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Record W117090199

Effective Use of Logbooks in Engineering Education: Enhancing Communication through Short Design Activities

2013· article· en· W117090199 on OpenAlexaffabout
Libby Osgood

Bibliographic record

VenueScholarship@Western (Western University) · 2013
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsDocumentationLogbookAccreditationCurriculumTask (project management)Scope (computer science)EngineeringEngineering ethicsMedical educationComputer scienceEngineering managementPedagogyPsychologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

For engineering educators who employ active learning techniques such as design projects, logbooks are an ideal way to enhance students’ ability to communicate effectively. In industry, students are expected to write effective reports and produce design documentation (Canadian Engineering Accreditation Board, 2008). In order to fully develop these documentation skills, students must have regular practice. Logbooks are an excellent repository for design documentation and encourage regular use. However, merely requiring the use of logbooks without providing regular guidance or training is irrational.\nLogbooks are primarily used in the engineering profession as a way to document an individual’s progress with a particular project. Activities such as precursory analysis, initial sketches, task lists, programmatic issues, reflections of past work, meeting agendas and meeting minutes are typical items recorded in a logbook. Logbooks are typically hardback, paper based products that are bound in such a way as to ensure that pages cannot be removed; consequently, logbooks are sometimes used as legal records in professional liability, intellectual property and project scope disputes (McAlpine, Hicks, Huet, & Culley, 2006).\nDesign projects present an ideal situation to employ logbooks to enhance communication skills (Yang, 2009). Many engineering educators require their students to use logbooks in active learning projects. However, after regular use, a renewed focus on logbooks is often necessary to reconsider what to record as pertinent information and when is an appropriate time to do so. For participants who are currently supervising design activities, a renewed look at logbooks will assist them in asserting the importance of logbook use in design activities. Furthermore, it will also enhance their own communication skills and the skills of the students they supervise.\nThis workshop is intended for instructors, professors, and graduate students to consider interactive methods to teach proper logbook use. Participants in the workshop will sample an interactive activity that is recommended to teach students the importance of logbooks. Instruction, brainstorming, and discussion will follow. Participants in the workshop will learn the importance of a logbook, define which activities should be recorded in a logbook and state the necessary elements to record in a logbook.

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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
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 communication0.0000.002
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 head0.058
GPT teacher head0.275
Teacher spread0.217 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations2
Published2013
Admission routes2
Has abstractyes

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