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Record W7080284735 · doi:10.18357/otessaj.2024.4.3.69

Beyond the Lecture: A Flipped Class Approach to Paralegal Education

2025· article· en· W7080284735 on OpenAlexafffundvenueabout

Bibliographic record

VenueThe Open/Technology in Education Society and Scholarship Association Journal · 2025
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsMacEwan University
FundersMacEwan University
KeywordsCurriculumComprehensionFlipped classroomFocus groupFlipped learningClass (philosophy)

Abstract

fetched live from OpenAlex

In Canada, paralegal education lacks comprehensive pedagogical research in effective instructional models. Historically, paralegal programs focus on clerical skills, neglecting higher-level legal comprehension and analytical abilities that are vital for a paralegal role in the workforce. This research addresses this gap by exploring the implementation of a flipped classroom approach in an Alberta university that offers paralegal education. This study evaluated whether a flipped classroom in a legal technology course could enhance engagement and understanding of fundamental legal principles among paralegal students, compared to lecture-based models in other previously experienced university courses. Survey data collected through a mixed methods approach in April 2024 revealed that most participants believed that the flipped classroom encouraged participation, felt more confident in applying legal concepts, and were better prepared for the workforce. By examining the impact of flipped classrooms on paralegal education, this research provides insights that can inform curriculum development, address paralegal training challenges, and ensure the acquisition of necessary competencies for success in the legal industry.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.837
Threshold uncertainty score0.923

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.281
Teacher spread0.270 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2025
Admission routes4
Has abstractyes

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