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Record W1601797899 · doi:10.19173/irrodl.v11i1.778

The role of volition in distance education: An exploration of its capacities

2010· article· en· W1601797899 on OpenAlexvenueno aff
Markus Deimann, Theo Bastiaens

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2010
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsnot available
Fundersnot available
KeywordsVolition (linguistics)PsychologyCompetence (human resources)CognitionCognitive psychologyGermanSocial psychology

Abstract

fetched live from OpenAlex

During the past two decades, volition, defined as the ability to stay task-focused and ward off distractions, has become of special relevance for educational research and practice. It describes how decreased motivation or negative emotions can be dealt with by applying action control strategies. However, despite its potential, an important area of education has neglected volitional considerations: distance education (DE). This seems paradoxical because by its very nature distance education requires a great deal of persistence and effort that is volitional. Consequently, the present paper introduces a conceptual framework built on volitional theories; it aims to augment traditional perspectives and to analyse major challenges to DE, such as dropout rates. The paper reports results from a longitudinal study (September 2007-July 2009) that was conducted to determine the factorial structure of the Volitional Persona Test (VPT), an online instrument to assess volitional competence, and to obtain detailed information on students’ volitional competence at a large DE university and at numerous traditional universities in German-speaking countries. It was demonstrated that the construct of volition can be subdivided into distinct factors, volitional self-efficacy, consequence control, emotion control, and meta-cognition, which may enable the development of support systems that are tailored to learners’ individual needs. Implications for future research are discussed.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.765
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.101
GPT teacher head0.460
Teacher spread0.359 · 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

Citations78
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueThe International Review of Research in Open and Distributed LearningSame topicMotivation and Self-Concept in SportsFrench-language works237,207