Teacher practice
Can showing shared interests improve student-teacher mentoring?
Open access · cc by · source: Europe PMC
Sharing common interests only helps students who initially feel very different from their instructors feel closer to them, which indirectly improves their mentoring relationship.
Study at a glance
- Design
- Other — Cluster-randomized classroom trial emailing shared instructor–student similarities
- N
- N=505 · 505 biology students in 15 classrooms across 13 US universities
- Population
- College biology students in semester-long research courses
- Outcome
- Perceived similarity and mentoring relationship quality, especially for initially dissimilar students
Structured fields used in claim comparison tables when every cited study has a complete layer.
Key findings
The intervention did not have a general, direct effect on all students' feelings of similarity or mentoring quality. However, for students who initially felt very different from their instructor, the intervention successfully increased their perceived similarity by the end of the term. This boost in perceived similarity subsequently led these students to report a higher-quality mentoring relationship.
Methodology
The researchers studied 505 biology students across 15 classrooms at 13 universities during a semester-long research course. Classrooms were randomly assigned to either a control group or an intervention group where students received emails highlighting three personal similarities they shared with their instructor. At the start and end of the semester, students completed surveys measuring how similar they felt to their teacher and how they rated the quality of their mentoring relationship.
Limitations
The study suffered from baseline differences because classrooms assigned to the intervention had larger enrollment sizes than control classes, which generally dampens feelings of connection. It also relies completely on self-reported survey data, meaning it does not measure actual behaviors or academic outcomes like grades. Lastly, because the evaluation grouped diverse dimensions of mentoring support into a single score, it cannot show if specific types of guidance like career advice were improved more than others.
How this study connects
Role on claims
Each row is a claim on a concept or method page where this paper supports, challenges, or qualifies the statement. Roles are hand-checked — not a model guess.
Classrooms were randomly assigned so that 505 biology students in 15 rooms at 13 universities received start- and end-of-term mentoring surveys; intervention rooms got emails highlighting three personal similarities with the instructor. There was no general effect on perceived similarity or mentoring quality; students who began feeling very different from the instructor did increase perceived similarity. Intervention classrooms were larger at baseline.
Evidence for the claim as stated.
Pre/post windows are not interchangeable designs. Peer feedback and faculty training are single-group rises. The ITS paper randomises after exclusions and adjusts for prior scores. Chatbots contrast two intact classes. Mentoring randomises classrooms and finds a null average with a subgroup gain. COVID UDL is a retrospective perception contrast, not a scored artefact. Calling all of them 'pre-test/post-test evidence that teaching improved' hides those differences.
Evidence for the claim as stated.
A classroom-randomised similarity-email intervention in 505 biology students across 15 classrooms at 13 universities did not raise perceived similarity or mentoring quality in general. It did increase end-of-term similarity for students who started out feeling very different from the instructor. Intervention classrooms were larger at baseline, which the authors note generally dampens connection.
Evidence for the claim as stated.
Unit of randomisation and what 'worked' disagree across the three papers. Classrooms were assigned in the mentoring study, so baseline enrolment size is a cluster confounder and the average treatment effect was null. Individuals were assigned in the CMC and ITS studies, which can show average gains in engagement or posttest scores without speaking to school-level implementation. Reading all three as 'RCTs of teaching' hides that.
Evidence for the claim as stated.
Open questions
Tensions this paper is part of
From concept pages' “where studies disagree.” Disagreement means the same question; scope means different assays, populations, or outcomes.
Pre/post windows are not interchangeable designs. Peer feedback and faculty training are single-group rises. The ITS paper randomises after exclusions and adjusts for prior scores. Chatbots contrast two intact classes. Mentoring randomises classrooms and finds a null average with a subgroup gain. COVID UDL is a retrospective perception contrast, not a scored artefact. Calling all of them 'pre-test/post-test evidence that teaching improved' hides those differences.
- Supports · Online peer feedback that improves argumentative essays
- Supports · Faculty training that shifts teaching innovation attitudes
- Supports · Can a dialogue ITS fix fraction multiplication?
- Supports · Do educational chatbots raise project-course grades?
- Supports · Did remote COVID teaching feel less engaging to students?
Unit of randomisation and what 'worked' disagree across the three papers. Classrooms were assigned in the mentoring study, so baseline enrolment size is a cluster confounder and the average treatment effect was null. Individuals were assigned in the CMC and ITS studies, which can show average gains in engagement or posttest scores without speaking to school-level implementation. Reading all three as 'RCTs of teaching' hides that.
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