Powering Up Student Performance in Learning

• Feedback in Learning: Video game design leverages immediate feedback to teach players without explicit instructions, demonstrating the importance of feedback in skill development.
• Mathematical Skill Enhancement: Immediate feedback is crucial in educational apps for mathematics, with research showing that it improves student outcomes, particularly for those struggling with the subject, and supports long-term gains in math achievement.
• Optimizing Feedback Efficiency: The effectiveness of feedback depends on its content and timing. Elaborated feedback, offering detailed insights into why an answer is right or wrong, coupled with timely delivery, significantly enhances student self-regulation and overall math proficiency.

What Video Games Can Teach Us About Learning

Shigeru Miyamoto is the creator of the original Super Mario Bros. and is a videogame legend. We should, of course, expect that we can learn a lot about gaming design from him. This transcript from a biopic of Miyamoto highlights how the use of a series of subtle design choices made it possible to teach novice users to become expert Super Mario gamers simply by playing the first few frames of the game. Because we are focusing this article on the practice of immediate feedback, we have added the callout: [immediate feedback] throughout the transcript so you won’t miss the different ways Miyamoto employed various feedback strategies to support user skill development.

A lot of Miyamoto’s genius can be seen in the first level of Super Mario Bros.—probably the most iconic level in video game history. It’s designed to naturally teach you the game mechanics while you play [immediate feedback]. If you look at a breakdown, there’s a lot of really subtle design work going on here. Though Mario is usually at the center of the screen, in this first scene, he starts at the far left. All the empty space to the right of him gives you a sense of where to go [immediate feedback]. This [goomba] character’s look and movement suggest it’s harmful [immediate feedback]. But don’t worry. If you run into it, you’ll just start the game over without much of a penalty [immediate feedback]. Next, you see gold blocks with question marks. These are made to look intriguing—and once you hit one, you’re rewarded [immediate feedback].

That then encourages you to hit the second block, which releases a mushroom [immediate feedback]. Even if you’re now scared of mushrooms, the positioning of the first obstacle makes it just about guaranteed that you're gonna run into this thing. When you do, Mario gets bigger and stronger [immediate feedback]. And just like that, you’ve learned all the basic rules in the game without having to read a single word [1].

If the transcript does not inspire you, check out the video link at the end of this article [1]. There is so much to learn about supporting student development through good game design!

Supporting Learning with Immediate Feedback

As we analyzed the feedback we received from v#1rious focus groups, watched how users interacted with other math apps and considered best practices in game design, we knew we needed to include immediate feedback mechanisms into our app if we were serious about supporting student development.

From External Influence to Educational Improvement

We recognize that digital learning apps, like ours, along with the features they include, such as immediate feedback mechanisms that we have designed to support students through their learning journeys, have been criticized for relying on behaviorist approaches that coerce students toward the correct answer without students actively engaging in the learning process [2].

However, it has been known since at least the middle of the 20th century that feedback mechanisms—even those employing what might be conceived of as behaviorist practices such as awarding tokens for correct responses—improve student outcomes, particularly for students experiencing difficulty with the subject matter [3]. Additionally, modern versions of such systems that utilize digital mechanisms for immediate feedback throughout the entire learning process have been shown to support both short- and long-term improvements in math achievement [4, 5].

The Importance of the Types and Timing of Feedback

As part of an integrated intervention system, immediate feedback supports each of the five strands of mathematics proficiency: conceptual understanding, procedural knowledge, strategic competence, adaptive reasoning, and productive disposition [6].

Within this framework, interventions should aim to support students’ abilities to develop mastery at each of these levels with increasing independence, leading to self-regulated learning.

In a study of 3rd graders experiencing mathematical difficulties, self-regulation components were shown to support students’ abilities to self-monitor, self-correct, and persevere through the lessons, resulting in statistically significant improvements in performance [7]. Similarly, the introduction of self-regulation strategies, including metacognitive reasoning, was shown to have long-lasting positive impacts on math performance for low-achieving 6th graders [8].

In a comprehensive study on the interplay between feedback and self-regulated learning, the feedback strategies of mathematics teachers from a high-achieving and low-achieving school were compared. The study showed not only that students’ self-regulated learning was higher in the high-achieving school, but that certain feedback strategies correlated with student self-regulation. Feedback that allowed students to feel accomplished in their attempts while also enabling them to assess their level of relative understanding was shown to support students’ self-regulation, which ultimately supported the students’ overall mathematical achievement [9].

Indeed, feedback strategies matter. In a meta-analysis of 77 studies on feedback in digital learning, feedback strategies were recognized as falling into four categories: knowledge of results, knowledge of correct response, elaborated feedback, and answer-until-correct [10]. In the meta-analysis, elaborated feedback—feedback that provides an explanation of why an answer is correct or incorrect and provides hints for further progression and development—was shown to be the most effective support for both the lower-order and higher-order strands of proficiency. While knowledge of results, knowledge of correct response, and answer until correct were also found to be effective forms of feedback, it was the additional metacognitive support provided in elaborated feedback that resulted in its large effect sizes (up to .99!) [10].

However, it is not just the type of feedback, but the timing of it that predicts the success of the feedback strategy.

In a study of 288 8th grader math students, the immediacy of feedback was shown to be the most significant predictor of student outcomes [11]. Additionally, in gamified environments, immediate feedback given throughout the entire learning process has been shown to increase engagement and motivation, decrease frustration and anxiety, and improve student outcomes in both the short- and long-term [4, 5, 12].

Powering Up Student Achievement with Feedback

As with all our design choices, our approach to immediate feedback fits into our larger design framework. In this case, we utilize an intentional conceptual and curricular progression coupled with schematic scaffolds and other motivation-focused gamification strategies to build student confidence toward mastery through increasingly complex cognitive challenges.

Within this system, we leverage immediate feedback to support students through these challenges by informing them of what they are getting right and wrong and providing hints and strategies for improvement. The purpose of this approach to immediate feedback is to help students develop their own metacognitive reasoning so they can solve new problems with increasing autonomy.

Because of its effectiveness in developing self-regulated learners capable of mastering all five strands of mathematical reasoning, we consider immediate feedback to be one our applications awesome power-ups 🍄!

References

[1] (https://www.youtube.com/watch?v=K-NBcP0YUQI&feature=youtu.be&start=149&end=228)

[2] Wilson, C., & Scott, B. (2017). Adaptive systems in education: A review and conceptual unification. The International Journal of Information and Learning Technology, 34(1), 2–19. https://doi.org/10.1108/IJILT-09-2016-0040

[3] Wolf M. M., Giles D. K., Hall R. V. (1968). Experiments with token reinforcement in a remedial classroom. Behavior Research and Therapy, 6, 51–64. https://doi.org/10.1016/0005-7967(68)90042-9

[4] Feng, M., Heffernan, N., Collins, K., Heffernan, C., & Murphy, R. F. (2023). Implementing and Evaluating ASSISTments Online Math Homework Support At large Scale over Two Years: Findings and Lessons Learned (pp. 28-40). In Cham: Springer Nature Switzerland.

[5] Feng, M., Huang, C., & Collins, K. (2023). Technology-based support shows promising long-term impact on math learning.

[6] Pulles, S. M., & Burns, M. K. (2022). Alignment of K‐8 mathematics interventions with strands of mathematical proficiency in meta‐analytic research. Psychology in the Schools, 59(6), 1192-1208. https://doi.org/10.1002/pits.22676

[7] Wang, A. Y., Fuchs, L. S., Fuchs, D., Gilbert, J. K., Krowka, S., & Abramson, R. (2019). Embedding self-regulation instruction within fractions intervention for third graders with mathematics difficulties. Journal of learning disabilities, 52(4), 337-348. https://doi.org/10.1177/0022219419851750

[8] Trias Seferian, D., Mels Auman, C., & Huertas Martínez, J. A. (2021). Teaching to Self-Regulate in Mathematics: A Quasi-Experimental Study with Low-Achieving Elementary School Students. Revista electrónica de investigación educativa, 23. https://doi.org/10.24320/redie.2021.23.e02.2945

[9] Guo, W., Lau, K. L., & Wei, J. (2019). Teacher feedback and students’ self-regulated learning in mathematics: A comparison between a high-achieving and a low-achieving secondary schools. Studies in Educational Evaluation, 63, 48-58. https://doi.org/10.1016/j.stueduc.2019.07.001

[10] Mertens, U., Finn, B., & Lindner, M. A. (2022). Effects of computer-based feedback on lower- and higher-order learning outcomes: A network meta-analysis. Journal of Educational Psychology, 114(8), 1743–1772. https://doi.org/10.1037/edu0000764

[11] Yaşar, C., & Akbaş, U. (2019). The effect of feedback timing on mathematics achievement. Elementary Education Online,18(4). https://doi:10.17051/ilkonline.2019.630657

[12] Li, X., Xia, Q., Chu, S. K. W., & Yang Y. (2022). Using gamification to facilitate students’ self-regulation in e-learning: A case study on students’ L2 English learning. Sustainability, 14 (12), 7008. https://doi.org/10.3390/su14127008