Episode 72 Distributed Practice in Games-Based Learning

Distributed Practice in Games-Based Learning

Hi and welcome to Experience Points by University XP. On Experience Points we explore different ways we can learn from games. I’m your host Dave Eng from games-based learning by University XP. Find out more at www.universityxp.com

On today’s episode we’ll examine Distributed Practice in Games-Based Learning.

You are probably familiar with “cramming” and studying as much as possible in the time leading up to a test. The opposite of this is “distributed practice.” Distributed practice is where students study in small increments leading up to a test or quiz.

Distributed practice is often recommended by teachers and instructors. But sometimes, students lack the foresight or discipline needed to prepare in small increments in the time leading up to the big test day.

However, games don’t have this issue. Games encourage players to return and play - often repeatedly - over time. So how can educators use distributed practice for teaching, instruction, and games-based learning?

This episode will define distributed practice as a concept of spaced practice with intervals of rest in between. This is compared to massed practice where all of a learner’s activity takes place in one sitting.

Distributed practice takes advantage of the “spacing effect” of separating times of practice, study, and engagement. This helps with students’ retrieval and successful application of learning as distributed practice’s biggest asset.

Details for how distributed practice is structured as well as time intervals between student sessions will be covered. Instructor strategies for implementing distributed practice will be included as well as how to design for distributed practice in games-based learning.

Distributed practice is known by several other names. They include spaced repetition or spaced practice. No matter what you call it, distributed practice requires the student to break up their study and practice into short sessions over a longer period of time.

These rest periods punctuate settings where a student is actively engaged and participating versus times when are doing something else. These rest periods can be spent studying or engaging in other materials or doing something outside of the direct realm of the subject being studied.

Reviews, assessments, or tests for these students normally take place after a number of distributed practice events rather than immediately after a specific session.  While smaller assessments - such as quizzes, challenges, or knowledge checks - may occur at the end of these spaced intervals; longer and more challenging assessments - for example: tests, presentations, projects, or boss battles - take place after a significant amount of time while engaging in distributed practice.

Massed practice on the other hand is the direct opposite of distributed practice. In massed practice a learner engages in fewer studying sessions over a given course. If you’ve ever crammed for a test by doing a lot of studying in one sitting the night before, then you’re already familiar with massed practice.

Massed practice doesn’t take into account the spacing that is included in distributed practice. As such it’s found to be less effective at helping students achieve learning outcomes as well as mastering course content or material.

Despite this, cramming is often the direction that many students pursue leading up to a major assessment like a test or a presentation. The reasons for this are various but often include poor preparation; lack of time management; procrastination; or lack of intrinsic motivation.

You may already be aware of mass practice’s limitations if you’ve relied on it before. You may have remembered or applied information in the short term; but didn’t benefit from it in the long term. Therefore, investing in distributed versus massed practice works better for students in their long term retention.

This success comes from the spacing of these learning sessions out with a break in between them. The use of spacing is the distinguishing factor in helping students with retention of material compared to massed practice.

Students can take advantage of this by studying for an eminent test or exam over the coming days or weeks leading up to it, rather than waiting the night before. Doing so ensures that enough time that has passed between study sessions in order for the spacing effect of distributed practice to apply.

Of course, anyone who has taught students before knows that they don’t always invest in spacing out their practice over days or weeks. Unfortunately, this means less “meaningful” learning for them compared to massed practice - or cramming - which prioritizes “rote” learning.

Investing in meaningful learning through distributed practice is a worthwhile skill to learn. It begins with the review and application of the “spacing effect” and how it influences individuals’ personal development.

The spacing effect is the cognitive phenomenon that is emphasized in distributed practice. The spacing effect takes advantage of the shorter; uninterrupted study sessions which leads to more meaningful - and long term learning - compared to a massed session.

This spacing effect affects college students, adult learners, and young children differently. However, it does have applications to a wide range of different learning paradigms  - such as games-based learning - that can be applied to these individual groups.

These different paradigms emphasize the “chunking” or separation of different elements of study into set periods of time over a longer period. These results lead to better memory recall and application. The spacing effect aids this by providing more contextual variability.

This means that learners must think, reflect, and determine how to best identify and apply information in different contexts when engaging with it over different time frames.

An example of this is when students study multiple different subjects simultaneously. A concept or problem set in a mathematics class may have philosophical applications that require the student to examine and revisit the problem from a different perspective.

Likewise, in games-based learning, players are able to apply the “language” of game mechanics to other games that they may play in the future. Playing a trick-taking game like Spades helps them use and apply the concept in other games that use trick-taking such as The Fox in the Forest. Likewise, using the same game mechanics in different contexts provides the player with insight on how it can be used to their advantage in different game structures.

Thus, with spacing, learners are provided a more effective means of learning and retaining information. Because of this, teachers and instructors can structure their classes to address curriculum and materials at regular and increasing intervals.

Likewise, instructors can also provide agency for students in choosing when and how they return to address these concepts while taking advantage of the spacing effect.

When using the concept of distributed practice we also have to address “retrieval.” Specifically we think about informational retrieval and how students’ recall past information during a new learning session.

What the spacing effect does is force students to engage in a more difficult and challenging retrieval process. This is a process that makes students recall information over longer period of times based on their spacing practices.

This is directly opposed to massed practice where students are required to only retain information in short term memory - a practice which can be counterintuitive to long-term memory creation.

Students’ retrieval of this memory over a longer term is due to their development of factual - semantic -  long term memory rather than shorter term experience - episodic memory.

The reasoning behind this is that the retrieval of information no longer becomes a practice of recalling the circumstances in which that experience was formed. Rather, retrieval becomes a practice more closely aligned with expertise development in a new domain.

Consequently, this also requires learners to reconcile information conceptually with their other learning experiences in different disciplines.

Distributed practice utilizes the spacing effect in order to maximize the retrieval of information for students. This has positive effects in education, academics, and the professional world.

The most successful and proactive students invest in a distributed learning practice in order to achieve their scholastic goals. In addition, students can generalize the success of distributed practice beyond remembering factual information. Benefits also extend to conceptual and procedural information as well.

Given enough experience and practice, learners can actualize and use the benefits of distributed practice to reduce the amount of time spent learning as well as increasing the capacity for recall and action. This directly contrasts massed practice which often suffers due to the shorter term retrieval and application of information.

The main benefit of distributed practice is the need to rest. The rest period creates a boundary between learning sessions. Those boundaries can be filled with other subjects, disciplines, activities, and sleep.  These boundaries are important because they represent a form of delineation between learning activities, retrieval, and application of information.

The key to distributed practice is the spacing effect and ensuring that enough time has passed in order to return to the learning activity. Preferably this is done over a longer period of time and over a repeated basis.

Studying distributed practice and the spacing effect originally centered around information acquisition and its lasting effect in animals. However, studies generalized this effect on human learning – specifically verbal learning.

The greatest effects in humans centered on the accomplishment of discrete tasks that have a high degree of fidelity  - otherwise known as realism -  towards its application.

This is closest to learning a new language where repeated and direct application of the new language in everyday settings has a lasting effect. This is why foreign immersion programs are relatable and applicable opportunities to use and practice a foreign language.

The most meaningful distributed practice structures incorporate large conceptual ideas into smaller and more discrete tasks. This is included in games-based learning where concepts such as supply and demand in economics are closely connected to game mechanics where actual commodities are traded which affects the pricing of goods. Players can see the connection of these smaller mechanics to the larger concept of supply and demand.

Thus, through the core loop of the game, continual action, and repeated exposure, the student learns experientially about the concept put into practice. Distributed practice builds on this by engaging with the student on multiple different occasions spread out over time.

This is where academic scheduling and reinforcement structure takes effect. This is also applies in game play when students repeatedly play the game and use their own agency to enact meaningful decisions within it.

Distributed practice relies on the spacing effect and the positive impact it can have for students when they return to the learning material. This means that regular breaks and a regular return to engaging activities distributed over time is the path to greatest student information retention.

However, the type and length of spacing is at the discretion of the instructor as the length of time may be set by them. Therefore, it’s recommended that spacing be set at longer intervals of rest between activities compared to shorter ones.

The reason behind this is that students will encounter or otherwise engage with other activities, subjects, or concepts between learning activities. These other experiences challenge their recall and application of the learning material every time they return to it.

Time between learning sessions is also in the hands of the students for self-directed activities. These include reading as well as studying as it requires that they manage and determine their own spacing schedule.  This can often be a challenging prospect for students whose time and attention often compete against other subjects, activities, and commitments.

Implementing distributed practice in learning can be a challenging prospect. However, a dedication to motivation and determination helps learners and instructors alike towards achieving this.

Student accommodation and dedication to their own studying, learning, and engagement schedule is paramount.  Instructors in the classroom have great leeway into how students engage with the material, often affecting when students review material.

Often, reviews that happen immediately after the original learning event is much more intense. However, outside of the classroom, it is ultimately up to the student to choose how and when they revisit the material and study.

A common format for re-engaging with learning material for students and instructors is practice testing. Specifically, re-developing the scenarios in which the information will be used and applied in order to improve performance.

Likewise, instructors can build on this model through the application of review exercises both before and after learning sessions. Such activities provide students with opportunities to re-engage with material at regular, spaced, and formal intervals.

Distributed practice for teaching and learning is already well defined. But how about distributed practice in gaming? Some of the most engaging and addicting games already use distributed practice by engaging and enticing players to come back to them. Because of this, games already institute and use distributed practice in order for players to succeed, achieve, and develop mastery of the game.

Furthermore, games-based learning programs can also be structured to break up learning programs into smaller sections - thus reducing the amount of time spent on any one area. This provides opportunities for students to take a break from the content in order to review, debrief, and reflect. Such structure takes advantage of the spacing effect of distributed practice.

Instructors can use the spacing between games-based learning  in order to use distributed practice to its full effect. Some of the most popular games can even require that players take breaks from playing order to mitigate the negative aspects of massed practice.

Educators can also use different styles, themes, and mechanics of games all surrounding a particular learning outcome for students. Such a structure forces the learner to use and apply information, concepts, and procedures in different ways utilizing different perspectives in order to more thoroughly engage with the learning experience.

Games-based learning can be used in conjunction with traditional learning models in its application of distributed practice, interleaved practice, and active learning. Doing so ensures that multiple modalities and approaches accommodate different learner perspectives and needs in the process.

When distributed practice is combined and applied with games-based learning, the positive effects for learners can be significant. Especially when compared against traditional learning techniques and massed practice.

The following sections will outline how distributed practice can be used in games-based learning through five different areas: motivation, investment, new content, meaningful choices & emergent challenges, and returning players.

Understanding player motivation is paramount for using games-based learning for engaging learners in the most earnest way possible. Player motivation is what triggers learners to play and keep playing throughout the game.

The best motivation to take advantage of here is intrinsic motivation where players continue to play and engage based on their internal desires to excel. This is compared to extrinsic motivation where outside factors - such as money, fame, or prestige -  motivate players to play.

Extrinsic motivation may be a good way to engage players at the beginning of the game. However, continual involvement - and distributed practice - depends on players’ development of emergent play.

That occurs thorough systemic depth of the game. This usually happens when players discover new and previously unrealized strategies, tactics, or philosophies to implement in the game that they can use to their advantage.

Players are most likely to return to the game and continue playing once they are intrinsically invested in it. This is especially relevant if players’ first stages include some sort of early progression - for example: leveling up - or personalization - like the ability to create one’s avatar - in the game. Both effects positively influence the player experience.

While this type of investment is preferred; other more mechanical forms of investment can be created in serious games. These include daily bonuses for engaging or logging into the game regularly to play. Such engagement focuses on extrinsic rewards.

However, this mechanic can be used in order to re-engage the player with the game in a distributed way in order to re-expose them to the content within the game.

Investment at its’ surface level is a valuable form of engagement. Invested players are more likely to keep playing and returning to a game. This is true whether a game was created for entertainment or educational value.

Introduction of new content into a games-based learning application can be useful - particularly when structuring your learning material and scaffolding players to use and apply information in new contexts.

This can be seen in current digital games where new player quests are introduced at regular intervals as well as “streaks” for routinely returning to the game. Such regular and timely returns - for instance every 24 hours - gives players “boosts” in terms of in-game abilities such as experience and rewards.

Adding new content can be difficult in games when the player base is diverse. This diversity can be represented in a population divided between original players and new players. Original players will want to see new content and new opportunities to keep the game fresh – whereas newer players may still require strict scaffolding for creating their own player experience.

This can occur when creating training programs where returning employees and new employees are mixed together. The result of which are different needs and applications for both groups of learners.

This can be overcome by creating game structures where new players are incentivized to review basic content to develop competency in the game. This is compared to experienced players who are charged with finding new ways to use and apply old competencies or help new players get acclimated to play.

Providing players with meaningful choices creates a space for them to deepen their connection and investment in the game. As such, these choices should provide players with feedback and reinforcement based on their application of concepts.

Likewise, designers and educators should create a structure where the game provides easier “on-boarding” challenges for players to learn the game while gradually increasing the difficulty as they continue to play and engage over multiple sessions.

Returning players, or more seasoned and experienced learners, represent a big challenge for games-based learning and education as a whole. That’s because these individuals bring to the classroom personalized knowledge that may upset the balance with new players.

This could come in the form of highly experienced players whose play in the game is beyond other players. Likewise these could also be from returning players who have not engaged in a while and would need to re-learn the game - and content - all over again. Because of this, the experience could be completely alien and foreign to them.

However, it’s still up to instructors and designers to create learning environments and serious games that cater to and include these returning players, players with preconceived notions, and new players alike. Doing so ensures that your game applies to the widest possible audience while also helping individuals achieve their learning outcomes.

This episode defined distributed practice for learning. It compared distributed practice to massed practice and the use of the spacing effect for greatest learning and knowledge retention. Specific references to retrieval for retention were addressed as well as the benefits of using distributed practice in an educational environment.

Structure is important for distributed practice: especially as it relates to time between learning sessions. Tips for implementing distributed practice for both educators and students were covered as well as how gaming addresses distributed practice.

Using distributed practice in games-based learning was covered from five perspectives.

Those perspectives included motivation, investment, new content, meaningful choices & emergent challenges, and returning players.

I hope you found this episode useful. If you’d like to learn more, then a great place to start is with my free course on gamification. You can sign up for it at www.universityxp.com/gamification You can also get a full transcript of this episode including links to references in the description or show notes. Thanks for joining me!

Again, I’m your host Dave Eng from games-based learning by University XP. On Experience Points we explore different ways we can learn from games. If you liked this episode please consider commenting, sharing, and subscribing.

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References

Allrich, R. (n.d.). Distributed practice. Retrieved May 01, 2021, from https://web.ics.purdue.edu/~rallrich/learn/dist.html#

Bast, C. (2019, October 18). Retention training: The spacing effect. Retrieved May 01, 2021, from https://www.anewspring.com/retention-training-the-spacing-effect/

Benjamin, A., & Tullis, J. (2010, November). What makes distributed practice effective? Retrieved May 01, 2021, from https://www.ncbi.nlm.nih.gov/pmc/episodes/PMC2930147/

ClassK12 - math practice for any K-12 classroom or home user. (n.d.). Retrieved May 01, 2021, from https://www.classk12.com/distributed-practice

Distributed practice. (n.d.). Retrieved May 01, 2021, from https://www.alleydog.com/glossary/definition.php?term=Distributed%2BPractice

Distributed Practice. APA dictionary of psychology. (2020). Retrieved May 01, 2021, from https://dictionary.apa.org/distributed-practice

Eng, D. (2019, August 06). Meaningful Choices. Retrieved May 01, 2021, from   https://www.universityxp.com/blog/2019/8/6/meaningful-choices

Eng, D. (2019, December 03). Core Loops. Retrieved May 01, 2021, from  https://www.universityxp.com/blog/2019/12/3/core-loops

Eng, D. (2019, June 04). Formal Game Structures. Retrieved May 01, 2021, from https://www.universityxp.com/blog/2019/6/04/formal-game-structures

Eng, D. (2019, May 07). Serious Games. Retrieved May 01, 2021, from  https://www.universityxp.com/blog/2019/5/7/what-are-serious-games

Eng, D. (2019, October 29). Gaming with Motivation. Retrieved May 01, 2021, from  https://www.universityxp.com/blog/2019/10/29/gaming-with-motivation

Eng, D. (2019, September 10). The Player Experience. Retrieved May 01, 2021, from  https://www.universityxp.com/blog/2019/9/10/the-player-experience

Eng, D. (2020, August 20). What is Player Agency? Retrieved May 01, 2021, from http://www.universityxp.com/blog/2020/8/20/what-is-player-agency

Eng, D. (2020, February 06). Game Mechanics. Retrieved May 01, 2021, from  https://www.universityxp.com/blog/2020/2/6/game-mechanics

Eng, D. (2020, February 13). Engagement Curves. Retrieved May 01, 2021, from  https://www.universityxp.com/blog/2020/2/13/engagement-curves

Eng, D. (2020, March 26). What is Games-Based Learning? Retrieved May 01, 2021, from https://www.universityxp.com/blog/2020/3/26/what-is-games-based-learning

Eng, D. (2020, September 10). What is Intrinsic Motivation? Retrieved May 01, 2021, from, from https://www.universityxp.com/blog/2020/9/10/what-is-intrinsic-motivation

Eng, D. (2021, February 9). What is Self-Determination Theory? Retrieved May 01, 2021, from  https://www.universityxp.com/blog/2021/2/9/what-is-self-determination-theory

Eng, D. (2021, January 12). What is a knowledge check?. Retrieved May 01, 2021, from  https://www.universityxp.com/blog/2021/1/12/what-is-a-knowledge-check

Feldbacher, C. (2019, December 1). 10 simple tips that will boost your PLAYER Retention (2021 Update). Retrieved May 01, 2021, from https://blog.felgo.com/mobile-game-development/10-simple-tips-that-will-boost-your-player-retention

Francisco, A. (2019, May 08). Ask the cognitive scientist: Distributed practice. Retrieved May 01, 2021, from https://digitalpromise.org/2019/05/08/ask-the-cognitive-scientist-distributed-practice

Game producers and their battle for retention. (n.d.). Retrieved May 01, 2021, from https://www.gamesparks.com/blog/game-producers-battle-for-retention/

Gerbier, E., & Toppino, T. (2015, February 13). The effect of distributed practice: Neuroscience, cognition, and education. Retrieved May 01, 2021, from https://www.sciencedirect.com/science/episode/abs/pii/S2211949315000022

Hansen, P. (2017, July 11). Bridges & Meaningful Distributive Practice. Retrieved May 01, 2021, from https://www.mathlearningcenter.org/new/blog/bridges-meaningful-distributive-practice

Jamshidi Farsani, H., Tamayo‐Serrano, P., Garbaya, S., & Lim, T. (2021). A three‐step model for the gamification of training and automaticity acquisition. Journal of Computer Assisted Learning. Retrieved May 01, 2021, from https://onlinelibrary.wiley.com/doi/full/10.1111/jcal.12539

Jost, N. S., Jossen, S. L., Rothen, N., & Martarelli, C. S. (2021, January 05). The advantage of distributed practice in a blended learning setting. Retrieved May 01, 2021, from https://link.springer.com/episode/10.1007/s10639-020-10424-9

Kennedy, L. (2019, May 26). 7 effective ways to use Distributed practice at your school. Retrieved May 01, 2021, from https://www.prodigygame.com/main-en/blog/distributed-practice/

Killian, S. (2019, August 9).Distributed Practice & Massed Practice: What Works Best?. Retrieved May 01, 2021, from https://www.evidencebasedteaching.org.au/distributed-practice-massed-practice/

Konijn, E. A., & Welbers, K. (2019, February 27). Gamification as a tool for engaging student Learning: A field experiment with a gamified app - Kasper Welbers, elly A Konijn, Christian Burgers, Anna bij de Vaate, Allison Eden, Britta C BRUGMAN, 2019. Retrieved May 01, 2021, from https://journals.sagepub.com/doi/full/10.1177/2042753018818342

Koster, R. (2019, January 31). What drives retention. Retrieved May 01, 2021, from https://www.gamasutra.com/blogs/RaphKoster/20190131/335683/What_Drives_Retention.php

Massed Practice. APA dictionary of psychology. (2020). Retrieved May 01, 2021, from https://dictionary.apa.org/massed-practice

Metalis, S. (1985, October 1). Effects of MASSED versus Distributed practice on acquisition of video game skill - Spero A. METALIS, 1985. Retrieved May 01, 2021, from https://journals.sagepub.com/doi/10.2466/pms.1985.61.2.457

Motivate player for better engagement and retention. (2019, September 11). Retrieved May 01, 2021, from https://thinkgamedesign.com/player-retention-engagement/

Spacing effect. (2021, January 25). Retrieved May 01, 2021, from https://thedecisionlab.com/biases/spacing-effect/

Spacing Effect. APA dictionary of psychology. (2020). Retrieved May 01, 2021, from https://dictionary.apa.org/spacing-effect

Stout, M. (n.d.). A boss is a test. Retrieved May 01, 2021, from https://www.gamasutra.com/view/feature/134503/boss_battle_design_and_structure.php

Syndeon Software, I. (n.d.). The spacing effect. Retrieved May 01, 2021, from http://www.flashcardlearner.com/episodes/the-spacing-effect/

Thalheimer, W. (2017, November 05). Five reasons Learners experience the spacing effect " work-learning Research. Retrieved May 01, 2021, from https://www.worklearning.com/2017/01/07/five-reasons-learners-experience-the-spacing-effect/

The spacing effect: How to improve learning and maximize retention. (2021, February 12). Retrieved May 01, 2021, from https://fs.blog/2018/12/spacing-effect/

User, G. (2020, December 21). How does game-based training work? Retrieved May 01, 2021, from http://blog.lemonadelxp.com/blog/how-does-game-based-training-work

VanHoof, T., Sumerack, M., & Madan, C. R. (2021, Winter). Science of learning Strategy Series: Episode 1, distributed ... : Journal of continuing education in the health professions. Retrieved May 01, 2021, from https://journals.lww.com/jcehp/Abstract/2021/04110/Science_of_Learning_Strategy_Series__Episode_1,.11.aspx

Vlach, H. A., & Sandhofer, C. M. (2012). Distributing learning over time: The spacing effect in children’s acquisition and generalization of science concepts. Child development, 83(4), 1137-1144. Retrieved May 01, 2021, from https://www.ncbi.nlm.nih.gov/pmc/episodes/PMC3399982/

Vlach, H., & Sandhofer, C. (2018, October 16). Distributing learning over time: The spacing effect in children's acquisition and generalization of science concepts. Retrieved May 01, 2021, from https://www.ncbi.nlm.nih.gov/pmc/episodes/PMC3399982/