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Record W4321208134 · doi:10.51357/jdll.v2i2.205

Examining the Discord Application in Higher Education: A Systematic Review of the Literature

2023· review· en· W4321208134 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Digital Life and Learning · 2023
Typereview
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsAsynchronous communicationHigher educationDistractionSystematic reviewAsynchronous learningEmpirical researchPsychologyComputer sciencePedagogyTeaching methodCognitive psychologyPolitical scienceCooperative learningTelecommunicationsSynchronous learning

Abstract

fetched live from OpenAlex

The ability to communicate is critical for enhancing the learning experience. Integrated messaging applications, such as Discord, are critical with the increased diffusion of digitally mediated courses. The Discord application allows educators and students to readily communicate learning experiences within asynchronous and synchronous environments by sending messages, images, links, audio, and video. Our systematic review sought to understand the benefits and challenges of using the Discord application in higher education courses. We summarized research from eight empirical studies within global higher education. Benefits of using Discord included ease of access, user-friendliness, useful communication and interaction, and increased social presence leading to enhanced student learning outcomes. Challenges included the increased potential for distraction and technology issues, both of which can inhibit engagement. Practical recommendations and future research recommendations regarding the use of Discord are provided.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.506
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.069
GPT teacher head0.372
Teacher spread0.303 · 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