Personalizing a Tutoring Session

Why should tutors personalize their tutoring sessions?

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. This process involves regularly gathering data from the student — see the Data Use section’s detailed tools for guidance on collecting, protecting, and reviewing student data.

What data should tutors use to personalize tutoring sessions?

Tutors should prioritize Mastery Data, which is any data collected that provides information on a student’s mastery of the content or standard that is being taught.

Examples include:

“Exit Ticket” Data: Routine end-of-session assessments measuring whether a student has mastered the learning goal of that day’s tutoring session can give tutors an idea of which students need support with which content.
Student Work: Schoolwork, tutoring activities, or assignments. Analyzing student work samples can provide guidance on a student’s patterns of thinking, mastery, conceptual understanding, or strengths and weaknesses.
Data from Blended Learning Software: If your program’s Delivery Mode is Blended, high-quality software can give tutors access to a wealth of data on students’ performance in each skill area and common misconceptions.
Standardized Assessment Data: Tutors can use assessment data to identify the skills and concepts that students have mastered and the skills and concepts where students need remediation or learning acceleration.

Tutors should routinely collect data both on their students’ content mastery and on their own instructional efficacy. If tutors can collect data through Exit Tickets, they can then use that data to inform the planning and personalization of their next session each time. If not, tutors can also analyze standardized assessment data to plan for personalization.

How should tutors use Mastery Data to personalize learning sessions?

First, identify potential student learning barriers. A student might not have fully accomplished their learning goals for a number of reasons. Without identifying the root cause of the lack of mastery, tutors might try to solve a problem the student doesn’t actually have. Analyzing student assessment data or work sample data can help a tutor understand the barrier and plan a specific approach to address its root cause.

Then, plan for how to help. Based on the learning barrier identified, tutors should then customize their session plan to support their student to full mastery. This process is useful both when a student did not accomplish full mastery after being introduced to a skill or concept during a prior tutoring session, or when using student data to plan a session introducing a new skill or concept.

The table below can support tutors in identifying the learning barrier students are experiencing. Tutors are first asked to objectively identify what they observed, then consider the root cause for what they observed. Finally, they’re given options for how to address the barrier.

What did you observe?	Why did it happen?	How will you address it?
Was the student able to practice all aspects of the session’s learning goal? How many at-bats, or opportunities for practice, did the student have during the session?	Insufficient or misaligned practice Your data shows that the student had the necessary prior knowledge; however, they still struggled to apply the new skills.	Review practice from past sessions to check alignment with their learning goals. Did the student practice what they were assessed on? Add additional at-bats to upcoming sessions. Plan to monitor the student’s mastery as they practice and provide feedback. Reassess the student after more practice. Did they improve? If so, why; if not, why not?
Did the content in the session require previous knowledge or skills? Has the student demonstrated mastery of this knowledge or skill? Was new information presented in a different and unfamiliar way? (e.g. The student now had to extract data from a chart, not a table as they’d done before.)	Prior Knowledge Issue The student didn’t have (or struggled with) prerequisite concepts/skills that were necessary to access new material in the first place.	Return to the session’s learning goal: are there prerequisite skills/concepts embedded in the goal that need to be addressed? Review or re-teach missing prerequisite skills and concepts in upcoming sessions. Provide additional practice on the learning goal after pre-requisite skills are addressed. Reassess the student after more practice. Did they improve? If so, why; if not, why not?
Did the student come up with a wrong answer while following a reasonable logical process? Why? Was there material this session built on or continued that required the student to think about this concept in a new way? Is there previous vernacular the student has learned that might be getting in the way of learning this new vocabulary?	Common Misconception The student holds one or more common misconceptions that can be confusing when learning this specific material for the first time.	Plan an error analysis highlighting student misconception. If this was what they had misunderstood, which wrong answer would they give to the new question you design? Address and clarify the misconception. Provide additional practice after clarifying. Reassess the student after more practice. Did they improve? If so, why; if not, why not?
Did the student show correct conceptual understanding, but... ...Make a computational error? ...Forget a single crucial step while following the correct process? ...Make a minor thoughtless error?	Precision/Execution Error The student grasped the fundamental concepts of the material, but made more basic errors.	Consider boosting the rigor of this student’s practice to avoid boredom and carelessness. Provide practice where the student must correct a series of work samples that include precision or execution errors similar to the ones they demonstrated in their own work. Reassess the student after more practice. Did they improve? If so, why; if not, why not?
Did the student make a mistake you didn’t expect or haven’t seen before? Is there something you know about the student’s thinking that might explain it?	Uncommon Misunderstanding The student showed a misunderstanding you had no reason to plan for beforehand.	Consider re-teaching material in a new way. Ask open-ended questions about their work sample to gain clarity on their line of thinking and potential misunderstanding. Reassess the student after more practice. Did they improve? If so, why; if not, why not?