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Record W4399861040 · doi:10.1145/3660650.3660661

Student Transitions Through an Entire Computing Program

2024· article· en· W4399861040 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicTeaching and Learning Programming
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDegree programWork (physics)Mathematics educationDisciplineComputer scienceMedical educationField (mathematics)PsychologySociologyMedicineEngineeringMathematics

Abstract

fetched live from OpenAlex

While the challenges experienced by first-year computing students have been well studied, little work has explored the transitions in disciplinary participation and challenges experienced by upper-years. This study explores how students’ needs and challenges evolve through a computing degree. We collected the experiences of first to final-year undergraduate computing students through surveys and interviews. We organized these experiences into themes that we compare against previous literature and illustrate with quotes. Upper-year students perceive changes in (a) levels of support and (b) the kinds of challenges they experience as they progress through the program. Second-year students feel pressured by the increasing difficulty of courses. This pressure increases through the third year as students begin to perceive a need to find employment. The experiences of our students suggest the need to better support the middle years of academic programs. Students in the first year are well-supported in their university transition, but students in the middle are often left to find their way as they develop a deeper understanding of their desired place in the field.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.842
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.362
Teacher spread0.334 · 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

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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