Self-Regulation and “Time Off”: Evaluations and Reflections on the Development of a Blended Course
Bibliographic record
Abstract
Changes in both the landscape of education and digital technology are giving rise to interesting, innovative, and potentially effective pedagogical possibilities. As educators of the 21st century, we are witnessing continuous changes in the way we teach as well as the way students learn. This study is a part of an ongoing research program aimed at evaluating the pedagogical effectiveness of blended teaching. More specifically, this paper aims to describe some of our reflections as we developed, delivered, and carried out an evaluation of a university course taught using a blended format. Undergraduate students (n=109) in a fourth-year capstone course participated in this study. We report on the students’ perceptions of the effectiveness of the delivery method of the course, while focusing on the struggles they encountered, including difficulties keeping up with the course content, particularly on the weeks where the lecture was online, as well as a struggle to stay organized and connected with their peers and their assignments. Self-regulation turned out to be a major determinant of success in this type of course. We conclude with suggestions to improve students’ social and academic experiences as they navigate learning in a digital world. Les changements survenus à la fois dans le paysage de l’éducation et dans la technologie numérique donnent naissance à des possibilités pédagogiques intéressantes, innovatrices et potentiellement efficaces. En tant qu’éducateurs du XXIe siècle, nous assistons à des changements continus dans la manière dont nous enseignons ainsi que dans la manière dont les étudiants apprennent. Cette étude s’inscrit dans le cadre d’un programme de recherche en cours qui a pour objectif d’évaluer l’efficacité pédagogique de l’enseignement hybride. Plus spécifiquement, cet article vise à décrire certaines de nos réflexions au fur et à mesure que nous élaborons, livrons et exécutons l’évaluation d’un cours universitaire enseigné selon un format hybride. Des étudiants de premier cycle (n=109) inscrits dans un tout dernier cours de quatrième année ont participé à cette étude. Nous présentons un rapport sur la manière dont les étudiants ont perçu l’efficacité de la méthode employée pour enseigner ce cours, tout en mettant l’accent sur les problèmes qu’ils ont rencontrés, y compris les difficultés à faire face au contenu du cours, en particulier durant les semaines où les cours magistraux étaient présentés en ligne, ainsi que sur leurs difficultés à rester organisés et connectés avec leurs camarades de classe et avec leurs devoirs. Il s’avère que l’autorégulation est un élément important pour la réussite de ce type de cours. Pour conclure, nous présentons des suggestions pour améliorer l’expérience sociale et académique des étudiants dans leur parcours de l’apprentissage au sein d’un monde numérique.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".