Implementation Checklist
- Identify stakeholder groups based on tutoring program design.
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If your program’s Tutor Consistency is Consistent, then each student’s experience of tutoring sessions will be shaped by the individual personality and instructional style of their tutor. Thoughtful and intentional pairings significantly increase the odds that a student will feel engaged with their sessions and supported by their tutor. A good student-tutor match helps students build strong relationships with their tutors and find motivation to reach their learning goals.
A Growth Mindset is the understanding that your skills and intelligence can be developed and improved through practice. This is in contrast to a Fixed Mindset, which is the belief that your qualities are fixed, innate, and cannot be improved. These concepts were originally codified by Stanford University psychologist Carol Dweck in her book Mindset.
When students can make connections between what they learn in tutoring and their culture, language, or life experiences, they can better access key ideas, develop higher-level understanding, and see the value of their learning in their daily lives.
Strong relationships are fundamental to students' success with tutoring. The more students feel safe, supported, and that they have a personal connection with their tutor, the more impactful the sessions will be. At the outset, relationship-building activities help tutors get to know their students and create a safe, positive learning environment. Building them into routine tutoring sessions helps tutors keep their knowledge of students alive and current.
We learn best from people who care about us. Students who feel a connection with their tutor are more likely to engage in learning, ask questions, build motivation, and achieve better academic outcomes. Strong tutor-student relationships built on a foundation of shared understanding and trust create the conditions for all students to take the risks necessary to make dramatic academic gains.
A virtual tutoring platform is an online conferencing system that facilitates virtual tutoring.
If your Student-Tutor Ratio is Small Groups instead of one-to-one, your tutors will need skills to establish group norms and manage behavior during sessions. In addition to the facilitation moves listed in the Facilitation Moves Checklist, small-group facilitation requires additional planning and tools to foster a positive, productive learning environment for a group.
Facilitation is what keeps a student engaged and on-task throughout a tutoring session. Effective facilitation requires thorough planning: not just around what concepts and skills to work on, but also around the routines, directions, and logistics of the tutoring session itself. Time the tutor spends thinking these things through ahead of time maximizes the time the student spends actually learning during the session, rather than getting situated or resolving confusions.
When students know what to expect, they can better internalize what is expected of them. If each session has a consistent rhythm, students will feel safer and more engaged, and tutors will deliver more consistent and effective sessions. Instead of spending prep time internalizing directions and pacing, they can focus on content.
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Blended learning is a delivery mode that combines live instruction with digital learning tools for independent practice. High-quality blended learning supplements live tutoring (either virtually or in person) with adaptive software, which modifies the presentation of material in response to student performance to support student learning.
If your Student-Tutor Ratio is Small Groups instead of one-on-one, the composition of these groups will influence session effectiveness. If students are grouped haphazardly, without regard for their academic strengths and struggles, then tutors will find it much more challenging to meet the individual needs of every student in a group.
Students all learn in different ways: some of these differences are obvious, while others are more subtle. However, this seemingly simple truth is surprisingly difficult to internalize in practice. Most learning experiences are designed with only one kind of learning in mind, and thus optimized for only one kind of learner.
The most effective sessions are personalized to meet an individual student’s needs. Student productivity and growth will increase if the tutor can identify the missing or incomplete skills that are holding a student back and focus on those specific skills. Identifying and addressing these skill gaps requires tutors to use both quantitative and qualitative data to shape the content they include and the approach they use during sessions.
A Landscape Analysis outlines the strengths, resources, and needs of a particular community. It provides a framework for designing a service and ensuring that it is embedded directly in the needs of the community.
While tutoring programs vary greatly in the content that is focused on during sessions, tutors should have a standards-aligned, rigorous, and grade-level appropriate curriculum to use during sessions. Having an established curriculum for tutors to follow ensures that tutors’ planning time is spent optimizing implementation and building deep content knowledge, not creating tutoring session plans.
Below, you will find two protocols for reviewing student academic data, one for a frequent post-session review and one for any data collected on an interim or infrequent basis. These protocols follow the same What/So What/Now What format as the Standard Data Review Protocol, but they are tailored with tutor-specific questions to guide data analysis.
Standardizing a Data Review process helps set a clear expectation that the end product of Data Review is not knowledge, but action. Any Data Review Protocol should ensure that raw data is converted into a clear and digestible format before the reflection process so that reviewers can focus their energies on reflecting on the data, rather than synthesizing the data.
Data Review is the process of collecting data, reflecting on it, and distilling it into actionable insights. This process is how you can turn data into knowledge and knowledge into action. Data Review requires going "below the surface" to find root causes for your results (both positive and negative) and planning actionable changes to continue improving your program.
Consult an attorney to ensure program compliance with all federal, state, and local laws.
Logic Model Elements (Program Outputs and Short Term Impact) | Sub-Area | Measures | Tool | Data Collection Cadence | Performance Expectation |
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A Performance Management Plan outlines how to assess a program’s progress towards making the desired Impact defined in its Logic Model, complete with key benchmarks to hit by specific dates. It is a reusable, consistent roadmap for finding rigorous answers to questions like “Are we on track?” or “What are we doing well?” or “How can we improve?”