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Record W2216625225 · doi:10.11575/prism/30326

A TOOL FOR TEACHING ADVANCED DATA STRUCTURES TO COMPUTER SCIENCE STUDENTS AN OVERVIEW OF THE BDP SYSTEM

2000· article· en· W2216625225 on OpenAlexaff
Katrin Becker, Melissa Beacham

Bibliographic record

VenuePRISM (University of Calgary) · 2000
Typearticle
Languageen
FieldComputer Science
TopicAlgorithms and Data Compression
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer scienceTask (project management)Data structureCode (set theory)Order (exchange)Software engineeringMathematics educationComputer engineeringHuman–computer interactionProgramming languageSystems engineeringEngineering

Abstract

fetched live from OpenAlex

In order to design and write effective, robust code using advanced data structures, it is crucial to achieve a thorough understanding of the algorithms used to manipulate these structures. One means of accomplishing the task is to provide students with a graphical, animated system that allows users to observe changes that the structure undergoes while it is being used. One such system has been developed which demonstrates B-Trees. Some preliminary testing is complete and some initial reactions of the students who have tried the system are outlined.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.038
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0380.019

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 head0.284
Teacher spread0.256 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations15
Published2000
Admission routes1
Has abstractyes

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