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Record W2749861634

The Design of an Educationally Beneficial Immediate Feedback System

2017· dissertation· en· W2749861634 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Atrium (University of Guelph) · 2017
Typedissertation
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsnot available
FundersUniversity of Guelph
KeywordsComputer scienceMathematics educationPsychology
DOInot available

Abstract

fetched live from OpenAlex

Student learning is positively affected by the quality, and timeliness of feedback they receive on their assignments and homework. Unfortunately, as class sizes increase, instructors find it increasingly difficult to produce meaningful feedback for students in a timely fashion. To maintain an environment in which a student can continue to receive beneficial feedback, an alternate scalable method of providing feedback needs to be established. This document presents the design of a system capable of providing automated feedback to students on their work immediately after it is requested. A prototype of the design that produces feedback on C programs was developed, and provided to computer science students. An analysis of the usage of the system, and the student work submitted to it shows the design can produce feedback that students find valuable, improves the learning experience, and improves programming ability. The positive results suggest that further research should be conducted.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.422
Threshold uncertainty score0.658

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 communication0.0000.000
Open science0.0010.000
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 head0.010
GPT teacher head0.213
Teacher spread0.203 · 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