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Record W2111358603

Assessment in History: The Case for “Decoding” the Discipline

2012· article· en· W2111358603 on OpenAlexaboutno aff
David Pace

Bibliographic record

VenueIndiana Magazine of History (Indiana University) · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsDecoding methodsPsychologySociologyComputer scienceAlgorithm
DOInot available

Abstract

fetched live from OpenAlex

I have been a professional historian for more than four decades, and I never once envied physicists — at least not until I encountered the “Force Concept Inventory” (Hestenes, Wells, & Swackhamer, 1992). This set of questions allows teachers of physics to determine whether students have internalized the basic Newtonian model taught in physics courses or whether they automatically fall back on “Aristotelian” notions of objects moving in space. It gives instructors in the field a simple instrument for determining the sophistication of students entering their classes and for evaluating the success of their own teaching strategies over a semester. This kind of disciplinary consensus about learning goals allows for the kind of far reaching and impressive assessment of learning that has allowed scholars of teaching and learning like Richard Hake to make convincing claims about the relative value of different teaching strategies (Hake, 1998; Bain, 2004). A historian reading such work is apt to be immediately struck by the absence in his or her own field of this kind of agreement about what should be taught and what constitutes reasonable evidence that it has been learned. While physicists certainly argue about theoretical issues at the forefront of knowledge, they do not need to spend a great deal of effort justifying either the truth value of Newtonian mechanics or its relevance to the curriculum. In a discipline such as history, by contrast, undergraduates can enter contested spaces from their first day in the college classroom, and the subject matter that they are studying is as varied as the cultures that have left a trace on this planet. Both the ambiguity of sources and the co-existence of mutually contradictory interpretations would seem to dictate that history is and is apt to remain a “fuzzy” discipline. This relative dearth of consensus is a result of the nature of the phenomena historians study, rather than any great deficiency in their profession, but it does lead to difficulties in creating a credible scholarship of teaching and learning. In a field in which reasoning is, of necessity, somewhat nebulous, it can be daunting to develop a clear consensus on what constitutes evidence that learning has occurred. Yet, assessment is at the core of the entire SoTL enterprise. It is difficult to imagine a robust scholarship of teaching and learning unless our work is cumulative and built on previous research and unless there is a means to systematically evaluate the validity of claims being made about student learning. In the now canonical formulation of Lee Shulman, the scholarship of teaching and learning must be “public, susceptible to critical review and evaluation, and accessible for exchange and use by other members of one’s scholarly community” (Shulman, 1998). Historians have made considerable progress in making SoTL public and accessible. An international society of historians working in the field has been created with its own website and newsletter, (http://www.indiana.edu/~histsotl/) and there is a growing programmatic literature exploring how the discipline might respond to the challenge of SoTL (Booth, 1996; Calder, Cutler, & Kelly, 2002; Pace, 2004, 2008; Brawley, Kelly, & Timmins, 2009).

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.084
GPT teacher head0.328
Teacher spread0.245 · 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

Citations8
Published2012
Admission routes1
Has abstractyes

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