Many EdTech platforms are built not primarily to support learning, but to maximise time-on-task, return visits and engagement metrics. This article presents the research evidence on how these design choices – including reward systems, leaderboards, streaks and manipulative design features – affect children’s motivation, autonomy and wellbeing. The evidence is drawn from the EdTech Accountability Framework compiled by Will Ellis / Reclaim Childhood.
Evidence Ratings
● Strong
● Moderate
● Weak
● None
| Rating | What it means |
| Strong | Peer-reviewed findings with sufficient scale and replication to inform policy, including null results. |
| Moderate | Independent but limited in scale or context. |
| Weak | Some independent work but too small or methodologically limited. |
| None | Vendor data only, or no trial found. |
Key Terms
| Term | Definition |
| The Instrument Test | A tool does nothing until the child acts on it (e.g. a word processor remains empty until the child types). An agent responds, adapts or produces output on the child’s behalf. The instrument test asks which is directing whom: if the child directs the tool, it may belong in the classroom; if the tool directs the child, it does not. |
| Architectural Grounds | A platform can be restricted based on its design, regardless of trial outcomes. Where evidence also shows harm, both grounds apply. |
| Engagement is Not Learning | Clicking, responding and staying on task is behavioural engagement. Struggling with a concept, making connections and building knowledge is cognitive engagement. Platforms built to maximise the first often undermine the second. A child completing 200 Times Tables Rock Stars questions in a session may be behaviourally engaged throughout and cognitively engaged for almost none of it. |
Table 1b: Evidence Against Engagement-Optimised Design
| Key Finding |
Evidence |
Source |
| Meta-analysis of 128 experiments. Tangible, expected rewards substantially undermine intrinsic motivation. Effects were stronger for children than for adults. |
Strong |
Deci, Koestner and Ryan (1999) |
| Controlling reward systems undermine children’s basic psychological needs for autonomy, competence and relatedness. The findings held across different countries and age groups. |
Strong |
Ryan and Deci (2020) |
| Longitudinal study over 16 weeks. Students in the gamified course with leaderboards and badges showed less intrinsic motivation, less satisfaction and lower final exam scores over time than those in the non-gamified course. The picture here is more mixed than the section heading implies. Some students respond positively to competitive ranking. The concern is not that leaderboards harm every child but that platforms deploy them as a default retention mechanism with no ability for teachers to disable them. |
Strong |
Hanus and Fox (2015) |
| Meta-analysis finding small positive effects of gamification on cognitive outcomes but noting motivational effects are less stable. Competition combined with collaboration was more effective than competition alone. |
Moderate |
Sailer and Homner (2019) |
| Systematic review of 40 studies. Gamification shows positive influence on motivation in the short term, followed by decline with continued exposure. Social comparison and competition are key drivers of demotivation in lower-performing students. |
Moderate |
Ratinho and Martins (2023) |
| Cross-sectional study of apps used by 160 children aged 3 to 5. 95% had at least one manipulative design feature in their most-used apps. Features included parasocial relationship pressure, fabricated time pressure, navigation constraints blocking exit, and lures including virtual rewards and leaderboards. Children from lower socioeconomic households were disproportionately exposed. |
Strong |
Radesky et al. (2022) |
| Study of 2,483 early adolescents. Engagement with Snapchat streaks was associated with higher problematic smartphone use, greater fear of missing out and reduced self-control. Longer streaks and more streak partners made compulsive checking patterns worse. Girls showed higher engagement and longer streaks. Direct evidence that streak mechanics produce compulsive use patterns in adolescents. |
Moderate |
van Essen et al. (2023) |
| Content analysis of children’s digital applications. 85 per cent contained deceptive design patterns including app characters shaming children for stopping play, fabricated time pressure, navigation constraints preventing exit, and virtual reward systems. The authors state these features serve commercial goals and prolonging engagement, rather than the developmental interests of children. |
Strong |
O’Donnell et al. (2026) |
| Randomised experiment with 73 children aged 3 to 5. Children using apps with high persuasive design features, including character pressure, instant rewards and visual manipulation, took significantly longer to stop using the app and were less able to disengage independently than children using low-persuasive-design apps. These features are designed to prolong engagement beyond the child’s own intention to stop. |
Strong |
Mallawaarachchi et al. (2025) |
| Survey of 740 students using structural equation modelling. Perceived persuasiveness of EdTech platform design undermines intrinsic motivation through cognitive overload and reduced perceived autonomy. Platforms that nudge users through personalisation and frequent prompts reduce learners’ sense of control. Participants were adults. Whether effects are stronger in younger learners has not been tested. |
Moderate |
Balaskas et al. (2025) |
⚠ Prohibited Platforms in This Category
Times Tables Rock Stars (currently the most widely used in UK primaries) | Doodle Maths / Doodle Learning | Reading Eggs / Reading Eggspress | Duolingo for Schools | EdShed / Spelling Shed | ClassDojo | NumBots | Sumdog | MyOn | TeeRead | Sparx Reader | Reading Plus | Education Perfect
Source: Will Ellis / Reclaim Childhood – reclaimchildhoodmedia.substack.com