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Record W3121797424

Sink or Skim: Textbook Reading Behaviors of Introductory Accounting Students

2006· article· en· W3121797424 on OpenAlexaff
Barbara J. Phillips

Bibliographic record

VenueSSRN Electronic Journal · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting Education and Careers
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsReading (process)Mathematics educationClass (philosophy)PsychologyConfusionComprehensionReading comprehensionPedagogyComputer scienceLinguistics
DOInot available

Abstract

fetched live from OpenAlex

Despite the significant emphasis that most instructors place on textbooks in introductory accounting courses, little research exists to describe how students interact with their textbooks. Using learning journals, 172 undergraduate students provided detailed, real-time accounts of their experiences with 13 chapters of an introductory financial accounting textbook. Using the method of grounded theory, supplemented with quantitative tests of association, this study begins to characterize textbook use from a student perspective. Results indicate that, for students, reading is a motivated behavior, with the specific motives varying across different groups of students and leading to different consequential actions. Academically strong students appear to read with the primary goal of understanding assigned material, as evidenced by their willingness to (a) engage in reading before the related material is covered in class, (b) persist when material becomes difficult, and (c) establish defined action plans that promptly resolve confusion. In contrast, weaker students appear to read with the primary goal of reducing anxiety, by deferring reading and terminating it when comprehension becomes difficult. The findings of this study are used to create instructional guidance that instructors can provide to students and to direct future research by outlining important and interesting questions requiring further investigation. Sink or Skim: Textbook Reading Behaviors of Introductory Accounting Students When you were a student in your first accounting class, did you ever count how many pages were left in the textbook chapter while doing the assigned reading? Did you ever read the textbook while working at a part-time job? Did you ever put off the assigned reading because you thought it would be more effective to complete just before the exam? Understanding how students read textbooks is of critical importance to instructors because educational researchers have observed that higher education institutions rely extensively on textbooks (McFall 2005). Textbooks aim to communicate the content, beliefs, values, and methods of a discipline (Richardson 2002), and influence the structure of courses and knowledge that is built within a particular field (Issitt 2004). A significant barrier that might thwart these goals is that students may not use textbooks in the way they were intended. The existing published research offers little insight into such issues because few empirical studies describe college textbook use (Bessler et al. 1999). The purpose of this study is to develop a multidimensional characterization of how students use their textbooks, so that we can begin to determine whether students’ reading behaviors are likely to prevent textbooks from achieving their intended goals. Several authors have developed normative standards regarding how students should read textbooks. Allen (1999) recommends students preview a chapter to set out a reading purpose, monitor their reading to keep their focus on that purpose, and periodically evaluate how much they are learning. To this process, Barnett (1998) adds the task of revising reading strategies based on self-evaluation and external feedback. In contrast to this reasoned approach, the scant empirical evidence suggests that most students are passive readers who fail to use active strategies (McFall 2005) even when trained to do so through a reading skills workshop (Barnett 1998). Furthermore, reading strategies differ by discipline; 70% of students surveyed in an

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.364
Threshold uncertainty score0.797

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.007
GPT teacher head0.247
Teacher spread0.241 · 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 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

Citations4
Published2006
Admission routes1
Has abstractyes

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