Development of a Web-Based Intervention Course to Promote Students’ Well-Being and Studying in Universities: Protocol for an Experimental Study Design
Bibliographic record
Abstract
BACKGROUND: The decline in the well-being among university students well as increasing dropouts has become a serious issue in universities around the world. Thus, effective ways to support students' well-being and their ability to study are highly needed. OBJECTIVE: The purpose of this study was to build an intervention course for university students, which promotes both students' well-being as well as their learning and study skills, and to describe the experimental study design that explores the effects of this intervention course. METHODS: Research has shown that psychological flexibility has a great effect on the well-being as well as the study skills of students pursuing higher education. The basis of our intervention course was to promote psychological flexibility and students' study skills with the help of peer support and reflection. RESULTS: This course was offered as a voluntary course to all the students at the University of Helsinki twice during the academic year 2020-2021. The first course was from October to December and the second course was from January to March. This course was advertised in fall 2020 through social media and by different student organizations and program leaders at different faculties of the University of Helsinki. As of October 2020, we enrolled 566 students comprising 310 students for the course in fall 2020 and 256 students for the course in spring 2021. Of the 256 students who enrolled in the second course, 170 students voluntarily participated in this study and they answered the questionnaires, including all the measures, simultaneously with the participants in the first group and thus served as the control group. The effect of this course will be measured with multiple data, including questionnaire data, reflective journals, and physiological data of well-being with a longitudinal experimental design. This research very strictly follows the ethical guidelines drawn up by the Finnish National Board on Research Integrity. We expect to publish the results of this study in fall 2021 at the latest. CONCLUSIONS: We argue that a web-based, 8-week intervention course, which promotes both student well-being and their study skills, is a good way to support students pursuing higher education, and both aspects should be considered when supporting university students. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/23613.
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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 | 0.027 | 0.021 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.035 | 0.007 |
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".