Athletes of all levels deserve environments optimized for motor learning and skill acquisition.
Evidence-based tools, frameworks, and research for sport coaches, coach developers, and education leaders.
Explore the strategy map About the SASS-SCAbout the Lab
A gap exists between evidence-based pedagogical practices aimed at enhancing motor learning and performance, and what takes place on the field in coaching and physical education.
Coach education has focused primarily on the technical, sport-specific side of coaching — what to coach. Out of 285 coach development programmes reviewed by Lefebvre and colleagues, three addressed pedagogy. The result is that coaches are certified largely on what they know about their sport, and left to work out how to teach it.
That matters because time spent listening is time away from the perception-action workspace. Coordination does not emerge from listening.
The Skill Acquisition Lab exists to close that gap: to make what the motor learning literature actually supports — including where it is contested — usable by the people running practice.
Faculty and Director of Pedagogical Support, Exercise & Sport Studies, Smith College · PhD candidate, Rocky Mountain University of Health Professions · Formerly Education Manager, USA Archery
I teach motor learning and coach education at Smith College, where I support the faculty and instructors who deliver our performance courses and our S.M. in Sport Coaching. Before that I led coach education at USA Archery, building development pathways around a competency matrix, an athlete development model, and a quality coaching framework.
My doctoral research develops the SASS-SC, a scale for measuring how frequently coaches apply evidence-based motor learning strategies. What I teach and what I research are the same problem approached from two directions.
SAM-SAS
How the strategies available to a coach relate to one another — and where the hierarchy stops being able to explain them.
A second axis runs through all of it. Stage of motor learning is not a node either. Whichever strategy a coach reaches for, the choice is keyed to where the athlete is: “Regardless of the theoretical preferences of a coach, coaches can adapt instructional strategies, such as constraints, to optimize the level of challenge for a participant’s stage of motor learning.”
The instrument
Skill Acquisition Strategies Scale for Sport Coaches.
The SASS-SC is a 50-item self-report scale measuring how frequently sport coaches use evidence-based motor learning strategies. Coaches rate each item against the past two weeks on a seven-point frequency scale, from never to every time. Five subdomains, ten items each, no reverse-scored items.
The SASS-SC is not intended to provide a measure of coach quality. Receiving a higher score on certain items would not necessarily indicate better coaching quality compared to a coach who scored lower on certain items.
Asking coaches to recall whether they implemented a particular motor learning strategy measures their perception of what took place — not how that strategy was received by the learner, or what came of it. A higher score does not mean more learning happened.
The scale is under development. Content validity work is complete; factor analysis and reliability testing are underway. It has not yet been validated, and no claim on this site should be read as saying otherwise. Anything published here about its performance will be published with its limitations attached.
Rate yourself after a session or at the end of a week, and look at the pattern rather than the score. Which strategies do you reach for by default, and which have you simply never tried?
Read the items before you design a session, as an evidence-informed menu of strategies you might consider on any given day.
Coach developers and departments can use the items to talk about how coaching happens, not just what gets coached.
Resources
Every source below appears in the reference list of the dissertation behind the SASS-SC. Where the evidence conflicts, it says so.
Wulf, G., & Lewthwaite, R. (2016). Optimizing performance through intrinsic motivation and attention for learning: The OPTIMAL theory of motor learning. Psychonomic Bulletin & Review, 23(5), 1382-1414. https://doi.org/10.3758/s13423-015-0999-9
The paper this subdomain rests on. OPTIMAL argues attention and motivation are not separate levers but combine — external focus, autonomy support and enhanced expectancies work better together than any of them alone.
Wulf, G., McNevin, N., & Shea, C. H. (2001). The automaticity of complex motor skill learning as a function of attentional focus. The Quarterly Journal of Experimental Psychology Section A, 54(4), 1143-1154. https://doi.org/10.1080/713756012
Where the constrained action hypothesis comes from: consciously attending to your own body constrains the motor system and undermines automaticity. The mechanism behind almost every external-cue recommendation you will hear.
Chua, L. K., Jimenez-Diaz, J., Lewthwaite, R., Kim, T., & Wulf, G. (2021). Superiority of external attentional focus for motor performance and learning: Systematic reviews and meta-analyses. Psychological Bulletin, 147(6), 618-645. https://doi.org/10.1037/bul0000335
The largest synthesis of external versus internal focus. External wins on performance, retention and transfer, and age, health and skill level did not moderate the effect — a stronger claim than most in this field.
Nicklas, A., Rein, R., Noël, B., & Klatt, S. (2024). A meta-analysis on immediate effects of attentional focus on motor tasks performance. International Review of Sport and Exercise Psychology, 17(2), 668-703. https://doi.org/10.1080/1750984x.2022.2062678
Confirms external over internal, and distal cues over proximal, but reports confidence intervals wide enough that the authors decline to generalise across all tasks and skill levels. Read alongside Chua for the honest range.
Wulf, G. (2013). Attentional focus and motor learning: a review of 15 years. International Review of Sport and Exercise Psychology, 6(1), 77-104. https://doi.org/10.1080/1750984x.2012.723728
A narrative review of 54 studies, 46 of them favouring external focus. Useful for seeing how consistent the pattern looked before the more cautious recent syntheses.
Carnero-Diaz, A., Pecci, J., Calvo Lluch, Á., & Camacho-Lazarraga, P. (2025). Use your imagination for better performance. Effects of analogy instruction in motor skills. A systematic review and meta-analysis. Psychology of Sport and Exercise, Article 102766. https://doi.org/10.1016/j.psychsport.2024.102766
Analogies outperformed explicit instruction for novices and youth — but explicit instruction held up better under stress. The authors argue analogy is underused in coaching and physical education.
Schoenfeld, B. J., Vigotsky, A., Contreras, B., Golden, S., Alto, A., Larson, R., Winkelman, N., & Paoli, A. (2018). Differential effects of attentional focus strategies during long-term resistance training. European journal of sport science, 18(5), 705-712. https://doi.org/10.1080/17461391.2018.1447020
The clearest exception to the rule. For building muscle in resistance training, internal cues outperformed external ones. If you coach strength, this is the study that stops you over-applying external focus.
Moran, J., Hammami, R., Butson, J., Allen, M., Mahmoudi, A., Vali, N., Bakhsh, J. M. K., Gholami, F., Pargaveh, M., & Sandercock, G. (2023). Do verbal coaching cues and analogies affect motor skill performance in youth populations? PLoS One, 18(3), e0280201. https://doi.org/10.1371/journal.pone.0280201
Cues built without the athlete’s needs and preferences in mind are less effective. A reminder that a cue is a communication, not an incantation.
McKay, B., Hussien, J., Vinh, M. A., Mir-Orefice, A., Brooks, H., & Ste-Marie, D. M. (2022). Meta-analysis of the reduced relative feedback frequency effect on motor learning and performance. Psychology of Sport and Exercise, 61, 102165. https://doi.org/10.1016/j.psychsport.2022.102165
Seventy-five studies, 2,228 participants, and no clear support for the guidance hypothesis or for reduced feedback frequency improving learning. The authors describe much of the literature as severely underpowered.
Petancevski, E. L., Inns, J., Fransen, J., & Impellizzeri, F. M. (2022). The effect of augmented feedback on the performance and learning of gross motor and sport-specific skills: A systematic review. Psychology of sport and exercise, 63, 102277. https://doi.org/10.1016/j.psychsport.2022.102277
High risk of bias in 18 of 24 studies, and conflicting evidence on feedback frequency, timing and duration. Worth reading before committing to any particular feedback schedule.
Lindsay, R. S., Larkin, P., Kittel, A., & Spittle, M. (2023). Mental imagery training programs for developing sport-specific motor skills: a systematic review and meta-analysis. Physical Education and Sport Pedagogy, 28(4), 444-465. https://doi.org/10.1080/17408989.2021.1991297
Motor imagery produces a real effect on performance, strongest when combined with physical practice. The authors note how little of this work has been done in coaching or physical education settings.
Winkelman, N. (2021) The language of coaching: The art and science of teaching movement. Human Kinetics.
The most usable book on cueing. Translates the attentional focus literature into language you can actually say on a field.
Guadagnoli, M. A., & Lee, T. D. (2004). Challenge point: A framework for conceptualizing the effects of various practice conditions in motor learning. Journal of Motor Behavior, 36(2), 212-224. https://doi.org/10.3200/JMBR.36.2.212-224
The Challenge Point Framework: there is an optimal difficulty at which learning is maximised, and comfortable high performance in practice is often a sign that little learning is taking place.
Bootsma, J. M., Hortobágyi, T., Rothwell, J. C., & Caljouw, S. R. (2018). The role of task difficulty in learning a visuomotor skill. Medicine and Science in Sports and Exercise, 50(9), 1842-1849. https://doi.org/10.1249/mss.0000000000001635
Found that increasing task difficulty changed performance but not learning, and argued the framework may oversimplify. A small sample and a star-tracing task, so read it as a serious challenge rather than a refutation.
Csikszentmihalyi, M. (2014). The collected works of Mihaly Csikszentmihalyi. Springer.
Flow. Pairs naturally with challenge point — too easy and athletes disengage, too hard and they become anxious.
Newell, K. M. (1986). Constraints on the development of coordination. In M. G. Wade & H. T. A. Whiting (Eds.), Motor development in children: Aspects of coordination and control (pp. 341-361). Springer. https://doi.org/10.1007/978-94-009-4460-2_19
Interacting constraints: task, environment, individual. The vocabulary in which almost every difficulty adjustment you make can be described.
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257-285. https://doi.org/10.1016/0364-0213(88)90023-7
Cognitive load theory. Why simplifying a task can help a beginner and hold back an advanced athlete.
Fontana, F. E., Furtado Jr, O., Mazzardo, O., & Gallagher, J. D. (2009). Whole and part practice: A meta-analysis. Perceptual and Motor Skills, 109(2), 517-530. https://doi.org/10.2466/pms.109.2.517-530
Whole versus part practice. The decision turns on task complexity and organisation, not on a general preference for either.
Chan, J. S., Luo, Y., Yan, J. H., Cai, L., & Peng, K. (2015). Children’s age modulates the effect of part and whole practice in motor learning. Human Movement Science, 42, 261-272. https://doi.org/10.1016/j.humov.2015.06.002
The whole-versus-part advantage reverses with age: fifth graders learned juggling better whole, first and third graders better in parts. The clearest evidence that breaking a skill down is a judgement, not a rule.
Moradi, J., Maleki, M., & Moradi, H. (2023). The effect of part and whole practice on learning lay-up shot skill in young and adolescent male students. Journal of Motor Learning and Development, 11(1), 143-153. https://doi.org/10.1123/jmld.2022-0033
Basketball lay-ups with young and adolescent players. Broadly replicates the age pattern — part practice suited the younger group, whole practice the older.
Mousavi, S. M., Dehghanizade, J., & Iwatsuki, T. (2022). Neither too easy nor too difficult: Effects of different success criteria on motor skill acquisition in children. Journal of Sport and Exercise Psychology, 44(6), 420-426. https://doi.org/10.1123/jsep.2022-0082
Broadening the criterion for success improved retention and transfer in children. One of the more directly usable findings in this subdomain.
Beik, M., Taheri, H., Saberi Kakhki, A., & Ghoshuni, M. (2021). Algorithm-based practice schedule and task similarity enhance motor learning in older adults. Journal of Motor Behavior, 53(4), 458-470. https://doi.org/10.1080/00222895.2020.1797620
Algorithmic practice — switching between block, serial and random based on the learner’s error rate — beat any single schedule for retention and transfer.
Hodges, N. J., & Lohse, K. R. (2022). An extended challenge-based framework for practice design in sports coaching. Journal of Sports Sciences, 40(7), 754–768. https://doi.org/10.1080/02640414.2021.2015917
An extended challenge-based framework bringing error, difficulty and the learner’s own state together. A more recent theoretical home than the challenge point framework alone.
Coker, C. A. (2022). Motor learning and control for practitioners, (5th ed.). Routledge. https://doi.org/10.4324/9781003039716
The textbook most working coaches will find usable across this whole map, not just this subdomain.
Ryan, R. M., & Deci, E. L. (2017). Self-determination theory: Basic psychological needs in motivation, development, and wellness. The Guilford Press. https://doi.org/10.1521/978.14625/28806
Self-determination theory. Autonomy, competence and relatedness as the drivers of motivation — the account underneath most of what follows.
Bandura, A. (1997). Self-efficacy: The exercise of control. WH Freeman and Company.
Self-efficacy: belief in your own capacity to succeed as a determinant of effort and persistence.
Wulf, G., Lewthwaite, R., Cardozo, P., & Chiviacowsky, S. (2018). Triple play: Additive contributions of enhanced expectancies, autonomy support, and external attentional focus to motor learning. Quarterly Journal of Experimental Psychology, 71(4), 824-831. https://doi.org/10.1080/17470218.2016.1276204
‘Triple play’. Enhanced expectancies, autonomy support and external focus combined outperform any pair of them. If you change one thing about a session, this argues for changing all three.
Chua, L. K., Wulf, G., & Lewthwaite, R. (2018). Onward and upward: Optimizing motor performance. Human Movement Science, 60, 107-114. https://doi.org/10.1016/j.humov.2018.05.006
Companion to the above: building those three elements in progressively has an immediate additive effect on performance.
Bacelar, M. F., Parma, J. O., Murrah, W. M., & Miller, M. W. (2024). Meta-analyzing enhanced expectancies on motor learning: Positive effects but methodological concerns. International Review of Sport and Exercise Psychology, 17(1), 587-616. https://doi.org/10.1080/1750984x.2022.2042839
Enhanced expectancies help learning — with a positive effect the authors themselves judge likely overestimated because of reporting bias. An unusually candid meta-analysis.
Parma, J. O., Bacelar, M. F., Cabral, D. A., Lohse, K. R., Hodges, N. J., & Miller, M. W. (2023). That looks easy! Evidence against the benefits of an easier criterion of success for enhancing motor learning. Psychology of Sport and Exercise, 66, 102394. https://doi.org/10.1016/j.psychsport.2023.102394
The sharpest test of easing success criteria. It clearly raised self-efficacy and perceived competence, and raised motivation where practice volume was high, but did not improve learning at all. Best understood as a way to sustain engagement, not to accelerate skill.
Jaitner, D., & Mess, F. (2019). Participation can make a difference to be competitive in sports: A systematic review on the relation between complex motor development and self-controlled learning settings. International Journal of Sports Science & Coaching, 14(2), 255-269. https://doi.org/10.1177/1747954118825063
Thirty-two studies: self-controlled groups usually learned better than controls and never worse. The strongest case for giving athletes choice.
St. Germain, L., McKay, B., Poskus, A., Williams, A., Leshchyshen, O., Feldman, S., Cashaback, J. G. A., & Carter, M. J. (2023). Exercising choice over feedback schedules during practice is not advantageous for motor learning. Psychonomic Bulletin & Review, 30(2), 621-633. https://doi.org/10.3758/s13423-022-02170-5
A large, well-powered experiment in which choice improved neither learning nor perceptions of autonomy, competence or motivation. Read directly against Jaitner and Mess.
De Meester, A., Galle, J., Soenens, B., & Haerens, L. (2024). Perseverance in motor tasks: The impact of different types of positive feedback. Physical Education and Sport Pedagogy, 29(2), 221-234. https://doi.org/10.1080/17408989.2022.2054969
Not all positive feedback is equal. Process-oriented feedback produced more persistence in 9–13 year olds than person-oriented or neutral feedback.
Smith, K., Burns, C., O’Neill, C., Duggan, J. D., Winkelman, N., Wilkie, M., Coughlan, E. (2023). How to coach: A review of theoretical approaches for the development of a novel coach education framework. International Journal of Sports Science & Coaching, 18(2), 594-608. https://doi.org/10.1177/17479541221136222
‘How to coach.’ Reviews coach education frameworks and finds how-to-coach content largely absent. The paper that names the gap this Lab exists to close.
Kal, E., Prosée, R., Winters, M., & Van Der Kamp, J. (2018). Does implicit motor learning lead to greater automatization of motor skills compared to explicit motor learning? A systematic review. PloS One, 13(9), Article e0203591. https://doi.org/10.1371/journal.pone.0203591
Twenty-five controlled trials of implicit versus explicit learning. Leans toward implicit for automaticity, but most comparisons showed no group difference — the honest baseline for this argument.
van Abswoude, F., Mombarg, R., de Groot, W., Spruijtenburg, G. E., & Steenbergen, B. (2021). Implicit motor learning in primary school children: A systematic review. Journal of Sports Sciences, 39(22), 2577-2595. https://doi.org/10.1080/02640414.2021.1947010
In primary school children, implicit and explicit produced equal motor learning outcomes, with a handful of studies favouring explicit. Manipulation checks were performed in only about half.
Nijmeijer, E. M., Brals, F. D., Kempe, M., Elferink-Gemser, M. T., & Benjaminse, A. (2025). How are athletes trained to move? A systematic review exploring the effects of implicit and explicit learning on biomechanics of sport-specific tasks. Journal of Biomechanics, 184, Article 112671. https://doi.org/10.1016/j.jbiomech.2025.112671
Across 25 studies, implicit learning outperformed controls on biomechanical outcomes in sport-specific tasks. The most favourable recent synthesis.
Bergmann, F., Gray, R., Wachsmuth, S., & Höner, O. (2021). Perceptual-motor and perceptual-cognitive skill acquisition in soccer: A systematic review on the influence of practice design and coaching behavior. Frontiers in Psychology, 12, 772201. https://doi.org/10.3389/fpsyg.2021.772201
Soccer. Self-organised approaches beat prescriptive ones for technical and tactical skills — and prescriptive approaches also worked for technical skills. Both halves of that matter.
Clark, M. E., McEwan, K., & Christie, C. J. (2019). The effectiveness of constraints-led training on skill development in interceptive sports: A systematic review. International Journal of Sports Science & Coaching, 14(2), 229-240. https://doi.org/10.1177/1747954118812461
The constraints-led approach in interceptive sports: 77% of studies found a positive effect on skill acquisition, with the authors flagging small samples and a need for better controls and retention tests.
Gray, R. (2020). Comparing the constraints led approach, differential learning and prescriptive instruction for training opposite-field hitting in baseball. Psychology of Sport and Exercise, 51, 101797. https://doi.org/10.1016/j.psychsport.2020.101797
Baseball, six weeks in a virtual environment, comparing constraints-led, differential learning and prescriptive instruction. The constraints-led group came out ahead.
Schöllhorn, W. I., Hegen, P., & Davids, K. (2012). The nonlinear nature of learning - A differential learning approach. The Open Sports Sciences Journal, 5(1), 100-112. https://doi.org/10.2174/1875399X01205010100
Differential learning: deliberately adding movement variability rather than repeating a target technique.
Rivera, D., Robinson, T., & King, A. C. (2024). The effects of differential learning on the standing broad jump. Perceptual and Motor Skills, 131(1), 311-325. https://doi.org/10.1177/00315125231218465
Differential learning improved standing broad jump distance over repetition-based training — a rare direct test in a discrete power task.
Renshaw, I., & Chow, J. Y. (2019). A constraint-led approach to sport and physical education pedagogy. Physical Education and Sport Pedagogy, 24(2), 103-116. https://doi.org/10.1080/17408989.2018.1552676
A constraints-led session design template. The most directly usable item in this list if you want to try the approach at your next session.
Gray, R. (2023). How we learn to move: A revolution in the way we coach & practice sports skills. Perception Action Consulting & Education LLC.
The best plain-language entry point to ecological dynamics for a working coach.
Bernstein, N. (1967). The Co-ordination and Regulation of Movements. Pergamon Press.
‘Repetition without repetition.’ The origin of the idea that solving the movement problem again is more useful than repeating the movement.
Shea, J. B., & Morgan, R. L. (1979). Contextual interference effects on the acquisition, retention, and transfer of a motor skill. Journal of Experimental psychology: Human Learning and memory, 5(2), 179. https://doi.org/10.1037/0278-7393.5.2.179
The contextual interference effect: random practice depresses performance now and improves retention and transfer later. The single most cited finding in this subdomain.
Ammar, A., Trabelsi, K., Boujelbane, M. A., Salem, A., Boukhris, O., Glenn, J. M., Zmijewski, P., Jahrami, H. A., Chtourour, H., & Schöllhorn, W. I. (2024). The effects of contextual interference learning on the acquisition and relatively permanent gains in skilled performance: A critical systematic review with multilevel meta-analysis. Educational Psychology Review, 36(2), 57. https://doi.org/10.1007/s10648-024-09892-z
The most important corrective here. Only 20% of 183 outcomes agreed with the contextual interference effect, and there was little evidence it enhances long-term performance. If you cite contextual interference, cite this too.
Czyż, S. H., Wójcik, A. M., & Solarská, P. (2024). The effect of contextual interference on transfer in motor learning-a systematic review and meta-analysis. Frontiers in Psychology, 15, 1377122. https://doi.org/10.3389/fpsyg.2024.1377122
Random schedules improve retention in the laboratory; in the field the benefit is small, and smaller again in younger athletes. Tells you where the effect lives and where it does not.
Czyż, S. H., & Coker, C. A. (2023). An applied model for using variability in practice. International Journal of Sports Science & Coaching, 18(5), 1692-1701. https://doi.org/10.1177/17479541231159473
An applied model for using variability in practice, organised around difficulty, managing athlete expectations, and representative design.
Raviv, L., Lupyan, G., & Green, S. C. (2022). How variability shapes learning and generalization. Trends in cognitive sciences, 26(6), 462-483. https://doi.org/10.1016/j.tics.2022.03.007
Four distinct kinds of variability — numerosity, heterogeneity, situational diversity, scheduling. Useful because ‘be more variable’ is not one instruction.
Pinder, R. A., Davids, K., Renshaw, I., & Araujo, D. (2011). Representative learning designs and functionality of research and practice in sport. Journal of Sport and Exercise Psychology, 33(1), 146-155. https://doi.org/10.1123/jsep.33.1.146
Representative learning design: practice should sample the information athletes will actually use in competition.
Krause, L., Farrow, D., Buszard, T., Pinder, R., & Reid, M. (2019a). Application of representative learning design for assessment of common practice tasks in tennis. Psychology of Sport and Exercise, 41, 36-45. https://doi.org/10.1016/j.psychsport.2018.11.008
Applies representative learning design to ordinary tennis practice tasks, and shows how far common drills sit from the demands of the game.
Maloney, M. A., Renshaw, I., Greenwood, D., & Farrow, D. (2022). Situational information and the design of representative learning tasks: What impact does a scoreboard have on expert taekwondo fighters' behaviour and affective-cognitive responses? Psychology of Sport and Exercise, 60, Article 102175. https://doi.org/10.1016/j.psychsport.2022.102175
Bringing a scoreboard into taekwondo training changed both affect and fighting behaviour. A cheap, concrete demonstration that context is part of the task.
Otte, F. W., Millar, S. K., & Klatt, S. (2019). Skill training periodization in “specialist” sports coaching—an introduction of the “PoST” framework for skill development. Frontiers in Sports and Active Living, 1, Article 61. https://doi.org/10.3389/fspor.2019.00061
The Periodisation of Skill Training framework — a roadmap for sequencing skill work across a season.
Farrow, D., & Robertson, S. (2017). Development of a skill acquisition periodization framework for high-performance sport. Sports Medicine, 47(6), 1043-1054. https://doi.org/10.1007/s40279-016-0646-2
Skill acquisition periodisation for high-performance sport, built on familiar training principles.
Brady, F. (2008). The contextual interference effect and sport skills. Perceptual and Motor Skills, 106(2), 461-472. https://doi.org/10.2466/pms.106.2.461-472
Reviews contextual interference in sport settings and finds the laboratory effect frequently fails to transfer to applied ones.
Cheong, J. P. G., Lay, B., Grove, J. R., Medic, N., & Razman, R. (2012). Practicing field hockey skills along the contextual interference continuum: A comparison of five practice schedules. Journal of Sports Science & Medicine, 11(2), 304-311.
Field hockey across five practice schedules: no difference in skill acquisition or retention.
1 never · 2 rarely, under 10% of chances · 3 occasionally, around 30% · 4 sometimes, around 50% · 5 frequently, around 70% · 6 usually, around 90% · 7 every time.
Every item asks about the coaching sessions you designed and facilitated over the past two weeks, so the scale measures recent practice rather than intention.
Each subdomain score is the mean of its ten items, which keeps it on the same 1–7 scale as the items themselves. There is no total score, deliberately.
Every item is phrased in the same direction. Nothing here is a trap.
It may mark a strategy you have not explored, or one that does not apply to your context. The point is the shape of the profile, not its height.
Research
Skill Acquisition Strategies Scale for Sport Coaches
A 50-item scale measuring how frequently coaches apply evidence-based motor learning strategies, developed across a sequence of studies with motor learning experts and practising coaches.
Sport Agnostic Map of Skill Acquisition Strategies
An organising map for the motor learning strategies available to a coach, built from the literature review behind the SASS-SC. It is a proposal, not a settled taxonomy, and parts of it will be wrong.
Structuring skill work across a season
A conceptual model for sequencing skill acquisition strategies across training cycles, drawing on existing periodisation frameworks in skill acquisition.
I’m looking to partner with national governing bodies and other organizations that certify in coaching, skill instruction, or physical education — groups with a stake in how their coaches learn. A partnership means shaping the study together and sampling your membership jointly, with your organization involved throughout rather than simply granting access. If that describes you, I’d welcome the conversation: kbissell@smith.edu
SASS-SC studies are conducted in partnership with national governing bodies, and participating organizations invite their own members. Doctoral research on the SASS-SC is conducted through Rocky Mountain University of Health Professions; coach education work and research partnerships are based at Smith College.
Work with the Lab
Help your organization integrate evidence-based motor learning strategies into coaching curricula and certification pathways.
Keynotes, clinics, and interactive workshops for coaching conferences, NGB summits, and professional development events.
Collaborate on skill acquisition research across sports, physical education, rehabilitation, and movement sciences.
Interested in collaboration, the SASS-SC, curriculum consulting, or speaking at your event?
kbissell@smith.edu