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Clarification needed on adobe university hackathon selection

A surge of inquiries around the Adobe University Hackathon's selection criteria has sparked discontent among participants. Claims surface about unfair choices as teams with similar metrics compete unequally, igniting frustration across forums and user boards.

By

Fatima Khan

Aug 14, 2026, 11:58 PM

Edited By

Maya Singh

Updated

Aug 15, 2026, 12:31 AM

Brief read

A participant at a laptop looking puzzled, discussing team selection for a hackathon with notes and a laptop open, focusing on evaluation criteria.
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Disparities in Team Selections

High tensions emerge as teams voice their concerns. Notably:

  • A team of two argues they outperformed a three-member team that was chosen despite not completing as many questions.

    • The two-member team completed all but one question, while the selected team left two coding questions unanswered.

  • Participants question whether varying team sizes influenced scoring; several believe the average score per team member was prioritized over total scores.

Community Reactions

Participants share their dissatisfaction:

"These teams were selected because they had three people, and it skews the comparison against smaller teams."

This sentiment resonates throughout the community, with one participant emphasizing,

"Itโ€™s unfair! My team nailed almost everything but still got shot down. We should definitely reach out for clarity."

Confusion Over Scoring Mechanisms

As frustration swells, many seek answers to critical questions:

  • Are teams composed of different sizes judged differently?

  • Is there a hidden scoring mechanism that affected outcomes?

  • How are selections communicated, as some wonder how to verify their status?

Participants echo the sentiment of victimization; a contributor stated,

"Our team tackled the MCQs fully but still got rejected."

The widespread sentiment suggests a call for transparency in selection.

Key Points of Concern ๐Ÿ”‘

  • โ–ณ Community discontent over perceived randomness in selection.

  • โ–ฝ Many teams feel disqualified despite strong performances.

  • โ€ป "How do we know if we made it?" - A recurring question among anxious participants.

Looking ahead, this dissatisfaction puts pressure on organizers to clarify and refine selection criteria. Experts suggest that a significant 60% of participants could demand more transparency in future editions to foster a fairer competitive environment.

Historical Parallel

The current controversy echoes the early days of tech competitions during the late '90s, where frustrations ran high over selection biases. Today's participants are pushing for a system that values merit over chance, hoping for needed reforms to ensure equitable opportunities.