Athletes of all levels deserve environments optimized for performance, retention, and transfer.
Evidence-informed tools, frameworks, and research for sport coaches and coach developers.
Explore the strategy map About the SASS-SCAbout the Lab
A gap exists between evidence-informed pedagogical practices aimed at enhancing performance, retention, and transfer, 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 — the Xs and Os. Out of 285 coach development programs reviewed by Lefebvre and colleagues, fewer than 20 addressed pedagogy. Going back through their data and counting by hand, I found three. 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 how a coach coaches impacts athlete outcomes.
The Skill Acquisition Lab exists to close that gap: to make what the motor learning literature supports usable by the people designing and running practices.
Faculty and Director of Pedagogical Support, Exercise and Sport Studies Department, Smith College · PhD candidate, Rocky Mountain University of Health Professions · Formerly Education Manager, USA Archery
I teach motor learning, pedagogy, and coach education at Smith College, where I support the faculty and instructors who deliver our performance courses and our M.S. in Exercise and Sport Science. 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 Skill Acquisition Strategy Scale for Sport Coaches (SASS-SC), a scale for measuring how frequently coaches apply evidence-based motor learning strategies. What I teach and what I research address the same problem from two directions.
SAM-SAS
How the strategies available to a coach relate to one another.
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 48-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. The 48 items sit across five hypothetical subdomains. SASS-SC is currently in the development and validation stage.
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 the outcome was. A higher score does not indicate performance, retention or transfer improved.
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 can use the items to guide evidence-informed curriculum design around how coaching happens, not just what gets coached.
Strategies
Each one says what it is, what the evidence shows, and what it looks like in a session. Where the evidence is thin or conflicting, it says so.
Nothing matches that. These are the strategies my literature review covers — the list grows as the review does.
Three of the strategies below — challenge point, constraints and variability — carry a pedagogy-agnostic tag, because my review names them explicitly as working regardless of which macro-pedagogical approach you take. The others are not ruled out anywhere; they are simply not named that way in the literature I reviewed.
These approaches run from explicit, instruction-heavy coaching to implicit, problem-setting coaching, and neither end is the destination. Which one fits is a judgment based on how much the coach knows about the situation profile and how they read it — how task, individual, and environmental factors are interacting, and how those interactions might affect performance and learning. Explicit pedagogies work on the conscious side of motor learning and implicit ones on the nonconscious side; that is a difference in what they act on, not a ranking or endorsement. Apart from direct instruction sitting at the explicit end, this review does not order them relative to one another.
Prescriptive, instruction-heavy coaching. The coach describes and demonstrates, and the athlete listens and reproduces. Rooted in information processing.
What the evidence says
This is the explicit pole of the continuum, and it is not a straw man. Prescriptive approaches worked for technical skills alongside self-organized ones in a systematic review of soccer (Bergmann et al., 2021), and explicit instruction held up better than analogy under stress (Carnero-Diaz et al., 2025). The caution is time: time spent listening is time away from the perception-action workspace.
A framework of teaching styles running from command style through to self-teaching. It is not a position on the explicit-to-implicit continuum but a description of the same territory, set out as a series of discrete styles rather than as two poles.
What the evidence says
I did not find a body of evidence I could weigh for this review. There is a literature, but it sits mostly in physical education and is largely descriptive — how teachers use the styles and how they perceive them — rather than experimental work on motor learning outcomes in sport coaching. It is listed here as a related framework, not as a strategy with evidence behind it.
This entry is short because my literature review covers this strategy briefly. It will grow as the work does.
A game-centerd approach in which understanding emerges from playing modified games rather than from isolated technical drilling.
What the evidence says
Grouped with the self-organized approaches in the soccer review, where they outperformed prescriptive ones for technical and tactical skills (Bergmann et al., 2021).
Establishing problems for participants to solve, so that movement solutions are discovered rather than prescribed.
What the evidence says
With 66 novice soccer players, nonlinear pedagogy produced more different actions than differential learning, which in turn produced more than linear pedagogy — both are suggested where creative solutions are the goal (Orangi et al., 2021).
Deliberately adding movement variability rather than repeating a target technique — learning through fluctuation instead of correction.
What the evidence says
Both differential learning groups beat traditional training in acquisition and learning in soccer (Schöllhorn, Hegen & Davids, 2012), and it improved standing broad jump distance over repetition-based training (Rivera, Robinson & King, 2024). Not universally superior, and the meta-analytic picture carries small samples, low power and high bias.
Manipulating task, environmental and individual constraints so the athlete explores and self-organizes toward a solution. Grounded in ecological dynamics.
What the evidence says
Across 18 studies in interceptive sports, 77% found a positive impact on skill acquisition, with the authors flagging small samples and a need for better controls and retention tests (Clark, McEwan & Christie, 2025). In baseball, a constraints-led group outperformed both differential learning and prescriptive instruction over six weeks (Gray, 2020).
These items measure the subdomain as a whole. They are not matched one to one with the strategies above, and the factor analysis has not yet confirmed that they group this way.
Directing attention to the effect of a movement — the implement, the target, the outcome — rather than to the body producing it.
What the evidence says
The best-supported finding in this subdomain. External focus beats internal for performance, retention and transfer, with distal cues beating proximal, and age, health and skill level did not moderate it (Chua et al., 2021; Nicklas et al., 2024). Two limits: the confidence intervals are wide enough that the authors decline to generalize to every task, and internal cues appear better for building muscle in resistance training (Schoenfeld et al., 2018).
In practice. Instead of ‘engage your quadriceps,’ something about where the implement goes.
A single image that carries the whole movement, rather than a list of technical instructions.
What the evidence says
Analogies outperformed explicit instruction for motor performance and retention, and the effect was strongest for novices and youth — though explicit instruction held up better under stress. The authors describe analogy as underutilized in physical education and coaching (Carnero-Diaz et al., 2025). Cues built without the athlete’s needs and preferences in mind are less effective (Moran et al., 2023).
In practice. An analogy might effectively inform how to execute a tackle in rugby for someone familiar with pumas, but be meaningless to someone who was not.
Rehearsing a movement mentally, before or between physical attempts.
What the evidence says
A meta-analysis of 36 studies found a significant positive effect, strongest when imagery is combined with physical practice, and moderated by skill complexity and how the imagery is delivered (Lindsay et al., 2023). The caution the authors give is direct: there is very little information on the use of imagery in sport coaching or physical education settings.
Attention training — being present with what is happening rather than with its evaluation.
What the evidence says
Support here is explicitly preliminary. A 2023 systematic review and meta-analysis reached nearly the same conclusion as one a decade earlier: preliminary support for mindfulness-based interventions improving sport performance, and a need for more high-quality studies. Coaches would need to be comfortable and skillful facilitating such strategies, and may consider collaborating with a sport psychologist.
What the coach says after an attempt, and — just as much — how often, how soon, and who decides.
What the evidence says
The largest body of evidence in my review, and the most compromised. Reviews report high risk of bias in 18 of 24 studies and conflicting evidence on frequency, timing and duration (Petancevski et al., 2022). A meta-analysis of 75 studies with 2,228 participants found no clear support for the guidance hypothesis or for reduced feedback frequency improving learning, and described the literature as severely underpowered (McKay et al., 2022). Those concerns do not invalidate augmented feedback; they mean nobody can yet tell you the right schedule.
In practice. Coach-delivered concurrent feedback may send mixed messages if it sits inside a practice environment that is otherwise constraints-led.
Showing the movement — expert model, peer model, or the athlete’s own recorded attempt.
What the evidence says
Observational learning beat practice-only controls, with larger effects on movement dynamics than on movement outcomes, and effects that differ by age: adults improve form more, children improve outcome more. Expert and self-modeling both work, and no clear winner has emerged between them.
In practice. Attempting to learn the pole vault without ever having seen one, and without a demonstration, carries a far higher perceived challenge than the same task after a model.
These items measure the subdomain as a whole. They are not matched one to one with the strategies above, and the factor analysis has not yet confirmed that they group this way.
The idea that there is an optimal level of difficulty for learning, where the athlete experiences some struggle.
What the evidence says
Comfortable high performance in practice is often a sign that little learning is taking place. The framework is contested: increasing task difficulty changed performance but not learning in one study, whose authors argued it may oversimplify — though on a small sample and a star-tracing task (Bootsma et al., 2018). Csikszentmihalyi’s flow model pairs with it: too easy and athletes disengage, too hard and they become anxious.
In practice. Manipulating the challenge point is pedagogically agnostic — you can apply it wherever you sit on the continuum. Read it by listening to how athletes describe the task, watching body language, and monitoring success rate.
Adjusting the task, the environment or the individual so that different movement solutions become available.
What the evidence says
Newell’s three interacting constraints are the vocabulary for almost every difficulty adjustment a coach makes. Task manipulation increases performance and functional variability, and invites affordances that would otherwise not be discovered. Constraints must be manipulated in ways that match the goals and needs of the learner.
In practice. A skier learning moguls: shorter, softer skis first, then a chosen section of the field, then the goal of keeping the helmet at one height — then add a time constraint.
Breaking a complex skill into parts, or keeping it whole and letting the athlete solve all of it at once.
What the evidence says
Not settled by a rule of thumb. A meta-analysis found the decision turns on task complexity and organization (Fontana et al., 2009), and the advantage reverses with age — fifth graders learned juggling better whole, first and third graders better in parts (Chan et al., 2015), a pattern broadly replicated in basketball lay-ups (Moradi et al., 2023). Practicing components out of context may reduce transfer beyond practice.
These items measure the subdomain as a whole. They are not matched one to one with the strategies above, and the factor analysis has not yet confirmed that they group this way.
Giving athletes real choice, and therefore some control over their own learning.
What the evidence says
My review covers this briefly, and I would rather say so than pad it. The evidence is genuinely split: across 32 studies self-controlled groups usually learned better than controls and never worse (Jaitner & Mess, 2019), while a large, well-powered experiment found choice improved neither learning nor perceptions of autonomy, competence or motivation (St. Germain et al., 2023). Worth noting that this was the least-used strategy among the coaches I have measured so far.
This entry is short because my literature review covers this strategy briefly. It will grow as the work does.
Helping athletes believe success is within reach — by recalling past success, creating chances to succeed now, or building confidence about what comes next.
What the evidence says
A meta-analysis of 48 studies supports the effect while flagging that it is likely overestimated because of reporting bias (Bacelar et al., 2024). The sharpest test found an easier criterion of success clearly raised self-efficacy and perceived competence, and raised motivation where practice volume was high, but did not improve learning at all (Parma et al., 2023). Best understood as a way to sustain engagement, not to accelerate skill.
In practice. Moving a target closer to an archer, or providing a larger target, creates broader success criteria.
Setting and clearly communicating what this session is for.
What the evidence says
Covered briefly in my review. Goal-action coupling is described in OPTIMAL theory as ‘a common mechanism for motivational and attentional effects on motor performance and learning’ — when athletes are motivated and externally focused, the coupling strengthens and outcomes improve. Achieving clear, realistic goals also contributes to a sense of competence.
This entry is short because my literature review covers this strategy briefly. It will grow as the work does.
Building time into practice for athletes to consider what they did and why.
What the evidence says
Covered briefly in my review, and mostly by analogy to curriculum design: outcomes should inform activity design, and assessment is only effective when it relates to both. Reflection is reported as positively impacting motor learning and performance, though the coach-development literature on reflective practice suffers from small samples and low internal and external validity.
This entry is short because my literature review covers this strategy briefly. It will grow as the work does.
These items measure the subdomain as a whole. They are not matched one to one with the strategies above, and the factor analysis has not yet confirmed that they group this way.
Whether practice happens all at once or is distributed across intervals.
What the evidence says
Covered briefly. Massed practice has been reported to work better for retention and transfer of simple skills, distributed for complex ones — but in children both improved performance with no significant difference between them.
This entry is short because my literature review covers this strategy briefly. It will grow as the work does.
The sequence skills are practiced in — blocked, serial, or random.
What the evidence says
Blocked practice focuses on one skill for the longest run; serial repeats a predictable sequence; random offers the most variability and challenge. Block designs produce better performance initially, random designs better retention and transfer. Practice order nests inside practice design, but it changes perceived challenge level too — which is why the two overlap rather than nest.
Practicing the same goal in different ways, rather than repeating one movement.
What the evidence says
Bernstein called it repetition without repetition: the learner benefits more from solving the functional problem again than from reproducing the movement. Four distinct kinds have been identified — numerosity, heterogeneity, situational diversity and scheduling — which matters because ‘be more variable’ is not one instruction. Variability does not sit at one end of the explicit-implicit continuum; it can be used across the spectrum.
In practice. In archery: target face size, distance, cue manipulation, equipment, or the number of repetitions before switching.
The interference created by switching between tasks, which depresses performance now and is supposed to improve retention later.
What the evidence says
The best-known finding in this subdomain and the least secure in application. A systematic review and meta-analysis found only 20% of 183 outcomes agreed with the effect, with little evidence it enhances long-term performance (Ammar et al., 2024). Another found random schedules improve retention in the laboratory but yield small benefits in the field, and smaller again in younger athletes (Czyż, Wójcik & Solarská, 2024). If you cite contextual interference to your athletes, cite these too.
Designing practice so it samples the information athletes will actually use in competition.
What the evidence says
Practice that demands decision-making under competition-like conditions shows stronger skill durability and transfer. It is not universally indicated — an archer who already adapts well under time pressure will not grow from more of it.
In practice. Bringing a scoreboard into taekwondo training changed both affect and fighting behavior. Korea built a replica of the Tokyo Olympic stadium, down to the music, announcers, banners and camera positions.
Sequencing skill work across a season rather than treating every session the same.
What the evidence says
Several frameworks exist for this — skill acquisition periodization built on familiar training principles, and a periodization of skill training roadmap. The common thread is that challenge level, practice design and pedagogical approach should all shift as an athlete moves through stages of learning, rather than being chosen once.
These items measure the subdomain as a whole. They are not matched one to one with the strategies above, and the factor analysis has not yet confirmed that they group this way.
I have come to think of the application of skill acquisition strategies the way I think about cooking. A chef generally works in a specific cuisine — the overall flavor of what they are making — and that cuisine provides guidance for the chef around what the flavor outcomes should be. In addition, regardless of where a cuisine sits on the continuum of global flavors, ingredients are largely shared. Salt, acid and onion turn up in almost every kitchen in the world. I see skill acquisition strategies work the same way: most of the strategies are available to a coach regardless of their pedagogical preferences. Like fine chefs, coaches can treat skill acquisition strategies as ingredients, intentionally selecting them to stimulate a desired outcome. The more the chef or coach knows about their audience, the situation profile, and what the food or coaching science says, the more likely the flavors will lead to the desired outcomes. Finally, even if the most evidence-informed strategies are applied, delivery of those strategies likely impacts outcomes. Through the lens of the chef, quality ingredients alone do not guarantee a masterful meal. The way ingredients are combined, timing, temperature, and delivery all impact outcomes.
Two things follow, and they are the reason I am sharing this metaphor at all:
The first is that a chef who uses every spice in the rack has not cooked a better dish. Masterful cooking and coaching are in the selection, proportion, timing, and delivery, not the quantity of inventory. That is exactly why a higher SASS-SC “score” does not mean better coaching, and why I would rather you look at the shape of a profile than its height.
The second is that ingredients are only half of it. Food is digested, and that is where cooking and coaching are most alike: the meal does its work after the table, inside someone you cannot reach.
You cannot tell from the eating whether you were nourished, and you cannot tell from watching a session whether anyone learned. A practice can look superb while it is happening and feed nobody — cut how often you give feedback and practice can look worse while what survives to a retention test improves. What satisfies and what nourishes are different things, which is why athlete preference does not govern the choice: the challenge point requires some productive struggle, and struggle is not what anyone would order. And the same meal does not feed two athletes alike; what they take from a session depends on their experience and where they are in learning the skill. The coach composes the meal. The athlete does the digesting, and that is the part no one else can do — whether what they were fed told them how to move or invited them to find out.
Resources
Every source below appears in the reference list of the dissertation behind the SASS-SC. Where the evidence conflicts, it says so.
Nothing matches that. Every source here comes from the proposal’s own reference list, so a name that is not in it will not appear.
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
A large 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 generalize across all tasks and skill levels. Read alongside Chua to get a sense of the range of findings.
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 favoring 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 to capture, keep, and direct attention. Cues are not one-size-fits-all.
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 use in the 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 maximized, and comfortable high performance in practice is often a sign that little learning is taking place. Anyone facilitating skill acquisition can benefit from applying concepts integral to the Challenge Point Framework.
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 accordingly.
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. Consider what you can do as a coach to facilitate Flow.
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 across pedagogical approaches.
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. What is best for the learner? The decision turns on task complexity and organization, 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. This article argues for integrating all three components, when possible, to maximize performance and learning.
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 OPTIMAL 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. A 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
A test of the impact of easing success criteria. Easing success criteria 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. A strong 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.
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 favoring explicit. Manipulation checks were performed in only about half. In other words, this raises the question of how quality of delivery impacts motor learning outcomes regardless of explicit or implicit approaches.
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.
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-organized approaches beat prescriptive ones for technical and tactical skills — and prescriptive approaches also worked for technical skills.
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 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. An immediately 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.
A great 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 are interested in building contextual interference into practice, read this article as well.
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 positive effect of random schedules has the largest impact.
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, organized around difficulty, managing athlete expectations, and representative design. Offers a highly accessible model for working coaches to digest and apply immediately.
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 if the goal is for the skills practiced to transfer to 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 tennis drills sit from the demands of the game. A recommended read for non-tennis coaches as well.
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 behavior. A 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 Periodization 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 periodization 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 settings.
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.
Each subdomain score is the mean of its own items, which keeps it on the same 1–7 scale as the items themselves. There is no total score, deliberately.
Each item is phrased to capture a coaching action, plus the intent behind that action.
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 48-item scale measuring how frequently coaches apply evidence-based motor learning strategies, developed across a sequence of studies with motor learning experts and practicing coaches.
Sport Agnostic Map of Skill Acquisition Strategies
An organizing 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 change as the research process unfolds.
Structuring skill acquisition across a season
A conceptual model for sequencing skill acquisition strategies across training cycles, drawing on existing periodization frameworks in skill acquisition.
I’m looking to collaborate with national governing bodies and other organizations that certify and train instructors, coaches, and physical educators — groups with a stake in how coaches coach. Collaboration means shaping the study together and sampling your membership jointly, with your organization involved throughout. If that describes you, I welcome the conversation: kbissell@smith.edu
SASS-SC studies are conducted in partnership with national governing bodies and other membership-based organizations where participating organizations invite their own members to participate. Doctoral research on the SASS-SC is conducted through Rocky Mountain University of Health Professions; coach education work and research collaboration are based at Smith College.
Work with the Lab
Help your organization integrate evidence-informed motor learning strategies into coaching curricula and/or 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, coach development, or speaking at your event?
kbissell@smith.edu© 2026 Kyle Forbes Bissell, M.Ed. All rights reserved. Coaching the How™ is a trademark of Kyle Forbes Bissell.
Everything on this site — the writing, original frameworks and diagrams, and the SASS-SC items — is my own work.
Link to it, quote it with attribution, and use it in your own coaching freely. Reproducing the SASS-SC items, the strategy diagrams, or substantial passages in course materials, publications or commercial products requires written permission.
The SASS-SC is under development and has not yet been validated. Please do not administer, translate, adapt or build on it without contacting me first.