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Record W2992177094

Students' Revealed Preference for Pedagogical Features in Introductory Economics Textbooks *

2015· article· en· W2992177094 on OpenAlexaboutno aff
Elijah M. James

Bibliographic record

VenueJournal of economics and economic education research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicInnovations in Educational Methods
Canadian institutionsnot available
Fundersnot available
KeywordsSubject (documents)DiligenceMathematics educationCurrencyComputer scienceSociologyPedagogyPsychologyLibrary sciencePhilosophy
DOInot available

Abstract

fetched live from OpenAlex

JEL codes: A1, A2, A22Technological advance has touched every facet of modern society, and teaching and education have not escaped its tentacles. Interactive electronic whiteboards, digital projectors, clickers in the classroom, digital texts, open educational resources (OERs), laptops, tablets, smart phones and other such modern electronic devices are being introduced into the classroom with increasing rapidity. Despite these innovations in teaching and learning tools and devices, a study by Watts and Schaur (2011) revealed that the traditional textbook remains the main tool for teaching the principles course in economics. For the purpose of this discussion, we define a traditional textbook as a printed and bound document used in schools for the formal study of a particular subject.According to Bargate (2012), Textbooks are the site where specialist knowledge and skills of the discipline are accumulated, communicated, and debated, and may possibly make or break students' interest in a subject. Other authors also extoll the importance of textbooks. See, for example, Pope (2002); Stevens, Clow, McConkey & Silver (2010); Razek, Hosch & Pearl (1982); Landrum & Hormel (2002); and Issitt (2004). Clearly, the selection of textbooks is an exercise that should be undertaken with due diligence. Many criteria are used in the textbook selection exercise. For example, Stevens, Clow, McConkey & Tiger (2007) and Elbeck, Williams, Peters & Frankforter (2009) examined currency, while Clow, Parker & *The author would like to thank the editors of the Journal of Economics and Economic Education Research for very helpful comments and suggestions.McConkey (2009) identified content, ancillary materials, length of textbook, and textbook costs as key factors in textbook selection.Proceeding on the assumption that the traditional textbook will continue to be the main tool used for the teaching of the principles course in economics, least for the foreseeable future, economics professors, textbook authors, and textbook publishers would benefit tremendously if they knew what pedagogical features the main readers of textbooks (that is, students) thought were in textbooks. Economics professors would benefit because they would be greatly aided in their selection of textbooks for their principles classes. Textbook authors would benefit because they would be able to include in their textbooks those features that students believe to be most helpful in their study of the subject; and textbook publishers would be greatly aided in their selection of manuscripts to be published on the basis of pedagogical elements.THE SAMPLEThe sample for this research project consisted of 250 students who were taking the introduction to economics course in the fall and winter semesters of 2011-2012 Dawson College in Montreal, Canada. It also consisted of 80 students who were taking the introduction to microeconomics course the same time. Thus, 330 students were surveyed. Of these, 175 were males while 155 were females. The students were also categorized as passing, at risk of failing, and failing.STUDENTS' REVEALED PREFERENCEIn order to gauge students' preferences for certain pedagogical features in introductory economics textbooks, the author designed a questionnaire consisting of ten questions regarding certain pedagogical features of textbooks. For each feature, the students were asked to rank their preferences for the feature on a Linkert-type scale denoting Not important, Somewhat important, Important, Very important or Extremely important. (The questionnaire is available from the author on request). The textbook features examined were:1. A preview of what is to be learnt2. Pre-test of knowledge before reading the chapter3. Explanations of graphs within the text (as opposed to being set apart in boxes)4. Basic concepts emphasized (such as highlighted, bold) in the text5. …

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)0.013
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.417
GPT teacher head0.558
Teacher spread0.141 · 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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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