Benefit of Gamification for Persistent Learners: Propensity to Replay Problems Moderates Algebra-Game Effectiveness
Saved in:
| Title: | Benefit of Gamification for Persistent Learners: Propensity to Replay Problems Moderates Algebra-Game Effectiveness |
|---|---|
| Language: | English |
| Authors: | Vanacore, Kirk, Sales, Adam, Liu, Allison, Ottmar, Erin |
| Source: | Grantee Submission. 2023. |
| Peer Reviewed: | Y |
| Page Count: | 10 |
| Publication Date: | 2023 |
| Sponsoring Agency: | Institute of Education Sciences (ED) |
| Contract Number: | R305A180401 R305D210036 |
| Document Type: | Speeches/Meeting Papers Reports - Research |
| Education Level: | Secondary Education |
| Descriptors: | Educational Games, Gamification, Algebra, Mathematics Instruction, Knowledge Level, Student Attitudes, Program Effectiveness, Student Behavior, Persistence, Computer Assisted Instruction, Student Characteristics, Repetition, Secondary School Mathematics |
| DOI: | 10.1145/3573051.3593395 |
| Abstract: | Computer-assisted learning platforms (CALPS) increasingly include gamified elements to improve student outcomes by enhancing their engagement with content. Although evidence exists that gamified programs increase engagement and learning outcomes, there is little causal research on what programmatic mechanisms drive the effect between engagement and learning. In the following paper, we explore this relationship through a method of causal moderation known as fully latent principal stratification. Using data from a large-scale randomized control trial assessing gamified and traditional CALP systems' effects on algebraic knowledge, we estimate the impact of using the gamified CALP on students who engage with one of its key gamification elements--replaying a problem after a suboptimal attempt. The gamified CALP asks students to manipulate algebraic expressions from start to goal states and provides feedback based on the efficiency of these manipulations, allowing students to replay the problems when their efficiency can be improved. We find that the effect of gamification is greater for students with a higher propensity to replay problems. This finding suggests that gamification elements that provide students with opportunities to retry problems are driving the game's efficacy and provide evidence for a scalable mechanism of gamification that can improve students' learning. [This paper was published in: "Proceedings of the Tenth ACM Conference on Learning @ Scale (L@S '23), July 20-22, 2023, Copenhagen, Denmark," ACM, 2023, pp.164-173.] |
| Abstractor: | As Provided |
| IES Funded: | Yes |
| Entry Date: | 2023 |
| Accession Number: | ED629730 |
| Database: | ERIC |
| Abstract: | Computer-assisted learning platforms (CALPS) increasingly include gamified elements to improve student outcomes by enhancing their engagement with content. Although evidence exists that gamified programs increase engagement and learning outcomes, there is little causal research on what programmatic mechanisms drive the effect between engagement and learning. In the following paper, we explore this relationship through a method of causal moderation known as fully latent principal stratification. Using data from a large-scale randomized control trial assessing gamified and traditional CALP systems' effects on algebraic knowledge, we estimate the impact of using the gamified CALP on students who engage with one of its key gamification elements--replaying a problem after a suboptimal attempt. The gamified CALP asks students to manipulate algebraic expressions from start to goal states and provides feedback based on the efficiency of these manipulations, allowing students to replay the problems when their efficiency can be improved. We find that the effect of gamification is greater for students with a higher propensity to replay problems. This finding suggests that gamification elements that provide students with opportunities to retry problems are driving the game's efficacy and provide evidence for a scalable mechanism of gamification that can improve students' learning. [This paper was published in: "Proceedings of the Tenth ACM Conference on Learning @ Scale (L@S '23), July 20-22, 2023, Copenhagen, Denmark," ACM, 2023, pp.164-173.] |
|---|---|
| DOI: | 10.1145/3573051.3593395 |
