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Record W2790370829 · doi:10.1080/03098265.2018.1455173

Can first-year undergraduate geography students do individual research?

2018· article· en· W2790370829 on OpenAlexaffabout
Xulin Guo, Kara Loy, Ryan Banow

Bibliographic record

VenueJournal of Geography in Higher Education · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicGeography Education and Pedagogy
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsUndergraduate researchScholarshipClass (philosophy)Mathematics educationScholarship of Teaching and LearningAcademic yearHigher educationPedagogyPsychologyTeaching methodMedical educationPolitical scienceComputer scienceMedicineTeaching and learning center

Abstract

fetched live from OpenAlex

Based on the affirmation in the scholarship of teaching and learning that adding research component into early geography classes is mutually beneficial to both instructors and students, this paper presents a case study that quantitatively articulates the effects of adding a research project into a first-year physical geography class on students’ academic performance. Pushing research into earlier stages of undergraduate students’ academics, even in large classes, can be very beneficial yet challenging because most students at this level have no experience in research; plus, they may still be adjusting to university life. Part of the Undergraduate Research Initiative called First Year Research Experience (FYRE) at the University of Saskatchewan in Canada invited faculty to embed a research component into first year undergraduate classes to align research and teaching. A two-year endeavour in a first year physical geography class resulted in some interesting outcomes. (1) The most challenging part of research for students was the research question formation. (2) Students valued the opportunity to conduct a research project. (3) Doing in-class research actually improved student performance as seen in the higher overall average grades. (4) Students who attained the highest exam marks were not those who attained the highest research project marks.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.089
GPT teacher head0.441
Teacher spread0.352 · 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

Citations13
Published2018
Admission routes2
Has abstractyes

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