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Record W2810376743 · doi:10.22329/celt.v11i0.4981

Exploring the Foundations for Student Success: A SoTL Journey

2018· article· en· W2810376743 on OpenAlexaffvenue
Wallace Lockhart, Brad Wuetherick, Nola Joorisity

Bibliographic record

VenueCollected Essays on Learning and Teaching · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Research Studies
Canadian institutionsDalhousie UniversityUniversity of Regina
Fundersnot available
KeywordsPerspective (graphical)Engineering ethicsSociologyDiversity (politics)Educational researchPhenomenonQualitative researchUndergraduate researchPedagogyEpistemologyComputer scienceSocial scienceEngineeringMedical education

Abstract

fetched live from OpenAlex

This paper illustrates the chronology of a research project which began in 2010 and continues today. The research has evolved over time from a focus on the phenomenon (developing an understanding of student diversity and its impacts on student success), to experimental research (to learn the impact or benefits derived from the introduction of high impact practices), to a more complex understanding of the foundations for student success. The fourth stage of the research, which is just underway, divides our efforts into two distinct directions. The first is quantitative research utilizing institutional and learning management system data which was previously untracked and untapped. The second is a shift to employing more qualitative research tools aimed at advocacy and institutional change. Through each phase of the research the paper presents two distinct perspectives: First is the perspective of instructors-turned-SoTL-researchers as we muddle our way through understanding our challenges and learning how to use SoTL research methods to help guide the way. The second perspective is that of an established SoTL researcher, who provides commentary and guidance to our journey. Our hope is that the reader finds these two perspectives of a research journey both informative and valuable in providing insights into how a long-term research project might unfold.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.842
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0110.000
Scholarly communication0.0000.000
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 head0.124
GPT teacher head0.444
Teacher spread0.320 · 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 designNot applicable
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

Citations3
Published2018
Admission routes2
Has abstractyes

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