Intelligence

ai

Understanding Computing Identity Development Through Mentorship and Epistemic Network Analysis

Source
arXiv — Computers and Society
Published
Last verified
19 Aug 2026
Confidence
Moderate
Evidence
Original document retained
Reading time
1 min
Country
International
Relevant to
Research & Evidence, Technology & Data

Executive summary

What happened, and why should leadership care?

A research study explored how computing identity develops among students in computing-related fields, utilizing open-ended survey responses from 37 participants. The study applied Epistemic Network Analysis (ENA) to model the co-occurrence of six identity-related constructs. A key focus was comparing identity narratives between individuals who reported mentorship support and those who did not, finding distinct structural patterns based on mentorship presence.

Why this matters

Why is this strategically important?

Understanding the factors influencing computing identity, particularly the role of mentorship, is crucial for fostering engagement and retention in technical fields. This insight can inform strategies to enhance participation and belonging, thereby strengthening the talent pipeline for critical sectors dependent on computing expertise.

Key insights

What should be noted from the evidence?

  • Computing identity significantly influences student participation, persistence, and sense of belonging in computing disciplines.
  • Traditional survey measures may not fully capture the complexity of identity development.
  • The study used open-ended survey responses from 37 participants in computing-related fields.
  • Epistemic Network Analysis (ENA) was employed to model co-occurrence patterns among six identity constructs: recognition, interest, competence, sense of belonging, self-doubt, and imposter syndrome.
  • Distinct differences were observed in the structure of computing identity narratives between participants who received mentorship support and those who did not.

Evidence and confidence

How far can this assessment be trusted?

Moderate confidence. Provenance established; supporting evidence remains partial.

Analysis is prepared editorially by Aziz Shuaib Ausi. The original publication remains the authoritative record, and executive judgement remains entirely human.

Source

Where does this originate?

Reported by arXiv — Computers and Society · International. This briefing summarises the publication for executive use; the document itself is not reproduced here.

Read the original publication