Riiid vs. Knewton Alta: A Head-to-Head Comparison for Boosting Student Outcomes
Purpose of Comparison: Both Riiid and Knewton Alta leverage AI to improve student learning, but they approach the challenge from different angles. Riiid focuses on predicting outcomes and pinpointing areas for focused improvement, while Knewton Alta emphasizes adaptive learning paths to ensure mastery. This comparison aims to determine which solution delivers more substantial results, and for what types of educational institutions and use cases.
Product Descriptions:
Riiid: Riiid offers an AI-powered personalized learning platform, initially known for its success in test preparation (particularly in Korea). Their core offering now extends to higher education, focusing on predicting student performance on final exams and then recommending targeted practice. They analyze a student’s learning patterns to identify knowledge gaps and prescribe specific exercises designed to maximize improvement. Riiid’s strength lies in its ability to forecast results and then efficiently guide students towards those goals.
Knewton Alta: Knewton Alta is an adaptive learning platform specifically designed for higher education. It’s integrated directly into existing Learning Management Systems (LMS) and course materials, providing a seamless experience for both instructors and students. Alta uses AI to continuously assess student understanding and adjust the difficulty and content presented. It doesn’t just offer practice problems; it dynamically alters the coursework itself to ensure students achieve mastery before moving on.
Comparison Framework: 10 Key Criteria
1. Prediction Accuracy
Riiid’s core value proposition is prediction. They claim a high degree of accuracy in forecasting final exam scores, enabling proactive intervention. While specific accuracy rates aren’t always publicly available (and likely vary by subject and dataset), their marketing emphasizes statistically significant improvements in predicted versus actual performance. They lean heavily on data from large-scale test prep programs to refine their algorithms.
Knewton Alta doesn’t prioritize predicting a final grade in the same way. Its AI focuses on real-time assessment of mastery, not future forecasting. While a student’s performance in Alta certainly indicates likely success in the course, Knewton doesn’t offer a specific “you will get X%” prediction. Their data focuses on demonstrating mastery levels achieved within the Alta platform.
Verdict: Riiid wins for prediction accuracy, as it’s central to their functionality.
2. Adaptability of Content
Knewton Alta shines here. Its adaptive engine dynamically adjusts the content presented to each student, offering remediation when needed and accelerating those who demonstrate proficiency. This happens within the course materials, meaning students aren’t pulled into separate practice modules; the learning path itself is personalized. It’s embedded directly into courseware.
Riiid primarily provides targeted practice outside the core course content. While personalized, it’s more about supplementing the existing curriculum with focused exercises based on predicted weaknesses. The core course structure remains unchanged, and students are directed to specific problems rather than having the entire learning path adjusted.
Verdict: Knewton Alta wins for adaptability of content – it’s a fundamental aspect of its design.
3. Integration with LMS
Knewton Alta is built for seamless integration with popular Learning Management Systems like Canvas, Blackboard, and Moodle. This is a major selling point, allowing instructors to easily incorporate Alta into their existing workflows without significant disruption. It’s designed to be a drop-in replacement for traditional homework systems.
Riiid, while offering integrations, historically has been more focused on its standalone platform. Integration is available, but reports suggest it may require more technical effort and customization compared to Alta’s plug-and-play approach. It’s more likely to require API connections and potentially custom development.
Verdict: Knewton Alta wins for LMS integration due to its ease of implementation.
4. Data Insights for Instructors
Both platforms provide data analytics to instructors, but they differ in focus. Riiid offers insights into class-wide performance trends and identifies students at risk of falling behind based on their prediction model. This allows instructors to intervene proactively with those needing extra support.
Knewton Alta provides granular data on student mastery levels for each learning objective. Instructors can see exactly where students are struggling, allowing them to adjust their teaching strategies and provide targeted assistance. This data is more focused on what students aren’t understanding, rather than predicting who will fail.
Verdict: Knewton Alta wins for granular data insights, providing more actionable information about specific learning gaps.
5. Subject Coverage
Knewton Alta currently focuses primarily on introductory college courses in STEM fields – math, chemistry, economics, and statistics. While expanding, its coverage remains relatively narrow.
Riiid has a broader scope, initially built on extensive test prep data. They’re expanding into a wider range of subjects within higher education, and their foundational technology is more easily adaptable to different content areas. They’ve demonstrated success in areas beyond STEM.
Verdict: Riiid wins for broader subject coverage, though Alta excels within its focus areas.
6. Scalability
Both platforms are cloud-based and designed to scale to large student populations. However, Knewton Alta, having been integrated into many institutions, has a proven track record of handling significant usage volume.
Riiid is also scalable, but its relative newcomer status in the US higher education market means it has less demonstrated experience with massive deployments. It’s scaling quickly, but the sheer volume Knewton has processed gives it an edge.
Verdict: Knewton Alta wins for proven scalability based on existing deployments.
7. Cost & Licensing
Pricing models for both platforms are complex and vary based on institution size, course enrollment, and features. Generally, Knewton Alta operates on a per-student, per-course licensing model.
Riiid’s pricing is also customized, and may include options for subscription-based access or per-student fees. Anecdotally, Riiid might offer more flexibility in pricing structures, particularly for pilot programs. Verify current pricing with both vendors.
Verdict: Tie. Cost is highly variable and needs to be assessed based on specific institutional needs.
8. User Experience (Student)
Knewton Alta’s integration within the LMS provides a seamless user experience for students, minimizing the need to navigate between platforms. The adaptive learning path feels natural and intuitive.
Riiid’s experience involves moving between the core course and the Riiid platform for targeted practice. While the platform itself is well-designed, the context switching could be disruptive for some students.
Verdict: Knewton Alta wins for a smoother, more integrated student experience.
9. AI Transparency & Explainability
Both companies emphasize the power of their AI, but transparency regarding the underlying algorithms remains limited. It’s difficult to understand exactly how each platform arrives at its recommendations or adapts content.
Knewton appears to be making strides in providing more explainable AI features, allowing instructors to understand why a student is being presented with certain content. Riiid’s focus on prediction makes the “why” less critical, but still valuable.
Verdict: Knewton Alta edges out Riiid for slightly better AI transparency.
10. Customer Support & Implementation
Knewton Alta, with its longer presence in the market, generally receives higher marks for customer support and implementation assistance. They have a well-established onboarding process and dedicated support teams.
Riiid is actively investing in its customer support infrastructure, but it’s still building out its team and resources. Implementation may require more active involvement from the institution’s IT staff.
Verdict: Knewton Alta wins for superior customer support and implementation services.
Key Takeaways
Overall, Knewton Alta emerges as the stronger solution for most higher education institutions seeking to improve student outcomes through AI. Its seamless LMS integration, highly adaptive content, and granular data insights offer a compelling package. It’s particularly well-suited for institutions prioritizing mastery-based learning and wanting to enhance existing course materials.
However, Riiid is a compelling option for institutions focused on early identification of at-risk students and proactive intervention. If your primary goal is to predict performance and provide targeted practice to boost final grades, Riiid’s predictive capabilities are a significant advantage. Riiid might also be a better fit for institutions exploring AI-driven learning solutions outside of a traditional LMS framework.
Validation Note: The claims made by both Riiid and Knewton Alta should be validated through proof-of-concept trials with your specific student population and curriculum. Conduct thorough reference checks with institutions currently using each platform to gather firsthand feedback on their experiences. Don’t rely solely on marketing materials; request detailed data and performance reports.
