Brady, F. (2004). Contextual interference: A meta-analytic study. Perceptual and Motor Skills, 99(1), 116-126. https://doi.org/10.2466/pms.99.1.116-126

Brunmair, M., & Richter, T. (2019). Similarity matters: A meta-analysis of interleaved learning and its moderators. Psychological Bulletin, 145(11), 1029-1052. https://doi.org/10.1037/bul0000209

Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132(3), 354-380. https://doi.org/10.1037/0033-2909.132.3.354

Costa, J. M., Miranda, G. L., & Melo, M. (2022). Four-component instructional design (4C/ID) model: A meta-analysis on use and effect. Learning Environments Research, 25(2), 445-463. https://doi.org/10.1007/s10984-021-09373-y

Debatin, T., Hopp, M. D., Vialle, W., & Ziegler, A. (2023). The meta-analyses of deliberate practice underestimate the effect size because they neglect the core characteristic of individualization. Current Psychology, 42(13), 10815-10825. https://doi.org/10.1007/s12144-021-02326-x

Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students' learning with effective learning techniques. Psychological Science in the Public Interest, 14(1), 4-58. https://doi.org/10.1177/1529100612453266

Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81-112. https://doi.org/10.3102/003465430298487

Morris, C. D., Bransford, J. D., & Franks, J. J. (1977). Levels of processing versus transfer-appropriate processing. Journal of Verbal Learning and Verbal Behavior, 16(5), 519-533. https://doi.org/10.1016/S0022-5371(77)80016-9

Richland, L. E., Kornell, N., & Kao, L. S. (2009). The pretesting effect: Do unsuccessful retrieval attempts enhance learning? Journal of Experimental Psychology: Applied, 15(3), 243-257. https://doi.org/10.1037/a0016496