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Record W4410890690 · doi:10.20343/teachlearninqu.13.23

Context Matters: Enhancing SoTL by Exploring Interpersonal Relationship Building in Higher Education

2025· article· en· W4410890690 on OpenAlexaff
Nira Rahman, Hannah Cobb, Lindsay Giddings, Mary Helen Truglia, Sara Dolan, Surita Jhangiani, Kevin O’Connor

Bibliographic record

VenueTeaching & Learning Inquiry The ISSOTL Journal · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsMount Royal UniversityUniversity of British ColumbiaUniversity of Calgary
FundersUniversity of Wyoming
KeywordsContext (archaeology)Higher educationInterpersonal communicationInterpersonal relationshipPsychologyPedagogyScholarship of Teaching and LearningSociologyFaculty developmentEngineering ethicsProfessional developmentSocial psychologyTeaching methodPolitical scienceEngineeringGeographyTeaching and learning center

Abstract

fetched live from OpenAlex

This paper contributes to SoTL by critically examining the literature on the nature of interpersonal relationships across global higher education settings through narrative inquiry, focusing on both online and in-person learning. Drawing on previous literature (to show patterns of inquiry) and fictional student cases (to give concrete details and examples), this paper examines how educators’ relationships with students shape learning outcomes and experiences and looks at the intricate role of trust in fostering interpersonal relationships within educational settings. The impact of trust is examined across various dimensions—from student-teacher dynamics to peer interactions and institutional structures. Key themes of deliberate interaction, clear communication, and activities for belonging emerge as crucial for fostering supportive learning environments. The analysis underscores the significance of empathetic communication and culturally responsive pedagogies in enhancing student engagement and well-being. Trust, foundational to all those themes, is analyzed through lenses of honesty and benevolence, two essential perspectives for establishing reliable educational environments for students from a variety of societal and educational backgrounds. Through the fictionalized cases, the authors investigate how trust, as cultivated through reflective practices such as the 5Rs framework (Bain et al. 2002), enhances student engagement and inclusivity. By integrating personal reflections and scholarly literature from SoTL, this paper advocates for pedagogical practices that prioritize inclusive, relational approaches in education across diverse contexts.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.810
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.083
GPT teacher head0.381
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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