MétaCan
Menu
Back to cohort
Record W4281567304 · doi:10.14705/rpnet.2022.56.1376

Student-centred learning and formative assessment: a possible answer to online language and literature teaching and learning

2022· book-chapter· en· W4281567304 on OpenAlexaffabout
Miao Li

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsFormative assessmentContext (archaeology)Student engagementPsychologyMathematics educationPedagogyComputer science

Abstract

fetched live from OpenAlex

The University of Calgary transitioned to online teaching in March 2020. Subsequent months saw instructors working to overcome the personal, technological, and pedagogical challenges involved in this. Central to those discussions was the need to increase student engagement and develop effective assessment formats. Based on student feedback and personal reflection, the adoption of a synchronous learning environment fostering student-centred learning and formative assessment was considered appropriate in the context of online language teaching and learning. It responded to students’ increased stress levels due to the lack of face-to-face communication and tackled the issues of student attention span and engagement, as well as academic integrity. This paper starts with a brief discussion of factors that affect students’ behavioural patterns and academic performances during online teaching and learning. It then presents five activities and assessments used in language teaching and examines the effectiveness of these activities in improving student engagement and their retention of course material.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.762
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.369
Teacher spread0.345 · 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 designQualitative
Domainnot available
GenreOther

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

Citations1
Published2022
Admission routes2
Has abstractyes

Explore more

Same topicHigher Education Practises and EngagementFrench-language works237,207