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Record W3013516778 · doi:10.1108/jarhe-12-2019-0309

Factors affecting assignment completion in higher education

2020· article· en· W3013516778 on OpenAlexaff
Wuttiporn Suamuang, Surachai Suksakulchai, Elizabeth Murphy

Bibliographic record

VenueJournal of Applied Research in Higher Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsTask (project management)Variety (cybernetics)PsychologyPerceptionAffect (linguistics)Time managementStructural equation modelingOrientation (vector space)Variable (mathematics)Relation (database)Point (geometry)Mathematics educationApplied psychologySocial psychologyComputer scienceMathematicsEngineeringCommunication

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to simultaneously investigate a variety of factors related to assignment completion (AC) (i.e. task orientation, cooperation, teacher feedback, time management and time spent on AC). Design/methodology/approach The study relied on a self-report survey to assess students' perceptions in relation to six variables. Participants included 1,106 undergraduate students from six public Thai universities. Analysis involved structural equation modeling. Findings This study provided new results related to task orientation as the strongest predictor of AC and time management. Cooperation and feedback improved AC with time management as an intervening variable. Time management and feedback did not predict time spent on AC. Research limitations/implications Future studies might explore the potential range of assignments that, for example, count for a higher portion of the grade versus those that are less or unimportant in terms of the course. Future studies might also look at the role of group assignments in relation to completion. Semi-structured interviews or observations might provide insights into how students manage their time and why task orientation has the most effect on AC. Future research might investigate more specifically at what point time management does or does not affect completion. In general, given the growth of online learning and contexts in which students may be increasingly called on to complete assignments independently, factors such as those investigated in this study will require more attention in varying countries and contexts, generically and for individual subjects. Practical implications Instructional designers and instructors can promote task orientation through reliance on strategic scaffolding. For designing a task-oriented environment, instructors need to offer challenging assignments. Instructors should also assign work that encourages motivation, effort and achievement. To ensure that cooperative learning positively affects time management, instructors and designers can allot specific in-class time for completion of tasks, reliance on flipped classroom activities and student conversations regarding time restrictions and time-management skills. Instructors can be supported to help them provide appropriate types of feedback, as well as ideas for implementing the feedback in practice. Originality/value Little research has been conducted on AC in higher education. Those studies that have been conducted have focused on the elementary and secondary levels. Furthermore, studies have not always taken into account the complex relationships between different factors that can potentially influence AC.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.295
GPT teacher head0.473
Teacher spread0.178 · 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 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

Citations5
Published2020
Admission routes1
Has abstractyes

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