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Record W2129936729 · doi:10.19173/irrodl.v16i4.2175

Usability Evaluation of the Student Centered e-Learning Environment

2015· article· en· W2129936729 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2015
Typearticle
Languageen
FieldComputer Science
TopicUsability and User Interface Design
Canadian institutionsnot available
Fundersnot available
KeywordsUsabilityComputer scienceWeb usabilityUsability engineeringUsability labSystem usability scaleHeuristic evaluationInterviewPluralistic walkthroughCognitive walkthroughMultimediaWorld Wide WebHuman–computer interaction

Abstract

fetched live from OpenAlex

<p>Student Centered e-Learning Environment (SCeLE) has substantial roles to support learning activities at Faculty of Computer Science, Universitas Indonesia (Fasilkom UI). Although it has been used for about 10 years, the usability aspect of SCeLE as an e-Learning system has not been evaluated. Therefore, the usability aspects of SCeLE Fasilkom UI as a learning support system and what makes SCeLE Fasilkom UI an ideal system are not known yet. Motivated by the mentioned conditions, the researchers found an urge to conduct a usability evaluation in order to propose a set of recommendation for SCeLE usability improvement, based on usability evaluation reflecting both students and lecturers experience as user.</p><p>In this present research, the usability testing was conducted for SCeLE, targeting learning activities underwent by undergraduate students at Fasilkom UI, in the form of blended mode online learning. The data collection stage in the usability testing was performed by distributing questionnaire to students and interviewing several lecturers and students. The collected data was then analyzed and interpreted to obtain usability problems and solution alternatives. The quantitative data was analyzed using central tendency as reference, while the qualitative data was analyzed using theme-based content analysis. Data interpretation was performed by determining how to handle each kind of data based on the theme, and classifying each of the identified usability problem based on its severity rating.</p><p>The recommendations constructed to solve the usability problems were based on solution alternatives from the analyzed data supported by literature study. The present research comes up with seven main recommendations and an extra recommendation. The main recommendations are solutions to tackle the identified usability problems, while the extra recommendation is not directly related to any of identified usability problems, but was considered potential to improve the SCeLE usability.<br /><br /></p>

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.

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)0.026
metaresearch head score (Gemma)0.005
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 score0.286
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0260.005
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 science0.0030.002
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 head0.282
GPT teacher head0.474
Teacher spread0.192 · 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