Designing Quality Topic 5
Learning with data and feedback that offers real-time, formative and summative feedback data on performance.
VISION
A high quality data driven program provides students data and feedback as an integral ongoing part of learning that captures student growth toward mastery.
- It is timely, relevant, actionable, and visually compelling.
- It is a powerful strategic tool that empowers students to make appropriate choices that lead toward a specific goal.
- It allows educators to more effectively serve each students needs.
Students receive tons of information. But they don’t necessarily have access to salient compelling information in real time that holds before them an interesting goal, a path toward that goal and an indicator of progress and potential next steps that can lead to purposeful action. Effective high-quality learning requires this kind of timely, relevant, actionable, ongoing feedback and data. This data should also be integral to the design, implementation and continuous quality improvement of online learning.
Design Principles
Relevant feedback, just in time delivery:
- Data and feedback delivered are relevant and readily available just in time.
- Embedded throughout learning process
Allows students to visualize and balance an array of factors that impact learning, such as memory, attention, motivation, resilience, not just traditional standards
- Actionable and manipulable for multiple purposes
Multiple Perspectives: Data views allow users to access a wide array of data sets, scales and levels of granularity and are also customizable by user or user group.
- Item to concept views; individual to group or community views
- Text or visualizations
Triangulation: Data can be seamlessly integrated across and validated using multiple platforms and tools.
- Varied assessment types, methods, standards, metrics, platforms, applications, etc.
- Integrates with grade-book or other types of existing classroom data tools
Path, Performance, and Progress: Feedback design is based on learning pathways, and data and feedback are used to indicate explicitly and measure student performance and progress along that pathway.
- Student goals are identified
- Trajectory mapped toward goal achievement
- Progress is recognized frequently: positive feedback loops
Continuous Quality Improvement Loop: Data is leveraged to continually improve design, implementation and quality.
- Data drives design and re-design
- Data is used by educators to improve learning or implementation
Creating a change in the culture of education is the most critical challenge that must be overcome to ensure successful implementation of high quality data driven courseware. To mitigate this challenge, we must provide educators with the tools and training that they need to analyze data in a manner that is useful and applicable to improving student outcomes.
Other key challenges are faced by the courseware designers. One challenge is developing a clear understanding of what students need to know; ensuring predictive, reliable, and valid measures. The second challenge designers face is ensuring a high return on development investment. The final challenge is convincing designers to development of open platforms so that data can be easily integrated across multiple products.